For Q1 2025, Marvell is forecasting total revenues of $1.15 billion with weak demand expected to continue in the carrier, enterprise and consumer segments. However, the company expects that revenues in these segments will stabilise after Q1 2025, with a recovery expected in H2 2025.

Data Centre Segment

Data centre revenue reached $765 million in Q4 with cloud services being a significant contributor while revenue from AI-driven optics exceeded $200 million (Exhibit 1). In fact, data centre revenue – particularly AI-driven optics – accelerated throughout the year, increasing from around one-third of total revenue in Q1 to more than half at the end of Q4. Clearly, the acquisition of Inphi is proving to be a major strategic asset.

Demand for its cloud-optimized silicon solutions is up, driven by the increase in AI and accelerated computing investment. The chip vendor has successfully executed several 5nm designs in the last two years and expects initial shipments for its two 5nm AI compute programs to start in Q1 2025. Marvell believes that it is on track for a very substantial ramp-up in H2 2025.

Marvell reported that it is also heavily engaged with cloud customers on new 3nm opportunities and remains confident of its 3nm funnel and design win rates. In addition, AI is increasing the cadence of new chip releases, and this plays well to Marvell’s strength as a key partner for its cloud customers with a proven ASIC platform.

The company also announced an extension of its long-standing collaboration with TSMC to develop the industry’s first technology platform to produce 2nm chips optimized for accelerated infrastructure. This new platform will enable Marvell to deliver substantial advancements in performance, power and area, which will be critical for next-generation accelerated workloads.

Carrier and Enterprise Networking

Carrier and enterprise markets have been experiencing a period of weak industry demand for several months. As a result, revenues at both segments were down sequentially in Q4. Marvell expects further sequential declines in Q1 of approximately 50% for carrier networking and 40% for enterprise. Beyond Q1, Marvell expects these markets to stabilise and forecasts a recovery in fiscal H2 2025.

At their peak during the pandemic, the carrier and enterprise networking market contributed a total of $2.5 billion to Marvell’s revenue. Looking forward, Marvell expects both of these markets to contribute over $1 billion each in revenue on an annual basis once demand normalizes. Both these businesses have very long product life cycles – typically seven years in production. In particular, Marvell stresses that it has not lost business or market share, with the lower revenues being attributable to demand softness and inventory corrections. In fact, the company maintains that its up-coming product upgrades will drive up revenues as both these cyclical markets recover over the next few years.

Analyst Viewpoint

Marvell is a critical enabler of accelerated infrastructure for AI with a full suite of solutions across data centre interconnect, switching and compute plus in-house expertise to integrate all these technologies together. Essentially, the company is a one-stop shop for data centres. As a result, Counterpoint Research believes that the company is well positioned to capitalise on the massive AI-based technology build-out as it continues to gain momentum during 2024.

Growth in generative AI applications is driving cloud providers to build new data centres. As a result,  Marvell is experiencing an increase in design wins in AI, custom silicon and networking optics. This is providing good opportunities, particularly in custom silicon. However, this is not a zero-sum game with both the merchant and custom silicon expected to benefit. Also, the on-going transformation of data centre architectures is resulting in increased investment in inferencing, which drives more bandwidth between data centres, resulting in more demand for Marvell’s data centre interconnect products.

In Q1 of fiscal 2025, Marvell expects continued sequential growth in its data centre revenues with initial shipments of its cloud-optimized silicon programmes for AI complementing its electro-optics products. Carrier, enterprise and consumer markets are expected to bottom out in Q1 –  representing a cyclical trough – which limits any downside. With a healthy gross margin of  42.1% and focus on high-growth areas (and clear view of demand for fiscal 2025 and 2026), Counterpoint Research believes that Marvell is set for recovery and a profitable fiscal 2025.

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5. LeapFrog Semiconductor develops RISC-V based AI-enhanced DSP for Wireless Infrastructure

The post Accelerating AI Revenues Plus Recovery in Non-AI Core Markets Signals Return to Profit for Marvell in Fiscal 2025 appeared first on Counterpoint.

Open RAN’s Massive MIMO Challenge

Solving the massive MIMO performance deficit is one of the key issues inhibiting an industry wide transition to open RAN. This challenge must be resolved before mainstream adoption of massive MIMO radios can occur. However, this will require a new breed of merchant silicon solutions designed specifically to efficiently process real-time, latency-sensitive Layer-1 workloads such as beamforming, channel coding, etc.

In early 2023, a number of vendors demonstrated alternatives to Intel’s x86 platform at MWC in Barcelona based on ASICs, GPUs as well as RISC-V architectures. Late last year, an interesting new contender – LeapFrog Semiconductor – appeared on the market. 

LeapFrog’s RISC-V Based Modular, Customizable And First Truly Software Defined Layer-1 Solution

LeapFrog Semiconductor is an early-stage fabless semiconductor company focused solely on developing next-generation Layer-1 silicon and software solutions for the mobile infrastructure and enterprise markets. Founded in 2020, it is funded and staffed by seasoned semiconductor veterans.

The San Diego-based start-up has developed a unique AI-enhanced DSP-based silicon platform based on the RISC-V architecture as well as a Network-on-Chip silicon design. The  result is a multi-core, distributed 5G RAN silicon platform, which is modular, customizable and flexible, thus creating the first truly software defined, AI-enhanced RAN solution.

LeapFrog’s DSP Chip

Known as the LeapFrog Processing Unit (LPU), LeapFrog’s DSP core uses a specialized Instruction Set Architecture (ISA) developed in-house that natively supports fine-grain parallelism. This means that Layer-1 computation is broken down into a large number of small tasks, resulting in a high level of parallelism. Together with its programmable NOC architecture which minimises communication and synchronization overheads, LeapFrog’s Layer-1 chip results in several unique benefits:

• Power and area efficient design – LeapFrog claims that its SoC is significantly smaller than rival designs and boasts single-digit (<10W) power consumption.
• Software-based Layer-1 solutions – LeapFrog’s RU and DU Layer-1 solutions are 100% software-based and are thus fully programmable, with no requirements for hardware-based accelerators.
• AI-enhanced L1 chip solution – the LeapFrog chip includes in-line processing of AI and L1 algorithms, which includes AI-based channel estimation and other L1 algorithms. This results in a low-latency chip solution and hence improved RAN system performance.
• Tile and chiplet-based silicon design – resulting in a scalable, customizable and modular design which can be optimized for different deployment scenarios. For example, chiplets can be combined to make different functions such as L1, I/O, CPU, etc.

In contrast, many rival open RAN chip designs currently under development are based on coarse-grained parallelism, thus necessitating the use of hardware accelerators or hard IP blocks. These designs are not as scalable as LeapFrog’s solution and offer very little flexibility with respect to changes in the computation logic. As a result, a new chip tape-out would be needed if any architectural or logic changes are required.

LeapFrog Network-on-Chip (LNOC)

LeapFrog has also developed a highly power efficient, programmable LeapFrog Network-on-Chip (LNOC) chip design which connects multiple LPUs to create a multi-core, distributed 5G RAN silicon platform. Leveraging innovations in chiplet and Die2Die (D2D) technologies, this results in a highly scalable, modular and flexible chip design complying with all 5G O-RAN specifications (Exhibit 1).

Exhibit 1: LeapFrog Semiconductor’s RISC-V 5G Layer 1 Silicon Architecture

LeapFrog believes that its LNOC design is currently the only chiplet-based 5G open RAN chip platform with a fully software-based RU and DU L1 solution that can be easily customized to suit different 5G deployment scenarios.  In addition, the company claims that its AI-enhanced L1 solution results in 50% to 100% better system performance and 10x lower cost and power compared to existing open RAN RU and DU platforms. Another benefit is that software development and testing can be performed on an FPGA platform, which is then transferred to LeapFrog’s silicon platform. This allows a faster time-to-market compared to alternative designs from other vendors. 

Target Markets

LeapFrog is targeting multiple markets with its unique LPU design. Chiplet based productization allows the same platform to scale all the way from small cell, fixed wireless access (FWA) to macro cell RU and DU market with a major focus on massive MIMO networks. Potential customers include small and large 5G infrastructure vendors, greenfield CSPs as well as hyperscalers. The company is also pursuing an IP licensing model for its general-purpose DSP targeting consumer/industrial IoT modems, wireless CPEs/gateways, automotive connectivity/sensor fusion as well as mobile handset modems. The IP is ready on FPGA now and was recently demonstrated at the India Mobile Congress and the RISC-V Summit in 2023. The chip design was tested in H2 2023 and delivery of samples to customers is expected to start in Q2 2024.

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The post LeapFrog Semiconductor develops RISC-V based AI-enhanced DSP for Wireless Infrastructure appeared first on Counterpoint.

Release 19 will be followed by Release 20, the first 3GPP release for 6G studies. During the next few years, 5G Advanced will continue to evolve within 3GPP while the standardization of 6G officially starts to ramp up in parallel. Release 18 is expected to be finalized in mid-2024 with Release 19 following in late 2025.

Performance Enhancements

5G Advanced continues to push the spectral efficiency limits and coverage in both sub-7GHz and millimetre wave spectrum. In addition to continued enhancements to massive MIMO radios and mobility, Release 19 provides advancements for new use cases such as XR and Non-Terrestrial Networks.

• Massive MIMO Radio – Release 18 introduced improvements to massive MIMO uplink and downlink throughput. Release 19 will boost capacity further by improving multi-user MIMO, which enables more UEs to share the same time and frequency resources.
  Release 19 will also enable the cost-efficient realization of distributed transmitters and receivers, thus improving signal quality. This is an important step towards enabling fully distributed MIMO (D-MIMO) systems. Other enhancements include 5G beam management with UE-initiated measurement reporting, thus resulting in faster beam selection.
• Mobility – 5G Advanced introduces a new handover procedure known as low-layer (i.e. L2) triggered mobility (LTM). In Release 18, LTM is supported between cells served by the same gNB. In Release 19, the LTM framework will be extended to support handover between cells served by different gNBs.
• XR and the Metaverse – Release 19 builds on the low latency and power saving features of Release 18 by enabling higher XR capacity by adding improved uplink and downlink scheduling using packet delay information.
• Non-Terrestrial Networks – 5G Advanced combines terrestrial and satellite communications under one standard for the first time. Release 19 will build on the enhancements introduced in Release 18 with a focus on increasing satellite downlink coverage, introducing UEs with higher output power and providing Redcap device support. It will also investigate whether additional support is required for regenerative payloads.

