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Rapid Transition To L4 Automation Key To Successful 5G Network Monetization

Despite huge investments in 5G, network operators are still highly reliant on revenues from traditional voice and broadband data services and are struggling to increase ARPU. With 5G Advanced around the corner, they will need to continue investing heavily in new network infrastructure for many years to come, despite rising debt levels. As a result, the business models of many of these operators risk becoming unsustainable unless major changes are made.

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.

Selected Highlights from ITU’s WRC-23 Meeting In Dubai

Held every four years, the ITU’s World Radio Conference (WRC) came to an end last week. During the 4-week long conference, 43 new resolutions were approved, 56 existing ones were revised while 33 resolutions were suppressed. Key highlights included:

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

Mobile Operators to Invest Over $30 Billion in Open RAN Networks by 2030

Accelerated growth is expected from 2025 onwards after stagnation in 2023 and 2024.
Open RAN network investments to grow at a CAGR of 24% during the forecast period.
Asia-Pacific and North America will remain the largest Open RAN markets in the forecast period.
Europe is expected to record the fastest growth with a CAGR of 108% during 2023-2030.

Open RAN network investments have increased steadily in recent years, driven primarily by greenfield network operators in the Asia-Pacific and North American regions. However, following this period of rapid network build-outs, greenfield operators are looking to lower capex in 2023 and 2024 and focus on network monetization. Some Tier-1 operators, notably Vodafone, have announced major plans recently to deploy open RAN, but most brownfield network operators remain very cautious about additional investments in 5G infrastructure, particularly Open RAN, due to the uncertain macroeconomic climate.

As a result, Counterpoint Research expects that the Open RAN market will stagnate during this and the next year. Investments will start to increase YoY after 2025 with network operators investing a cumulative total of more than $30 billion between 2022 and 2030. This represents a CAGR of 24% for the forecast period of 2023-2030.

Although the Asia-Pacific and North American regions will remain the largest Open RAN markets for most of the forecast period, Europe is expected to record the fastest growth with a CAGR of 108% between 2023 and 2030 as its Tier-1s finally start commercial deployments at scale, driven partly by the need to replace legacy Chinese 3G and 4G networks.

The Open RAN-compliant radio market to date has been dominated by Asian vendors Samsung, NEC and Fujitsu. However, Counterpoint Research expects that their market share will be impacted during the forecast period as other incumbents start offering Open RAN-compliant solutions.

Counterpoint Research’s recently published Open RAN Tracker is the culmination of an extensive study on the Open RAN market. The tracker provides details of all operators across different regions, covering both trial and commercially deployed networks, and market shares by region and by vendor.

Background

Counterpoint Technology Market Research is a global research firm specializing in products in the TMT (technology, media and telecom) industry. It services major technology and financial firms with a mix of monthly reports, customized projects and detailed analyses of the mobile and technology markets. Its key analysts are seasoned experts in the high-tech industry.

3GPP 5G NTN Standards Set To Dramatically Boost Mobile Satellite Addressable Market

Satellite communications is back in the limelight following the launch of Apple’s direct Satellite-to-Phone service earlier this year. Partnering with satellite operator Globalstar, the service provides SOS messaging for iPhone 14/15 users. Recently, the service was expanded to include roadside assistance via satellite as well. A host of similar services and partnerships have been announced between satellite operators and chip vendors/cellular operators during the past few months, including Inmarsat with Mediatek, Iridium with Qualcomm and most recently SpaceX with KDDI.

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.

NG-LLS Fronthaul Interface – A Pivotal Moment For The 5G RAN Ecosystem?

One of the major challenges to the adoption of open RAN in 5G networks in dense, urban environments is its sub-optimal support for massive MIMO radios. While there are several reasons behind this performance deficit, a key reason is that the O-RAN Alliance 7.2x open fronthaul specification was not originally designed to accommodate massive MIMO radio systems. Recently, the O-RAN Alliance announced a new fronthaul interface specification designed specifically for use with massive MIMO radio systems in dense, high-traffic environments.

This Technology Report provides an objective analysis of the O-RAN Alliance’s Next Generation Lower-Layer Split (LLS) and discusses the implications of the new interface on the adoption of open RAN massive MIMO radios.

Key Takeaway 1: Impact of Incumbents

With the availability of the new NG-LLS fronthaul split, it “appears” that the open RAN community has united around a single specification which will enable open RAN to be adopted in high-traffic urban regions. This should be welcome news as it means that operators will be able to use open RAN technology across all parts of their networks, from rural deployments to dense, high traffic urban environments. However, the NG-LLS standard has brought major incumbents such as Ericsson and Nokia into the open RAN limelight. While this brings scale and credibility to open RAN in the high-end 5G market, it also raises questions about open RAN’s goal of diversifying the radio supply chain and lowering barriers to smaller vendors.

Key Takeaway 2: Massive MIMO Use Cases Suitable for Split 7.2b

Although Split 7.2b has limitations when deployed in dense, high-traffic urban networks, Counterpoint Research believes that it will continue to be a good choice for other mMIMO use cases. For example, in uses cases with moderate traffic loads, where cell sizes are larger and where end-user mobility is low such as in Fixed Wireless Access applications. Radios based on Split 7.2b will also benefit from reduced complexity and lower costs compared to NG-LLS based radios. In future, the application of advanced AI/ML algorithms in the DU may narrow the performance differential between Split 7.2b and NG-LLS for some use cases.

The full version of this Technology 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).

Table of Contents:

• Snapshot
• Key Takeaways
• Introduction
• Overview of 5G Fronthaul Splits
• The Split 7.2x vs Split 7.3 (or 7.2c) Debate
• Next-Generation Lower-Layer Split
• Overview of ULPI Class B and Class A
• WBDF vs ULPI
• Beamforming
• Equalisation

• ULPI Performance Gains vs Increased RU Complexity
• Benefits of Equaliser in DU
• Leveraging AI for Channel Estimation
• Massive MIMO Uses Cases Suitable for Split 7.2b
• Non-massive MIMO Use Cases
• Implications for 5G RAN Ecosystem
• Analyst Viewpoint

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New Report

Counterpoint Research – 5G SA Core Deployments Decelerate in H1 2023

In some markets, operators await evidence of successful use cases before switching to 5G SA.
In H1 2023, the Asia-Pacific region continued to lead in terms of 5G SA Core deployments.
Ericsson led the overall market followed by Nokia, Huawei, ZTE, Samsung, and Mavenir.

Counterpoint Research’s recently published July update of the 5G SA Core Tracker is a culmination of an extensive study of the 5G SA market. It provides details of all operators with 5G SA cores in commercial operation at the end of H1 2023, including market share by region, vendor, and the popular frequency bands for deployments. Apart from that, it touches upon the potential monetization opportunities for telecom operators across different domains and uses cases.

Last year, there was steady growth in the commercial deployment of 5G Standalone (SA), with more than 20 operators moving to 5G standalone core. However, the pace slowed down in H1 2023 with the number of operators launching commercial 5G SA ranging in single digits. The primary reason for the slowdown in commercial deployment of 5G SA was the restraint arising from global macroeconomic factors and the lack of a clear picture of 5G monetization for operators. Although the pace of commercial deployment has slowed down in 2023, operators are working on monetization avenues, and are working on SA-specific use cases, including on-demand network slicing and FWA.

Most of the 5G SA commercial deployments have been in developed economies, and Counterpoint Research expects the next bulk of network rollouts will take place in emerging markets. This will drive the continuing transition from 5G NSA to 5G SA.

Exhibit 1: 5G SA Deployments by Region, H1 2023

As shown in Exhibit 1, the Asia-Pacific region led the segment, followed by Europe and North America, with the other regions – Middle East and Africa, and Latin America – lagging.