With a long history as an innovator in satellite communications, San Diego-based Qualcomm is leading the charge in non-terrestrial networking. In addition to its contributions to 5G NR NTN and 5G IoT NTN standards, the vendor recently launched two modems: the 212S modem, a satellite-only IoT modem and the 9205S modem. The latter connects to both terrestrial cellular and satellite networks and includes a Global Navigation Satellite Systems (GNSS) chip to provide location data.

Role of AI/ML in 5G Advanced

AI/ML will become a key feature of 5G networks with numerous applications ranging from network planning and network operations optimization to full network automation. Another important application is the use of AI/ML to improve the performance and functionality of the 5G air interface.

3GPP studied the use of AI/ML in the air interface in Release 18 and defined three use cases: channel state feedback (CSF) information, beam management and positioning. Based on the conclusions of Release 18 studies, Release 19 will specify a general AI/ML framework, i.e. actual specifications to support the above three use cases as well as specific support for each individual use case. Release 19 will also explore new areas in the AI/ML air interface such as mobility improvement and AI/ML-related model training, model management and global 5G data collection.

AI/ML is another major focus for Qualcomm. The company has dedicated significant technical resources to develop full-scale demonstrations of the three Release 18 defined use cases. For example, it recently demonstrated CSF-based cross-node machine learning involving E2E optimization between devices and the network. This reduces device communication overheads resulting in improved capacity and throughput. Qualcomm has also demonstrated the use of AI/ML to improve beam prediction on its 28GHz massive MIMO test network and is heavily involved in positioning technologies. For example, it has showcased its outdoor precise positioning technology, which uses multi-cell roundtrip (RTT) and angle-of-arrival (AoA) based technologies, as well as its RF finger printing technology operating in an indoor industrial private network.

Over the next few months, 3GPP will continue exploring the applicability of AI/ML based solutions for other use cases such as load balancing between cells, mobility optimization and network energy savings. For example, there will be support for conditional Layer 2 mobility in Release 19 and a new study item targeting new use cases designed to improve coverage and capacity optimization, such as AI-assisted dynamic cell shaping.

Enhancing Device and Network Sustainability

5G Advanced focuses on sustainability and introduces energy-saving features for devices and networks as well as exploring end-to-end energy saving opportunities that benefit devices. There are also improved features for RedCap and the study of ambient IoT as a new device type.

• Power-optimized devices – Releases 18 and 19 build on existing energy saving features, for example, a new low-power wakeup signal (LP-WUS). A low-complexity, power-optimized receiver is specified to monitor low-power wake-up signals from the network which only wakes-up the main radio when data is available at the device. This avoids the significant power consumption required to keep the main radio monitoring control signals from the network.
• Ambient IoT – enables new use cases enabled by very-low power devices that harvest energy from the ambient environment, for example, RF waves. Release 19 will investigate new architectures for ambient IoT devices and will include the development of a harmonized specification. Numerous use cases will be studied, including smart agriculture, industrial wireless sensor networks, smart logistics, warehousing, etc.
• Network energy savings – 5G Advanced reduces network energy consumption by dynamically adjusting the network’s operation based on feedback from the device, i.e. shutting down parts of the network when idle and transmitting less power depending on the overall traffic load or using more efficient antennas.

Setting The Stage For 6G

Although Release 19 will be the last release focused on 5G, it will also include some longer-term technologies that will become the foundation of 6G, thus setting the direction for Release 20. For example, Integrated Sensing and Communications (ISAC), which combines wireless communications with RF sensing, will enable a raft of new position-based use cases. Release 19 will study channel characteristics suitable for the sensing of various objects, including vehicles, UAVs and humans. Full duplex, another 6G technology, allows  transmitters and receivers to operate simultaneously on the same frequency, potentially resulting in a doubling of network capacity. Release 19 will study sub-band full duplex, a type of full duplex, which will improve capacity and latency, particularly for the uplink. Release 19 will also include channel model studies for the upper mid-band spectrum (7-16GHz), which will be supported by “Giga-MIMO” in the 6G timeframe, in order to enable wide-area coverage in this higher band.

Whereas AI/ML is a key pillar of 5G Advanced, it will be a core foundational technology of 6G and will underpin the key features that will make 6G revolutionary. For example, 6G will start to move away from the traditional, model-driven approach of designing communication systems and transition towards a more data-driven design. Indeed, it is likely that the 6G air-interface will be designed to be AI-native from the outset, thus signalling a paradigm change in the way communication systems are designed.  An AI-native air interface could offer many benefits. For example, it could refine existing communication protocols by continuously learning and improving them, thereby enabling the air interface to be customized dynamically to suit local radio environments.

Analyst Viewpoint

Despite huge investments in 5G, network operators are still reliant on revenues from traditional voice and broadband data services and are struggling to increase ARPU. Clearly, operators will need to leverage the capabilities of 5G Advanced in order to realize the full potential of 5G.

Although Release 19 includes a focus on new 6G focused technologies, Counterpoint Research believes that 5G is currently only at the midpoint of its development. Over the next few years, 5G Advanced will offer a plethora of new features to improve device and network capabilities and lower OPEX costs. It will also offer innovative new use cases thus enabling operators to generate new revenue streams. Together, this should enable operators to drive up ARPU of existing customers, lower OPEX costs and to acquire new B2B customers across several verticals.

However, 5G Advanced requires operators to deploy 5G SA cores across their networks. While around 92% of all 5G devices support 5G SA, only 21% of operators have started to invest in 5G SA. Of these, only 47 have commercially deployed 5G SA cores in their networks to date[1]. In the short-term, operators need to urgently prioritize 5G SA core deployment in order to fully benefit from their 5G investments.

[1] Source: GSA, 5G Standalone, October 2023

This blog is sponsored by Qualcomm.

The post 3GPP’s Release 19 Continues 5G Advanced Standardization, Sets The Stage For 6G appeared first on Counterpoint.

Overcoming Operator Challenges

To survive financially and benefit from their 5G investments, operators need to develop new revenue streams while reducing OPEX costs. To achieve this, they need to radically transform the way they operate their networks. Instead of a fixed architecture, a fully flexible and agile service platform is required with the capability of delivering a wide variety of services on-demand. This means that networks need to be cloud-based, software defined, highly programmable and ultimately completely automated. By making their networks agile, operators will be able to deliver a huge variety of services with user experiences and connectivity dynamically tailored to individual use cases, or even individual users. Over the next few years, Counterpoint Research believes that AL/ML driven automation will play a critical role in facilitating this business model transformation, allowing operators to develop new revenue streams while significantly reducing OPEX costs.

Transition to L4 Automation

Autonomous networks are networks that can run with minimal (and ultimately zero, i.e. zero-touch) human intervention while leveraging technologies such as AI, machine learning and edge computing. Operators have already started the journey to automation, which they plan to implement in stages. For example, most Tier-1 operators have reached either Level 2 or Level 3 and many plan to reach Level 4 automation by the end of 2025/26.

Compared to L3 automation, L4 offers many new features and capabilities. With L3 networks, O&M updates are implemented into the network manually and run to gauge the network’s response. This typically involves multiple iterations. In contrast, L4 automation offers the capability of using a digital twin, i.e. a virtual or digital copy of the physical network. This is essentially a simulation environment which enables network changes to be run hundreds of times in isolation, enabling the optimum parameters to be identified before they are implemented into the physical network.

L4 automation also enables improved data collection processes allowing operators to have greater visibility into the network. For example, L4 offers the ability to collect more data from a base station compared to L3. L4 can also collect data more frequently. As a result, L4 automation can offer predictive and preventative capabilities, where potential faults are identified and rectified, thus ensuring that base stations are always online. Operators typically do not want to implement automation for everything, with most focusing on two processes: network deployment and fault monitoring and maintenance.

Huawei’s RAN Digital Twin

Huawei has developed a RAN Digital Twin System (RDTS) which is used in conjunction with its IntelligentRAN architecture to leverage the new capabilities of L4 automation. Central to its operation are the following four new innovative features:

• Improved Data Collection – it typically takes around 15 to 30 minutes to collect historical data on a conventional mobile network. By implementing L4, Huawei is able to do this in around 10-200ms, i.e. effectively in real-time.
• Predictive O&M Capabilities – maintenance costs can be significantly reduced by using RDTS. For example, RDTS enables operators to predict equipment failures due to overheating boards and detect faults in optical modules and back-up power supplies by up to seven days in advance. Faults can thus be rectified before they disrupt network operations. In contrast, a conventional network may require 4+ hour post processing after a fault is rectified in the field.
• Transition from KPIs to SLAs (Service Level Agreements) – using the RDTS enables operators to offer SLAs to their customers, resulting in new business opportunities and higher revenues.
• Single To Multiple Target Optimization – conventional networks can only handle single target optimization, for example, energy efficiency. However, by using the RDTS, Huawei’s IntelligentRAN is able to perform multiple target optimization, for example, simultaneously optimizing energy efficiency and user experience.

IntelligentRAN L4 i-series solutions

In early 2023, Huawei launched its 3-layer, hierarchical IntelligentRAN architecture which has been deployed to date by more than 30 operators worldwide. IntelligentRAN enables the key capabilities of L4 autonomous networks to be realised. This includes intent-driven networking, intelligent sensing, multi-target decision optimization and proactive/predictive O&M. At its recent Global Mobile Broadband Forum in Dubai, Huawei announced three additional L4 i-series solutions:

• iLiveStreaming – by means of dynamic allocation of time, frequency and space resources coupled with intelligent SLA trend prediction, Huawei is able to offer deterministic experience assurance delivering a reliability higher than 95% for uplink livestreaming.
• iKeyEvent – using spatiotemporal traffic prediction technology, iKeyEvent enables network risks to be identified and hence predicted and monitored at big events such as major sports meetings. Emergency plans are then generated automatically and the control loop-closed within seconds.
• iPowerStar – uses intelligent algorithms to manage end-to-end energy consumption across multiple network channels, including the time, space, frequency and power domains. Multi-target optimization helps operators minimise energy consumption without compromising on network performance or user experience. Huawei claims that iPowerStar reduces carbon emissions by 30%.

Operator Examples

In recent months, Huawei has demonstrated the benefits of using the RDTS system operating within its IntelligentRAN architecture with several of its operator partners. For example:

• In the Middle East – Huawei demonstrated how the RDTS eliminates the need to perform multiple iterations on a live network (typically 20+ times with conventional O&M over 20 days) to just once with a RDTS network. Huawei claims that this enables operators to deploy new features and services ten times faster than with conventional O&M.
• In China – by using Huawei’s RDTS in conjunction with its IntelligentRAN system, a Chinese operator was able to reduce the number of O&M site visits from 29,000 to 780 visits per year. According to Huawei, this reduces maintenance inspection and passive analysis costs by up to 90%.
• In Europe – guaranteeing the performance of a live streaming service is very challenging. Prior to using RDTS, an European operator was able to get a 5 times package gain compared to the traditional streaming package. However, by implementing Huawei’s Live Streaming Solution, the operator was able to increase its SLA assurance from 50% to 90% enabling it to generate $200 per hour per package compared to the original $40 live streaming package. This certainty of guaranteed service experience will open up new business opportunities for operators.

Viewpoint

The business models of many network operators risk become unsustainable unless they fully embrace automation. L4 autonomous networks will allow operators to deliver an experience that is far better than with previous generations of mobile networks. With L4, intent-driven networking replaces policy-based network management, deterministic service assurance replaces best-efforts approaches while proactive O&M (leveraging predictive/preventive capabilities) is used instead of responsive O&M. Together, these new capabilities will enable operators to significantly reduce OPEX costs as well as generate new revenues.

However, there are still challenges ahead. Standards, or specifically a lack of collaboration among standards bodies and open-source groups, is perhaps the biggest challenge. In particular, the industry needs to define data standards and formats. Another challenge is transforming company culture and skills, for example, with respect to network operations personnel. Linked with culture and skills is a lack of a common understanding of key technologies: for example, is there a precise, industry agreed definition for intent-driven management? The development of open APIs will also be very important. Collaboration with industry and ecosystem partners, including device manufacturers, equipment suppliers and developers will be essential in order to bring the economies of scale needed to benefit all players.

This blog is sponsored by Huawei.

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The post Rapid Transition To L4 Automation Key To Successful 5G Network Monetization appeared first on Counterpoint.

• 4G/5G Spectrum – WRC-23 identified spectrum for 4G and 5G which will be crucial for expanding broadband connectivity and developing mobile services. The new spectrum includes the 3,300-3,400MHz, 3,600-3,800MHz, 4,800-4,990MHz and 6,425-7,125MHz frequency bands in various countries and regions.In particular, the decision  to set aside the 6.425-7.125GHz band for licensed, mobile operations and to harmonise this band is very important for the mobile community. The 6GHz band is the only remaining midband spectrum currently available to respond to the data traffic growth in the 5G-Advanced era and is critical for manufacturers of the 6GHz equipment ecosystem.However, a  compromise was adopted in ITU Region 1 and Region 3, which means that the 6,425-7,125MHz band can also be used by Wi-Fi. Individual administrations will have the freedom to decide what happens in this frequency range.
• HIBS spectrum – WRC-23 also identified the 2GHz and 2.6GHz bands for using high-altitude platform stations as IMT base stations (HIBS) and established regulations for their operations. This technology offers a new platform to provide mobile broadband with minimal infrastructure using the same frequencies and devices as IMT mobile networks. HIBS can contribute to bridging the digital divide in remote and rural areas and maintain connectivity during disasters.
• Low-bands – WRC-23 also defined mobile use of more low-band spectrum in the 470-694MHz band in the EMEA region (Europe, the Middle East and Africa).In the UK, Ofcom has already released spectrum down to the 700MHz (694-790MHz) band for use by mobile networks, by shifting Digital Terrestrial TV (DTV) services into the 600MHz band and lower (starting around 470MHz). DTV is going to be around for a number of years yet, but once it does end (i.e. once people have shifted to broadband-based TV) then it looks increasingly likely that the bands will be used for mobile.

• 6G Spectrum – prior to the start of WRC-23, the ITU adopted a resolution intended to guide the development of a 6G standard. During the conference, regulators agreed to study the 7-8.5GHz band for 6G in time for the next ITU conference in 2027. That spectrum band aligns with proposals from major incumbents for early 6G operations at spectrum bands between 7GHz and 20GHz.

The full version of this insight report, including a complete set of analyst takeaways, is published in the following report, available to clients of Counterpoint Research’s 5G Network Infrastructure Service (5GNI).

Report: Highlights from ITU’s WRC-23 Meeting In Dubai

Table of Contents

• Key Highlights
• Mobile Agreements
• 5G Spectrum
• 6G Spectrum
• Terrestrial Broadcast Agreements
• Satellite Agreements
• Other Agreements
• Analyst Viewpoint

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The post Selected Highlights from ITU’s WRC-23 Meeting In Dubai appeared first on Counterpoint.

In addition to the incumbent operators, there are a number of new players such as AST SpaceMobile and Lynk Global. AST SpaceMobile has partnered with Rakuten Mobile and currently has one operational satellite in-orbit. It has been granted preliminary experimental licenses in Japan and in the US. Meanwhile Lynk launched a limited commercial “store-and-forward” service using three satellites in April. Both companies plan to launch full constellations over the next few years.

The Mobile Satellite Services (MSS) market has historically been a niche market due primarily to the fact that MSS is based on proprietary technologies. However, 3GPP is working with the satellite industry on a global standardized solution, called 5G Non-Terrestrial Networks (NTN). 5G NTN will enable seamless roaming between terrestrial and satellite networks, using largely standard cellular devices, i.e., eliminating the need for proprietary terminals and fragmented satellite constellations. This could dramatically increase the addressable market for mobile satellite services.

5G Non-Terrestrial Networks (NTN)

With the emergence of new Satellite-to-Phone services, there is now a widespread industry push to deploy NTN-based satellite networks as this would benefit the satellite industry and the wider mobile industry. However, 3GPP has been working on NTN for some time. For example, there has been an ongoing study on 5G NTN since 3GPP Release 15, while in 2022, 3GPP introduced two parallel workstreams in its Release 17 specifications addressing 5G satellite-based mobile broadband and low-complexity IoT use cases:

• NR-NTN (New Radio NTN) – adapts the 5G NR framework for satellite communications, providing direct mobile broadband services as well as voice using standard apps. This will enable 5G phones operating on dedicated 5G NTN frequencies and existing sub-7GHz terrestrial frequencies to link directly with Release-17 compatible satellites. Release 17 also includes enhancements for satellite backhaul and the inclusion of 80MHz MSS uplink spectrum in L-band (1-2GHz) plus a similar amount of downlink spectrum in S-band (2-4GHz).
• IoT-NTN – provides satellite support for low-complexity eMTC and NB-IoT devices, which expands the coverage for key use cases such as worldwide asset tracking (for example, air freight, shipping containers and other assets outside cellular coverage). IoT-NTN is designed for low data rate applications such as the transmission of sensor data and text messages.

Release 17 established the NR-NTN and IoT-NTN standards while the upcoming 5G Advanced Release 18 will introduce new capabilities, coverage/mobility enhancements and support for expanded spectrum bands. For example, there are plans to extend the NR-NTN frequency range beyond 10GHz by adding Fixed Satellite Services (FSS) spectrum in the 17.7-20.2GHz band for downlink and 27.5-30.0GHz for uplink.

Satellite IoT

Traditional mobile satellite operators such as Inmarsat, Iridium and Globalstar have been offering M2M/IoT type services for many years targeting various industry verticals, ranging from agriculture, construction and oil and gas to maritime, transportation and utilities. Some of the traditional FSS players, such as AsiaSat, Eutelsat and Intelsat, also offer M2M/IoT services over Ku or Ka bands.

Another player with a long history in satellite communications is San Diego-based chip vendor Qualcomm. The company was a founding partner and key technology provider in Globalstar and also developed satellite-based asset tracking service OmniTRACS. Qualcomm is still heavily involved in the satcom business and earlier this year announced Snapdragon Satellite, its Satellite-to-Phone service. More recently, it announced the availability of two Release 17 compatible GEO/GSO IoT-NTN satellite modems launched in collaboration with US-based Skylo, a NTN connectivity service provider, that enables cellular devices to connect to existing, proprietary satellite networks:

• Qualcomm 212S Modem – a satellite-only IoT modem designed to enable stationary sensing and monitoring IoT devices to communicate with NTN-based satellites. The chipset is an ultra-low power device and can be powered from solar panels or supercapacitors.
• Qualcomm 9205S Modem – enables IoT devices to connect to both terrestrial cellular and satellite networks and has integrated GNSS to provide location data. Typical applications include industrial applications requiring always-on, hybrid terrestrial and satellite connectivity for tracking assets such as agricultural machinery, shipping containers, livestock, etc.

Both devices are designed for low-power, cost optimized applications and support the Qualcomm Aware cloud platform, which provides real-time asset tracking and device management in off-grid, remote areas for IoT.

Most of the major chip vendors, such as MediaTek, Qualcomm and Sony Semiconductors, have already developed Release 17 compatible chipsets. This means that satellite-compliant 5G IoT devices could be available commercially by the end of 2023 and should become commonplace in 2024.

NTN Satellite Operators

Only a few NTN-based satellites have been launched to date. A noteworthy example is Spanish LEO operator Sateliot, the first company to deploy satellites complying with 3GPP’s Release 17 IoT-NTN standard. Sateliot currently has two satellites in orbit and recently carried out a successful roaming test between its satellite network and Telefonica’s 5G terrestrial network using an IoT device with a standard SIM card. Sateliot plans to start commercial activities in 2024. Ultimately, the company hopes to launch a total of 250 nanosatellites, which will enable it to offer global 5G IoT-NTN services.

No satellite operator presently supports 3GPP’s Release 17 NR-NTN standard for voice and data. Although AST SpaceMobile and Lynk Global have demonstrated two-way satellite-to-5G terrestrial communications, neither uses the NR-NTN standard, although they have plans to test the NR-NTN standard.

Satellite Déjà Vu?

Over two decades ago, the mobile satellite industry invested billions to launch a number of ground-breaking LEO-based voice and narrowband data constellations. Only a handful survived and even fewer have prospered. Will history repeat itself?

Although there are some parallels, Counterpoint Research believes that there are also some important differences this time. During the past 20 years, satellites have become much smaller, more capable and less expensive. Some of these satellites are based on CubeSat technology, which uses commercial, off-the-shelf (COTS) components, thus drastically reducing costs while accelerating time to market. This is particularly relevant to nanosatellites, many of whom are being developed to target the IoT-NTN market. Another important difference is that launch costs have decreased significantly due to the entry of new private launch companies, notably SpaceX.

Perhaps the most important differentiator between current and next-generation satellites, however, is that the latter will be based on 3GPP’s NTN standards. Historically, proprietary satellite systems have resulted in a limited range of low volume and hence expensive end user devices – a significant barrier to growth. As with 5G (and 4G before it), a common set of cellular-based standards will enable the mobile satellite industry – plus the vertical markets it serves – to benefit from the vast economies of scale of the cellular device ecosystem. This should result in higher volume chipset production, more affordable devices and services and hence a much larger market of end users. For instance, Sateliot estimates that the cost of satellite IoT connectivity will drop from hundreds of dollars per device per month to less than $10 per device per month.

Furthermore, the adoption of 5G NTN and its integration with terrestrial 5G will result in a truly seamless global telecoms network, with increased space segment capacity, resulting in more users benefiting from higher data rate services. This will lead to more applications and use cases thus creating more value-add for vertical market users. Clearly, this could lead to a significant expansion of the mobile satellite services market globally.

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The post 3GPP 5G NTN Standards Set To Dramatically Boost Mobile Satellite Addressable Market appeared first on Counterpoint.

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5G Advanced will expand the role of wireless AI across 5G networks introducing new, innovative AI applications that will enhance the design and operation of networks and devices over the next three to five years. Indeed, wireless AI is set to become a key pillar of 5G Advanced and will play a critical role in the end-to-end (E2E) design and optimization of wireless systems. In the case of 6G, wireless AI will become native and all-pervasive, operating autonomously between devices and networks and across all protocols and network layers.

E2E Systems Optimization

AI has already been used in smartphones and other devices for several years and is now increasingly being used in the network. However, AI is currently implemented independently, i.e. either on the device or in the network. As a result, E2E systems performance optimization across devices and network has not been fully realized yet. One of the reasons for this is that on-device AI training has not been possible until recently.

On-device AI will play a key role in improving the E2E optimization of 5G networks, bringing important benefits for operators and users, as well as overcoming key challenges. Firstly, on-device AI enables processing to be distributed over millions of devices thus harnessing the aggregated computational power of all these devices. Secondly, it enables AI model learning to be customized to a particular user’s personalized data. Finally, this personalized data stays local on the device and is not shared with the cloud. This improves reliability and alleviates data sovereignty concerns. On-device AI will not be limited to just smartphones but will be implemented across all kinds of devices from consumer devices to sensors and a plethora of industrial equipment.

New AI-native processors are being developed to implement on-device AI and other AI-based applications. A good example is Qualcomm’s new Snapdragon X75 5G modem-RF chip, which has a dedicated hardware tensor accelerator. Using Qualcomm’s own AI implementation, this Gen 2 AI processor boosts the X75’s AI performance more than 2.5 times compared to the previous Gen 1 design.

While on-device AI will play a key role in improving the E2E performance of 5G networks, overall systems optimization is limited when AI is implemented independently. To enable true E2E performance optimization, AI training and inference needs to be done on a systems-wide basis, i.e.  collaboratively across both the network and the devices. Making this a reality in wireless system design requires not only AI know-how but also deep wireless domain knowledge. This so-called cross-node AI is a key focus of 5G Advanced with a number of use cases being defined in 3GPP’s Release 18 specification and further use cases expected to be added in later releases.

Wireless AI: 5G Advanced Release 18 Use Cases

3GPP’s Release 18 is the starting point for more extensive use of wireless AI expected in 6G. Three use cases have been prioritized for study in this release:

• Use of cross-node Machine Learning (ML) to dynamically adapt the Channel State Information (CSI) feedback mechanism between a base station and a device, thus enabling coordinated performance optimization between networks and devices.
• Use of ML to enable intelligent beam management at both the base station and device, thus improving usable network capacity and device battery life.
• Use of ML to enhance positioning accuracy of devices in both indoor and outdoor environments, including both direct and ML-assisted positioning.

Channel State Feedback:

CSI is used to determine the propagation characteristics of the communication link between a base station and a user device and describes how this propagation is affected by the local radio environment. Accurate CSI data is essential to provide reliable communications. With traditional model-based CSI, the user device compresses the downlink CSI data and feeds the compressed data back to the base station. Despite this compression, the signalling overhead can still be significant, particularly in the case of massive MIMO radios, reducing the device’s uplink capacity and adversely affecting its battery life.

An alternative approach is to use AI to track the various parameters of the communications link. In contrast to model-based CSI, a data driven air interface can dynamically learn from its environment to improve performance and efficiency. AI-based channel estimation thus overcomes many of the limitations of model-based CSI feedback techniques resulting in higher accuracy and hence an improved link performance. The is particularly effective at the edges of a cell.

Implementing ML-based CSI feedback, however, can be challenging in a system with multiple vendors. To overcome this, Qualcomm has developed a sequential training technique which avoids the need to share data across vendors. With this approach, the user device is firstly trained using its own data. Then, the same data is used to train the network. This eliminates the need to share proprietary, neural network models across vendors. Qualcomm has successfully demonstrated sequential training on massive MIMO radios at its 3.5GHz test network in San Diego (Exhibit 1).

Exhibit 1: Realizing system capacity gain even in challenging non-LOS communication

AI-based Millimetre Wave Beam Management:

The second use case involves the use of ML to improve beam prediction on millimetre wave radios. Rather than continuously measuring all beams, ML is used to intelligently select the most appropriate beams to be measured – as and when needed. A ML algorithm is then used to predict future beams by interpolating between the beams selected – i.e. without the need to measure the beams all the time. This is done at both the device and the base station. As with CSI feedback, this improves network throughput and reduces power consumption.

Qualcomm recently demonstrated the use of ML-based algorithms on its 28GHz massive MIMO test network and showed that the performance of the AI-based system was equivalent to a base case network set-up where all beams are measured.

Precise Positioning:

The third use case involves the use of ML to enable precise positioning. Qualcomm has demonstrated the use of multi-cell roundtrip (RTT) and angle-of-arrival (AoA)-based positioning in an outdoor network in San Diego. The vendor also demonstrated how ML-based positioning with RF finger printing can be used to overcome challenging non-line of sight channel conditions in indoor industrial private networks.

An AI-Native 6G Air Interface

6G will need to deliver a significant leap in performance and spectrum efficiency compared to 5G if it is to deliver even faster data rates and more capacity while enabling new 6G use cases. To do this, the 6G air interface will need to accommodate higher-order Giga MIMO radios capable of operating in the upper mid-band spectrum (7-16GHz), support wider bandwidths in new sub-THz 6G bands (100GHz+) as well as on existing 5G bands. In addition, 6G will need to accommodate a far broader range of devices and services plus support continuous innovation in air interface design.

To meet these requirements, the 6G air interface must be designed to be AI native from the outset, i.e. 6G will largely move away from the traditional, model-driven approach of designing communications networks and transition toward a data-driven design, in which ML is integrated across all protocols and layers with distributed learning and inference implemented across devices and networks.

This will be a truly disruptive change to the way communication systems have been designed in the past but will offer many benefits. For example, through self-learning, an AI-native air interface design will be able to support continuous performance improvements, where both sides of the air interface — the network and device — can dynamically adapt to their surroundings and optimize operations based on local conditions.

5G Advanced wireless AI/ML will be the foundation for much more AI innovation in 6G and will result in many new network capabilities. For instance, the ability of the 6G AI native air interface to refine existing communication protocols and learn new protocols coupled with the ability to offer E2E network optimization will result in wireless networks that can be dynamically customized to suit specific deployment scenarios, radio environments and use cases. This will a boon for operators, enabling them to automatically adapt their networks to target a range of applications, including various niche and vertical-specific markets.

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The post 5G Advanced and Wireless AI Set To Transform Cellular Networks, Unlocking True Potential appeared first on Counterpoint.

Key Takeaway No. 1: Platform Limitations

Softbank is offering a dual-purpose platform where the main application is AI compute via a high-performance edge analytics platform to capitalise on the expected surge in demand for AI processing capacity. Although the company is also developing a range of 5G applications, the AI and 5G workloads will be offered simultaneously. Counterpoint Research believes that the platform is unlikely to be feasible for vRAN workloads alone and understands that the two partners are not targeting this market.

Key Takeaway No. 2: Leveraging GPU Usage in the RAN

NVIDIA is planning to leverage its GPU processing capacity in the RAN in a number of ways, for example, to  improve spectral efficiency. One way of doing this is to apply AI to optimise channel estimation feedback data between a user device and a base station. A compute intensive problem with mMIMO radios, using AI to compress receiver feedback data would reduce signalling overhead, thereby resulting in an useful increase in uplink channel capacity. This could be particularly effective at the edges of a cell. Using its GPUs in this way, NVIDIA claims that it can boost gain for cell edge users by 14-17 dB. Other applications include using AI to optimise beamforming management in millimetre wave mMIMO radios as well as to accelerate Layer 2 scheduling.

The full version of this insight report, including a complete set of Key Takeaways is published in the following report, available to clients of Counterpoint Research’s 5G Network Infrastructure Service (5GNI).

New Report: NVIDIA and Softbank Join Forces To Deploy AI-Based 5G MEC Telco Network Across Japan

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The post NVIDIA and Softbank Developing AI-Based 5G MEC Telco Network appeared first on Counterpoint.

Virtually all open RAN deployments to date are based on Intel’s FlexRAN reference software architecture running on x86-based COTS servers. While this configuration is adequate for low to medium traffic scenarios, it is not sufficient for high-traffic use cases in dense urban areas involving the use of massive MIMO radios.

Solving the massive MIMO performance deficit is a major challenge delaying the transition to open RAN. This challenge must be resolved before mainstream adoption of open RAN-based massive MIMO radios can occur. However, this will require a new breed of merchant silicon solutions designed to efficiently process latency-sensitive Layer-1 baseband workloads. Last year, a number of vendors announced alternatives to Intel’s FlexRAN platform based on ASICs, GPUs as well as RISC-V architectures and several of these vendors showcased their latest products recently at MWC-23 in Barcelona (Exhibit 1).

Look Aside Versus In-line Acceleration

Open RAN COTS platforms typically use PCIe-based accelerator cards to process the compute-intensive Layer 1 workloads. There are essentially two types of architecture designs: look-aside and in-line:

• Look-aside accelerators offload a small subset of the 5G Layer 1 functions, for example, forward error correction, from the host CPU to an external FPGA or eASIC-based accelerator. However, this offloading adds latency and degrades system performance as the compute is done offline.

An alternative to using PCIe cards is to integrate the look-aside accelerator and CPU in a SoC. This eliminates the need for a separate PCIe card. Look-aside acceleration is used by AMD and Intel, including in the latter’s vRAN Boost integrated SoC design.

• With the in-line accelerator architecture, all the Layer 1 data passes directly through the accelerator and is processed in real-time – a critical requirement for Layer 1 workloads. This processing is done by other types of processors, for example, ARM or RISC-V based DSPs, which results in a more energy-efficient implementation and reduces the need for additional CPUs with a high number of cores. For operators, this results in significant CAPEX and OPEX savings, particularly in the case of massive MIMO base stations, the most demanding of all 5G network deployments.

In-line accelerators also offer important scalability benefits as operators can add extra accelerator cards (up to six cards in a standard telco grade server) as more L1 capacity is required. In contrast, the look-aside architecture involves adding expensive, power-hungry COTS CPUs (+FPGA/eASIC cards) to meet capacity increases. In-line acceleration is used by ARM-based chip vendors such as Qualcomm Technologies, Inc and Marvell, as well as some RISC-V start-ups.

Layer-1 Software Stack

Chip vendors typically offer Layer-1 reference software stacks, which OEMs or third-party software vendors then customize and harden. This is an intensive two- or three-year process that demands considerable technical expertise and resources, particularly for telco-grade massive MIMO networks. With 5G, there is added complexity as the Layer 1 stack needs to be very adaptive and programmable to cater for the multitude of workloads and use cases. As a result, very few chip vendors offer carrier-grade Layer 1 software. In fact, the choice of vendors with the capability to develop macro cell massive MIMO Layer 1 stacks is essentially limited to the Tier-1 incumbents plus a handful of open RAN challenger vendors.

Tier-1 incumbents are unlikely to offer the same level of openness and flexibility as the challenger vendors, and hence accelerator cards from the latter may be a more attractive option for operators looking for a higher level of network customization. For example, Qualcomm Technologies will offer a set of APIs that allow vendors to port alternative software into its Layer 1 stack – such as beamforming or channel estimation algorithms. This lowers the barriers to entry for small software vendors and enables new players to enter the market – i.e. without requiring them to develop a full commercial-grade Layer 1 stack themselves. This could result in a rapid expansion of the Layer 1 software ecosystem.

Exhibit 1: Open RAN Layer 1 Accelerator Card Options by Vendor (Macro Cells)

Energy Efficiency – A Critical Metric

Reducing OPEX costs has become a major priority for operators due to soaring energy costs plus the need to minimize their carbon footprints. As a result, energy efficiency, i.e. Gbps/Watt, will be a critical metric for operators when evaluating Layer 1 accelerator cards. However, only a few vendors have revealed power consumption data. In a recent demo, Qualcomm Technologies showed the total power consumption of its Qualcomm® X100 5G RAN Accelerator Card [1] to be just 16-18W when driving a 16-layer 64TRx massive MIMO radio configuration serving four user devices (using four layers/device). According to the vendor, the card is designed to support a throughput of 24Gbps at less than 40W peak power consumption.

Viewpoint

The open RAN story is gaining momentum and Counterpoint Research expects this growth to accelerate during 2023 and beyond driven by the availability of new merchant silicon solutions. To succeed in the marketplace, however, these new silicon platforms will need to demonstrate the potential to compete against the latest incumbent RAN solutions – across all key technical metrics – as well as offering the same level of advanced 5G features. Clearly, energy efficiency will be a major product differentiator, which puts current x86-based look-aside designs at a disadvantage compared to the latest in-line accelerators and suggests that most operators will favour the in-line architecture approach. Ultimately, the winning vendors will be those that are best able to satisfy the key technical requirements of individual operators while at the same time offering them the flexibility to customize their networks to suit their own requirements.

[1] Qualcomm X100 5G RAN Accelerator Card is a product of Qualcomm Technologies, Inc. and/or its subsidiaries. Qualcomm is a trademark or registered trademark of Qualcomm Incorporated

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The post Open RAN Networks – Layer 1 Acceleration Strategy Will Be Key To Operator Success appeared first on Counterpoint.

Improving Customer Experience

In the short term, improving network quality is Rakuten’s main priority.  Following a recent customer survey, Rakuten has launched several initiatives to improve customer experience, most of which will be resolved by a new roaming agreement with KDDI – which includes access to the latter’s sub-1GHz spectrum for the first time. This should improve coverage, particular in-doors such as in the home and in high-traffic shopping malls, as well as underground in subways, tunnels, etc. However, Rakuten urgently needs to build its own low-band networks – i.e. in the so-called “platinum” band – starting probably in early 2024.

Selling the Family Silver

Rakuten is still in a precarious situation financially and is in the process of selling more of the family silver to fund its mobile network roll-out. This includes IPOs and the sale of stakes in some non-core assets, for example, the Seiyu supermarket chain. The company has also pushed back its target date to become profitable from the end of 2023 to an unspecified time in 2024.

Challenges of Rolling Out Greenfield Networks

Rakuten’s experience over the past three years illustrates the challenges of rolling out a greenfield network in a mature market and the time, effort and investment required to achieve coverage and reliability on a par with better-heeled rivals. Indeed, many of these challenges have nothing to do with the choice of network architecture, i.e. open RAN. As a result, there are many lessons here for Dish and 1&1 Drillisch.

The silver lining for Rakuten, perhaps, is that it is primarily a tech company and its Rakuten Symphony division is starting to deliver meaningful revenues, which are projected to accelerate during 2023. Dish and 1&1 Drillisch do not have that luxury!

Exhibit 1:  Summary of Rakuten’s Customer Churn Survey

The full version of this insight report, including all highlights and viewpoints is published in the following report “Rakuten Unveils Plan To Boost Subscriber Growth” available to clients of Counterpoint Research’s 5G Network Infrastructure Service (5GNI).

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In contrast to traditional RAN networks, the baseband unit of a cloud RAN base station is split into two units: a Distributed Unit (DU) and a Centralized unit (CU). Today, the vast majority of commercially deployed DU basebands run on x86 processors. However, alternatives to Intel’s x86 platform, based on ASICs, GPU and RISC-V architectures are expected to become widely available during the next three years.

Cloud RAN platforms typically use PCIe-based accelerator cards to process the compute-intensive Layer 1 workloads. There are essentially two types of accelerator architecture: look-aside and in-line:

• Look-aside accelerators offload a small subset of the 5G Layer 1 functions, for example, forward error correction, from the host CPU to an external FPGA-based accelerator.
• With an in-line accelerator card, all the Layer 1 data passes directly through the accelerator and is processed in real-time – a critical requirement for Layer 1 workloads. This processing is done by other processor types, for example, ARM or RISC-V based DSPs.

However, there is a marked difference in the approach of vendors towards Layer 1 acceleration, with some vendors supporting the look-aside option, some supporting the in-line option, while others plan to offer both options.

Counterpoint Research’s latest report “Cloud RAN Platforms – Why Are Vendors Adopting Different Layer 1 Acceleration Strategies?” provides details of the cloud RAN platform configurations offered by various incumbent and challenger vendors and discusses the reasoning and underlying strategy behind their technology choices and partnerships.

Table of Contents

Snapshot
Introduction
Key Cloud RAN Platforms
-Ericsson
-Nokia
-Samsung
-NEC
-Fujitsu
-Rakuten
-Mavenir
-JMA Wireless
Viewpoint

This report is available to clients of Counterpoint Research’s 5G Network Infrastructure (5GNI) Service.

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The post Cloud RAN Platforms – Why Are Vendors Adopting Different Layer-1 Acceleration Strategies? appeared first on Counterpoint.

This report provides an overview of the emerging open RAN PCIe-based Layer-1 accelerator card market based on new merchant silicon and highlights the opportunities and technical challenges facing the open RAN chip community as they strive to develop alternative chip solutions capable of efficiently processing real-time, latency-sensitive Layer-1 workloads.

Key Takeaway No. 1: Too much diversity?

The launch of new L1 accelerator cards from various vendors, large and small, should be welcomed by CSPs calling for diversity and will go some way to quell criticism that the open RAN market is too Intel-based. However, CSPs may now be faced with another dilemma – too much choice! They must now face the difficult challenge of testing and comparing multiple accelerator cards, inevitably involving complicated technical and commercial trade-offs.

Key Takeaway No. 2: Look-Aside or In-Line Accelerators?

At present, the choice of accelerator architecture is binary: either look-aside or inline. Both types have their advantages and drawbacks. Depending on use cases and applications, Counterpoint Research believes that operators may need to use both types of accelerators. However, only one vendor currently offers a software/silicon platform with the capability to do this.

Key Takeaway No. 3: Interoperability and Vendor Lock-In

Developing commercial-grade Layer 1 software suitable for massive MIMO networks is an expensive process requiring very specific skills and a lot of experience – but with no guarantee of commercial success. Although open RAN is designed to promote interoperability and vendor diversity, all L1 stacks are currently tied to the underlying silicon architectures and hence are not portable between hardware platforms. This introduces a new form of vendor lock-in for CSPs. Clearly, there is an urgent need for an universal software abstraction layer between the L1 stack and the various hardware platforms to enable stack portability.

The complete versions of these Key Takeaways, including the full set of  Takeaways is published in the following report, available to clients of Counterpoint Research’s 5G Network Infrastructure (5GNI) Service.

Report: New L1 Accelerator Cards Set To Boost Open RAN Market – Or Create More Lock-In?

Table of Contents

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The post New Layer-1 Accelerator Cards Set To Boost Open RAN Market – Or Create More Lock-In? appeared first on Counterpoint.

The “10 Gbps Everywhere” Experience

Compared to conventional 5G, 5.5G represents a 10-fold improvement in performance across the board. This means that 5.5G networks will be able to provide ubiquitous 10 Gbps downlink and 1 Gbps uplink speeds while supporting 100 billion IoT connections – compared to just 10 billion with 5G. In addition, 5.5G is expected to deliver latency and positioning accuracy that are a fraction of the current 5G standard as well as significant reductions in overall network power consumption.

5.5G will provide enhanced connectivity and better user experiences. By leveraging the 10 Gbps downlink throughput and low milli-second latency, 5.5G will bridge the gap between the physical and virtual worlds. Although 5G already provides some immersive services, 5.5G will enable interactive immersive services, such as 24k resolution VR gaming, glasses-free 3D video and 3D online malls.

Benefits for Enterprises

In addition to enhanced connectivity, 5.5G will offer a broad range of new capabilities for enterprises. Counterpoint Research expects a surge in new private network applications as networks are able to leverage the technical innovations enabled by 5.5G. For instance, enterprises will benefit greatly from the 1 Gbps uplink capability, enabling, for example, high-precision AI-based industrial vision inspection, while enhanced positioning with sub-10cm accuracy – both indoors and outdoors – will enable a plethora of new Industry 4.0 applications.

In addition, 5.5G will support three rapidly developing IoT technologies: NB IoT, RedCap and passive IoT tags, an innovative, low cost location sensing technology. A promising application of passive IoT tags is HCS-based Millimetre Wave[1] technology, an integrated sensing and communications technology, which enables centimetre precise positioning of objects, including pedestrians and personal items, livestock, autonomous vehicles, drones, etc. On the network side, enhanced AI/ML capabilities across the RAN, core and network management domains plus new power saving features will result in significant energy savings for operators.

Standards and Spectrum

Technical standards are the bedrock of the telecommunications industry and it is imperative that common standards are adopted worldwide. The standardization of 5.5G via 3GPP Release 18 is on-going. However, the industry must work together to ensure that Release 18 is frozen by the first quarter of 2024 as planned to enable 5.5G to be introduced from 2025 onwards.

Release 18 will be followed by Releases 19 and 20 after which the 3GPP will focus on 6G. Clearly, industry players need to collaborate closely over the next few years in order to define and maximise the technical innovations and capabilities of 5.5G and to ensure new services and use case scenarios are properly supported. This will help to maximise the potential of 5.5G for operators and extend its lifecycle.

Additional spectrum will be required to enable 5.5G to deliver its full potential. Re-farming of legacy 2G and 3G bands will free some lower band spectrum. However, this is not sufficient. More spectrum in the 6GHz and millimetre bands is necessary. With the WRC-23 radio conference taking place in November, it is essential that all stakeholders, including governments and regulators as well as operators and vendors, agree on the best spectrum strategy. Clearly, the 6GHz band should be a key 5.5G target band for the industry. In fact, the 3GPP has already licensed the 6,425-7,125MHz bands and Counterpoint Research expects that the upper part of this band will be identified as an IMT band at WRC-23. Millimetre wave is another key spectrum band for 5.5G and more than 800MHz additional millimetre wave spectrum will likely be needed to enable operators to deliver the 10 Gbps experience.

Networks and Devices

Networks and devices will need to be upgraded to enable 5G Advanced and this will involve further innovation with respect to 5.5G chipset technologies and devices.

5.5G will introduce a plethora of new devices with new capabilities beyond smartphones. Some of these will be full-capability devices while others will have reduced capabilities. For example, Red Cap devices only need to support a shortened set of specific capabilities, for example, video surveillance devices used for industrial quality control, process monitoring, sensing or tracking. However, all players, including chipset and device OEMs, must start working immediately to define the digital requirements for individual vertical use cases and applications in order to ensure that an ecosystem of suppliers is developed.

A significant recent development is the release of millimetre chipsets. For example, Qualcomm recently demonstrated its 5.5G Snapdragon chip, which offers 10 Gbps speed with 10CC carrier aggregation on millimetre wave and 5CC carrier aggregation on sub-6GHz frequencies. Similarly, MediaTek’s chipset offers downlink and uplink speeds of 7.67 Gbps and 3.76 Gbps respectively.

Upgrading Fibre to 5G Advanced

Achieving the “10 Gbps Everywhere” experience” will involve upgrading standards for fixed fibre broadband as well as for 5G RAN and Core. In fact, the evolution of Fibre Broadband 5G (F5G) to all-optical F5.5G has already progressed from proposals to specification design.

Performance improvements in fibre networks will be achieved by agreements on the use of key technologies such as 50G Passive Optical Network (PON) technology, Fibre to the Room (FTTR), etc. 50G PON is being standardized as the next-generation PON by the ITU-T. Together with technologies such as “uplink/downlink symmetry” and “multi-band in one,” this will pave the way for a smooth evolution to F5.5G. Last September, ETSI released its F5G Advanced White Paper and the standards body has been leading the formulation of F5.5G’s first release, Release 3, which will be frozen in first half of 2024.

The development of 5.5G and F5.5G will require a converged fixed/wireless IP network. Work on the definition of a new converged network – tentatively called Net5.5G – has already begun. Both the IETF and the IEEE are working on the first phase of Net5.5G standardization, but consensus is still needed on fixed/wireless bearer technologies such as 800GE backbone, 400GE MAN, etc. as well as on key aspects of other technologies such as WiFi-7, Segment Routing over IPv6 (SRv6), etc. before the new standard is released in 2024. With new capabilities, Net5.5G will enable operators maximise the potential of 5.5G and provide new opportunities for growth.

Viewpoint

The increasing popularity of immersive experiences and the emergence of the metaverse coupled with the demands of enterprise digital transformation mean that 5G networks will soon be unable to support the expected exponential growth in traffic. With 6G around 8-12 years away, 5.5G is the next obvious evolution of 5G and next-generation consumer and B2B opportunities will only be possible if operators and enterprises upgrade to 5.5G.

However, a successful and timely upgrade to 5.5G will require all industry stakeholders – from technical standards bodies, operators, network and device manufacturers to policy developers and regulators – to work closely together and collaborate on key 5.5G enablers, including standards, spectrum, networks and device specifications, etc. Major MNOs will be required to pilot new 5.5G technologies and build business cases.  In addition, Counterpoint Research believes that an industry consensus on the digital requirements of new use cases needs to be developed, particularly with respect to enterprise vertical uses cases, as well as a focus on developing a diverse ecosystem of players encompassing all verticals. Finally, closer collaboration between the mobile and fixed telecoms communities will be essential in order to ensure synchronization of standards between wireless and fixed networks.

[1] Harmonized Communications Sensing

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The post 5G Advanced – Stakeholder Collaboration Essential To Maximise ROI For Operators appeared first on Counterpoint.

Key Features of NetCloud

Key features of NetCloud include:

A “Private Networks-in-a-Box” solution – which includes access points, core/gateway, network planning software, routers, private SIMs plus a single pane of glass cloud management and orchestration system via NetCloud.

Cradlepoint Distribution Channels – NetCloud will leverage Cradlepoint’s existing sales channels via network enterprise resellers, managed service providers, etc. Later in the year, the company plans to target distribution via mobile operators.

Flexible Customer Offering – based on a CAPEX or OPEX business model to suit customers. Enterprises can buy cellular access points, core capacity, etc on a capacity and service duration basis. For example, Cradlepoint offers 500Mbps 2 Gbps and 5 Gbps options for its core on a 3 or 5 year basis with SIM cards being sold in packs of 10.

At present, NetCloud is only available for use in the US’s 4G LTE CBRS market, but later this year, Cradlepoint will offer 5G radios for use in markets beyond the US, for example, Europe. The company also expects to introduce eSIM capabilities at the same time.

The key elements of Cradlepoint NetCloud solution are shown in Exhibit 1 below:

Exhibit 1:  Overview of Cradlepoint’s NetCloud Private Network Solution

Viewpoint

In the past year or so, there have been many “Private-Networks-in-a-Box” announcements from numerous vendors such as AWS, Cisco, HPE, etc. as well as operators such as Dish, etc. who believe that private network solutions can be marketed as an “out-of-a box” product like Wi-Fi. With so many offerings, this could turn out to be a very competitive market with thin margins, where success is largely determined by the vendors’ “go-to-market” strategy and distribution channels.

The launch of NetCloud is a clear indication that Ericsson (with Cradlepoint) plans to play across the whole breadth of the private networks market. Although surprisingly a bit late launching its own “box” solution, Counterpoint Research believes that Cradlepoint is well-positioned to benefit from the opportunities in this market due to its strong position in the enterprise market (32,000 customer base), its global distribution network of 6,000 resellers and partners – and backed by Ericsson’s connectivity expertise.

Related Reports

Private Networks – Market Sizing and Forecasts: 2021-2030

Private Networks – High Expectations Amid An Expanding Ecosystem

Network Slicing vs Private Networks: Benefits and Drawbacks

Private Cellular Networks – Devices Key To Growth In Unlicensed Spectrum

5G Mobile Edge Computing – An Emerging Technology Slowly Transitioning To Commercial Reality

The post Ericsson's Cradlepoint Launches NetCloud Private Networks Solution appeared first on Counterpoint.

Private Networks Market by Verticals

Counterpoint Research segments the private networks market into seven vertical markets: public sector, manufacturing, energy and utilities, natural resources extraction, transportation and logistics, SME and Others. The public sector consists of several sub-verticals such as public safety networks, smart cities, healthcare and government as well as education and defence. The SME market encompasses mostly non-industrial applications of private networks, for example, office buildings, hotels, shopping malls, leisure centres, etc. Counterpoint Research forecasts that manufacturing will be the biggest vertical by revenue at the end of the forecast period in 2030.

Variations by Region

The release of CBRS spectrum has been a key driver in the US, which is predominantly based on 4G LTE and typically used for simple applications that do not require 5G, for example, mobile broadband connectivity in schools. In contrast, Europe has a higher proportion of 5G networks with the focus being on Industry 4.0 automation and the development of smart factories. Key use cases driving the market in Europe include AGVs/AMR connectivity, advanced worker productivity technologies such as AR/VR, predictive maintenance, video analytics (particularly security), asset tracking, etc.

Most deployments of private networks are in the developed, high GDP regions of the world with developing regions of the world lagging. An exception is Latin America, where there are numerous networks targeting the mining industry (predominantly copper mines).

Exhibit 1: Global Private Networks Market: 2021-2030

Key Points and Issues

 Some key points discussed in the report include:

• Spectrum – spectrum availability has been the key driver behind the growth of the private networks market, with countries such as Germany, France, the UK and US leading deployments due to early availability of spectrum in those countries. However, none of these countries use the same spectrum bands for private networks. They also have different usage rules. Spectrum fragmentation is therefore an issue and there is an urgent need for harmonisation of private networks spectrum, particularly between countries in the same regions, such as Europe.
• 5G Advanced – the introduction of devices supporting 5.5G from 2025 onwards will provide a boost to 5G private networks and will result in a number of new device capabilities leveraging the advanced features offered by NR-Light (Redcap), expanded sidelink, etc. as well as new indoor/outdoor positioning techniques, passive IoT tag technology, etc. These developments will enable new applications and drive growth in key verticals such as advanced manufacturing, energy and utilities, etc.
• Private Networks vs Network Slicing – although network slicing is starting to be introduced over public networks, the technology is not yet mature. However, as slicing become mainstream (and coupled with improvements in the uplink capacity of public networks), it will in time become a lower cost alternative to dedicated private networks for some use cases.

Report Overview

Counterpoint Research’s “Private Networks Market – Market Sizing and Forecasts: 2021-2030” PPT report provides market sizing and multi-year forecasts for the global private networks market divided by vertical, region, technology and spectrum. An overview of the business and technological challenges facing the industry is also presented as well as Counterpoint’s key takeaways about the future of the private networks market.

Table of Contents:

• Study Overview and Assumptions
• Private Networks: Introduction & Definitions
• Market Sizing and Forecasts
  • Global Market Revenues
  • Market by Verticals
    • Definition of Verticals
    • Forecast Revenues by Vertical
    • Key Drivers per Vertical
  • Forecast Revenue by Regions
    • Definition of Regions
    • Forecast Revenue per Region
    • Key Drivers per Region
  • Forecast Revenue by Technology
    • 4G versus 5G
  • Forecast Revenue by Spectrum
    • Sub 6GHz vs millimetre Wave
  • Key Challenges
  • Key Takeaways

Related Reports and Blogs

Private Networks Tracker, May 2022

Private Networks – High Expectations Amid and Expanding Ecosystem

5G Network Slicing versus Private Networks: Benefits and Drawbacks

Private Cellular Networks – Devices Key To Growth in Unlicensed Spectrum

5G Mobile Edge Computing – An Emerging Technology Slowly Transitioning To Commercial Reality

The post Counterpoint Research Forecasts Private Networks Market To Reach $21.8 billion by 2030 appeared first on Counterpoint.

Huawei’s “ONE 5G” Concept

Amalgamating multi-band, multi-RAT base stations into single hardware units that can efficiently maximise the use of  available spectrum was a major theme at the Forum. For CSPs, this brings many benefits: replacing multiple “boxes” with a one or two “box” solution leads to lower tower costs and simplified, more spectrum-efficient multi-band network deployment, while the use of dynamic power sharing across all carriers, spectrum bands and RATs reduces power consumption. Centre-stage at the event, therefore, was Huawei’s “ONE 5G” concept – a set of base station solutions designed to integrate legacy base station hardware into single RAN units and facilitate the transition and optimised usage of all mobile spectrum bands, including legacy narrowband FDD bands, to 5G.

Huawei demonstrated several new ultra-wideband products including its second-generation, 800 MHz MetaAAU with ELAA technology; multi-band 4T4R radio; FDD 8T8R radio incorporating its Hertz antenna and new indoor Giga Lampsite 5.0 products. Several of Huawei’s new antenna products now incorporate its proprietary Signal Direct Injection Feeding (SDIF) technology, which dispenses with the need for cables inside the antenna enclosure. This provides many benefits, including a higher gain/better coverage (due to reduced signal loss), improved power dissipation, higher reliability – plus a claimed 1Kg/band saving in weight.

Other Key Themes

Other major themes included Intelligent RAN, where the vendor demonstrated its latest AI-based solutions and 5G Advanced, where numerous innovations in IoT and private networks based on the upcoming 5.5G standard were showcased.  Of particular interest was the vendor’s  HCS-based Millimetre Wave positioning technology using passive IoT tags, a promising technology for numerous applications requiring precise positioning, such as autonomous vehicles, drones, etc.

*Harmonized Communications Sensing

A full review of Huawei’s Global MBB Forum, including a full set of takeaways, is published in the following report, available to clients of Counterpoint Research’s 5G Network Infrastructure Service.

Selected Highlights from Huawei’s Global MBB Forum

Table of Contents

Overview:

• CSPs – Facing Network Challenges
• Huawei’s “ONE” Concept
• Frequency Bands Transitioning to 5G
• Challenges of Fragmented FDD Spectrum

New Base Station Products:

• 2nd-gen MetaAAU with ELAA
• Meta BladeAAU
• Ultra-Wideband, Multi-Band 4T4R Radio
• FDD 8T8R + Hertz Antenna
• Dual-Band FDD mMIMO Radio
• New mmWave Products

Intelligent RAN:

• Intelligent RAN Benefits
• Huawei Solutions & Deployments
• Operator Examples

5G Advanced and IoT:

• IoT Connections By Technology
• Passive IoT Technologies
• HCS : Millimetre Wave Positioning using Passive IoT
• Hybrid Private Networks
• Connected 5G Factory
• Healthcare – Smart Hospital
• Healthcare – 5G Mobile Stroke Care
• Oil & Gas Extraction

Key Takeaways

The post Huawei's "ONE 5G" Concept Centre Stage at Global MBB Forum appeared first on Counterpoint.

Samsung Networks – Open RAN/vRAN Leader?

Samsung Networks first entered the mobile infrastructure market, primarily as a 4G network infrastructure vendor, around ten years ago. Since then, it has developed a portfolio of 4G and 5G products, with a major focus on the open RAN/vRAN based market. Counterpoint Research believes that Samsung is the undisputed leader in this emerging market at the present time, having won multi-billion dollar contracts with several major MNOs, including Verizon, Vodafone and most recently Dish.

However, Samsung is not just focused on the emerging open RAN/vRAN market. At the recent MWC event in Las Vegas, the vendor outlined its mobile infrastructure strategy to industry analysts, which encompasses targeting the cable and regional MNO markets in the US (and elsewhere), as well as the private networks market.

Exhibit 1:  Samsung’s Strand 2TRx Small Cell Radio

The CBRS Market

The CBRS service provider ecosystem encompasses a diverse set of mobile and fixed operators as well as a host of enterprises and other organizations building their own private networks.  Samsung sees opportunities in multiple CBRS markets, including the following:

• Cable Market – cable operators made significant investment in CBRS spectrum back in 2020. However, they are only now starting to build their networks, typically offloading MVNO traffic in selected high-traffic regions, rather than building out nationwide mobile coverage.
• Regional Operators – driven by digital divide stimulus funds from the US government, the rural broadband market will be a major opportunity during the next few years with many regional operators seeking to launch rural FWA services.
• Private Networks – as well as private networks deployed by traditional mobile service providers, Samsung sees opportunities in serving a diverse range of customers in the CBRS band ranging from enterprises, schools and universities to industrial companies involved in energy and utilities, manufacturing, transportation and logistics, etc.

Key Takeaway No. 1:  The Disruptive Incumbent

Samsung is a challenger vendor and sees an opportunity to disrupt the status quo. As the smallest of the Big 5 in terms of market share, it has less to lose by introducing open RAN based networks compared to rivals. And in contrast to many smaller, open-RAN only players, its  can offer legacy as well as open RAN technology. With its own chip and foundry businesses – plus access to considerable technical and financial resources as part of a $260 billion cap industrial conglomerate – it is regarded as a reliable alternative to Ericsson and Nokia by many MNOs. However, with major rivals expected to launched “similar” products in 2023, the open RAN/vRAN market is set to become much more competitive.

Key Takeaway No. 2:  CBRS Early Mover Advantage Paying Dividends

Samsung launched its first FCC-certified CBRS mMIMO radio in July 2019. Since then the vendor has developed an extensive range of CBRS radios, including products developed specifically for the cable and  FWA markets. As a result, Counterpoint Research expects Samsung to benefit further from similar opportunities from other cable operators to complement its recent Comcast Xfinity Mobile win.

Buoyed by multi-billion dollar FCC funding, the rural FWA market is likely to be another major opportunity. Although there will be stiff competition from its Nordic rivals (plus some smaller vendors), Counterpoint Research believes that the Korean vendor is also well placed in this market, due primarily to its early mover CBRS advantage and backed by its growing reputation and track record as a reliable alternative to other incumbents in this market.

The complete version of this article, including the full set of key takeaways, is published in the following 5G Vendor Report, available to clients of Counterpoint Research’s 5G Network Infrastructure Service:

Samsung Outlines Mobile Networks Strategy at MWC, Las Vegas

Table of Contents

Snapshot

Introduction

Key Target Markets

Strand Small Cell Radio

Key Cable & Regional MNO Customers

-Comcast

-Mediacom

-Mercury Broadband

-Avista Edge

Key Takeaways

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The post MWC-22 Las Vegas: Samsung Networks Makes Breakthrough In US Cable Market appeared first on Counterpoint.

Qualcomm’s Open RAN Macro Portfolio

Qualcomm’s open RAN macro portfolio essentially consists of two products: the QRU 100 radio platform and the X100 RAN accelerator card:

• QRU 100 Radio Platform – designed for use in 32TRx and 64TRx massive MIMO radios as well as much simpler 4TRx and 8TRx MIMO radios. The QRU 100 radio chip  includes transceivers, Layer-1 Low PHY baseband and beamforming processors and supports advanced cellular features such as RAN sharing, DSS, etc. In the case of mmWave applications, the chip also includes the RF front-end and antenna modules.
• X100 RAN Accelerator Card – an in-line PCIe-based accelerator card based on the QDU 100 chip, which processes latency sensitive and compute intensive Layer-1 High PHY baseband workloads such as channel coding, demodulation as well as mMIMO processing. This reduces the number of CPU cores required and hence the overall cost of the DU. The X100 card supports all O-RAN Alliance defined baseband function split options (including future options such as 7.3) and operates at sub-6GHz and mmWave frequencies – Exhibit 1(a).

Qualcomm is partnering  with HPE and the X100 card is being tested in the server vendor’s telco-grade ProLiant DL 110 Gen 10 Plus server, which has been optimised for open RAN workloads. The DL100 server is capable of supporting four cards within its 1U server footprint. Qualcomm claims that the card consumes approximately 35W of power when 70% loaded.

The key target markets for the above products will be the public macro MNO market as well as the enterprise private network market.

©Qualcomm, Inc, NTT DoCoMo

Exhibit 1(a) Qualcomm’s X100 Accelerator Card and (b) Qualcomm’s OREC partners and roles

Testing and Validation Schedule

Qualcomm has been providing engineering samples of its hardware to partner vendors, which include Fujitsu, NEC and Mavenir, since around mid-2022. Extensive lab testing will start around the end of 2022 or early 2023 with commercial deployments expected to start towards the end of 2023.

In addition, Qualcomm intends to undergo extensive integration tests with its partners at NTT DoCoMo’s OREC facility in 2023. This will involve testing the X100 card on an Intel-based HPE Proliant server as part of a complete 5G base station solution configured as shown in Exhibit 1(b).

Carrier-Grade Layer-1 Stack

Very few chip vendors offer a production-grade RAN software stack. Instead, they typically offer a reference stack of Layer-1 algorithms. Hardening the Layer-1 stack is both an intensive and extensive process that requires considerable technical expertise and resources.

Traditionally, Qualcomm has provided its small cells SoCs with software, including Layer-1, for the sub-6GHz and mmWave small cells market via its FSM platform. Unlike many of its open RAN rivals, Qualcomm will continue this tradition and offer its own carrier-grade Layer-1 software stack for the QRU100 and X100 card, which can then be customized by the customer. However, this will be an evolutionary process, with features being added according to a calendar of releases and followed by extensive testing and tuning until the required performance and stability is achieved.

Qualcomm’s Role and Partner Ecosystem

Qualcomm’s role in the 5G infrastructure market will be as an open RAN chip solutions provider enabling many new radio OEMs to enter the market as well as supplying some traditional vendors. Qualcomm already dominates the small cells market with its FSM100 (and FSM200) solutions and has developed an impressive list of customers. Clearly, the goal here is to do the same in the macro base station market by offering a range of proven, pre-integrated open RAN-based chip solutions to a wide variety of vendors, thereby gaining market share at the expense of the incumbents. Partners to date include Fujitsu, NEC, Mavenir, Rakuten Symphony and Viettel.

Viewpoint

The open RAN/vRAN story is gaining momentum as major operators such as NTT DoCoMo, Verizon and others slowly transition to fully virtualized networks. Counterpoint Research expects this to accelerate during 2023, driven primarily by operators’ interest in leveraging the benefits of cloud-native architectures – rather than any clear-cut TCO benefits. These benefits include improved network agility, scalability and automation and will enable the introduction of new types of services.

Although the cost/performance differential compared to state-of-the-art, proprietary 5G base stations will persist, operators have an urgent need to introduce innovative new services in order to monetise their 5G networks. Counterpoint Research believes that this need will drive the adoption of disaggregated, virtualized RAN networks and that the benefits and flexibility offered by this type of architecture – for specific use cases such as as low-latency 5G MEC – will likely offset the cost/performance deficit for most operators.

Related Reports

The Emerging Cloud RAN Ecosystem – Players and Solutions

Cloud RAN – Technology Review and Challenges

Open RAN Radios – Chinese Vendors Set To Dominate An Emerging Market?

The post Qualcomm On Track To Launch Open RAN 5G Macro Base Station Portfolio appeared first on Counterpoint.

Key highlights during the quarter included the appointment of Samsung as a major radio supplier. Post period, Apple announced that it will include Dish’s Band 70 frequencies in its latest iPhone 14 model, a major boost for Dish. The operator is now preparing for the launch of its first post-paid service Boost Infinite, expected before the end of the year.

Key Quarterly Data

News on the subscriber front, however, was not so good for either the wireless or the pay-TV business as the company continued to shed subscribers.

• Wireless subscribers – Dish lost another 210,000 retail subscribers during the quarter bring its total wireless subscriber base down to 7.87 million. The company has lost around 1.1 million wireless subscribers since it entered the wireless business in August 2020 when it purchased Boost Mobile for $1.4 billion from T-Mobile. ARPU increased slightly from the previous quarter to $37.90 while churn rate improved marginally to 4.39%.
• Pay-TV – Dish’s pay-TV business also lost around 257,000 customers in the second quarter and the company ended the quarter with 7.79 million satellite TV subscribers and 2.2 million Sling TV streaming customers.

Total revenue was $4.21 billion for the quarter, down 6% from $4.49 billion YoY while net income dropped 30.3% to $523 million YoY. Exhibit 1 shows how revenues for the pay-TV and wireless businesses have fallen during the past two years.

© Counterpoint Research, Data: Dish Networks

Exhibit 1:  Dish Pay-TV and Wireless Revenues During The Past Two Years

Samsung – More than a radio vendor?

Counterpoint Research believes that the most significant news during the quarter was the announcement that Dish had signed a new radio contract with Samsung Networks. According the company, Samsung will support virtually all of Dish’s FDD and TDD spectrum bands, including CBRS and the mid-band 3.45-3.55 GHz bands. Dish already has radio contracts with Fujitsu and MTI, with most of the radios to date being delivered by Fujitsu. Samsung thus becomes Dish’s third radio vendor. Without doubt, this is another major win for Samsung in the Tier-1 RAN market following similar multi-billion contract awards with Verizon and Vodafone. However, Counterpoint Research believes that the Korean vendor will play a bigger role at Dish as it can help Dish in a number of ways.

One of Dish’s key challenges right now is resolving its VoNR integration issues. Unlike Rakuten, Dish is not a technology company and so the addition of a mega tech company such as Samsung should be a major boost to the company. Samsung is also a major device manufacturer and Dish may well be relying on the Korean vendor expertise to resolve many of its systems integration issues.

Key Takeaway No. 1: Falling subscribers

Dish continued to lose a sizeable number of its pre-paid wireless customers during the quarter, even though the transition from T-Mobile’s CDMA network has ended. In fact, Dish estimates that the CDMA debacle has cost the company around $500 million directly and another $1 billion indirectly. Pay-TV subscribers are also falling.

With T-Mobile’s CDMA network shutdown, Dish should now be able to use its marketing resources to attract new customers rather than dealing with CDMA-related customer issues.  Counterpoint Research believes that it is imperative that Dish demonstrates that is has stabilised its pre-paid customer base during the next few weeks and months and that it has a strategy in place to attract new users. For example, the company recently announced that it is expanding its distribution efforts in Walmart and Best-Buy retail stores. Dish also needs to slow the decline in its pay-TV subscriber base.

The complete version of this article, including the full set of key takeaways, is published in the following 5G Insights Report, available to clients of Counterpoint Research’s 5G Network Infrastructure Service:

Dish Gets Ready To Launch Boost Infinite Post-Paid Service

Table of Contents

Snapshot

Quarter Overview

Key Earnings Data

Samsung – More than a radio vendor?

Spectrum News – 800 MHz and Band 70

Handset Availability – iPhone 14, etc.

Business Strategy Update

-Enterprise Market

-Post Paid Retail

-Fixed Wireless Access

-Pre-Paid Retail

Key Takeaways

Related Reports

5G Infrastructure Vendors – Are They Immune to Recession?

Rakuten Mobile – Time To Show Disruptive networks Can Deliver Disruptive Profits?

Cloud RAN – Waiting For A Viable Business Case?

The post Dish Gets Ready To Launch Boost Infinite Post-Paid Service appeared first on Counterpoint.