Key Points

Key points discussed in the report include:

Operators – 47 operators have deployed 5G SA commercially with many more in the testing and trial phase. Globally, most of the deployments are in developed economies with those in emerging economies lagging. Although the pace of deployment is steady in developed markets, it is progressing slowly in emerging markets, and in some markets, operators are biding their time and looking for evidence of successful use cases before switching from 5G NSA to SA. The ongoing economic headwinds also delayed the commercial deployment of SA, which was seen in H1 2023.
Vendors – Ericsson and Nokia lead the 5G SA Core market globally and are benefiting from the geopolitical sanctions on Chinese vendors Huawei and ZTE in some markets. South Korea’s Samsung and Japan’s NEC are mainly focused on their respective domestic markets but are expanding their reach to Tier-2 operators and emerging markets, while emerging vendors Parallel Wireless and Mavenir are working with leading operators in Europe, and Middle East and Africa.
Spectrum – Most operators are deploying 5G in mid-band frequencies, n78, as it provides faster speeds and good coverage. Some operators have also launched commercial services in the sub-GHz n28 and mmWave wave n258 bands. FWA seems to be the most popular use case at present but there is a lot of interest in edge services and network slicing as well.
Use Cases – Operators are looking for avenues to monetize the 5G services, as they are struggling to make the RoI from their investments in 5G. Although FWA is a promised application for 5G SA monetization, there are many other use cases that operators can look into to increase their RoI, including network slicing, live broadcasting, XR applications, and private networks. Although eMBB is the most widely used 5G use case currently, MNOs need to move to 5G SA to leverage URLLC and mMTC use cases.

Report Overview

Counterpoint Research’s 5G SA Core Tracker, July 2023 provides an overview of the 5G Standalone (SA) market, highlighting the key trends and drivers that are shaping the market, along with details of commercial launches by vendor, region, and frequency band. Additionally, the tracker provides details about the 5G SA vendor ecosystem split into two categories – public operator and private network markets.

Table of Contents:

Overview
Market Update
5G SA Market Deployments
- Commercial Deployment by Operators
- Network Engagements by Region
- Network Engagements by Deployments Status
- Leading 5G Core Vendors
- Mobile Core Vendor Ecosystem
- 5G Core Vendors Market Landscape
Outlook
5G Standalone Use Cases

Background

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press@counterpointresearch.com

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Big Role for 5G RedCap in 5G Evolution, Massive IoT Adoption

5G RedCap promises a mix of capabilities including improved throughput, extended battery life and less complexity to power diverse use cases cost-effectively.
5G RedCap (including eRedCap) modules are expected to contribute to one-fourth of total cellular IoT module shipments by 2030.
5G RedCap will serve use cases such as wearables, medical devices, video surveillance, industrial sensors and smart grid applications.

We have come a long way from the first generation (1G) to the fifth generation (5G) of cellular connectivity. Despite being in the initial stages of its rollout, 5G is poised for adoption at a speed not seen by previous cellular standards.

However, from the IoT perspective, 5G is being considered only for high-end applications due to the higher cost and existence of many use cases which need low power and low bandwidth, currently served by LPWAN. We can see the potential that 5G brings to IoT applications in terms of faster connectivity, low latency, reliability and large capacity compared to LTE networks. These benefits make 5G valuable for certain IoT use cases, creating a need for low-end 5G for the LPWAN application.

What are 5G RedCap and 5G eRedCap?

5G RedCap (Reduced Capacity), aka NR-Lite (New Radio-Lite), is a lighter version of the 5G standard that will cater to those use cases where ultra-low latency is not essential, but there is a need for reasonable throughput to support data flows in applications like router/CPE, mass-market automotive, POS and telematics devices, which are currently addressed by LTE Cat 4. In the upcoming 3GPP Release-18, there will be another version of 5G RedCap, called eRedCap (enhanced-RedCap), which will serve the use cases currently being served by LTE Cat 1 and LTE Cat 1 bis.

Market opportunity for 5G RedCap

5G RedCap addresses new use cases that cannot be served by advanced 5G standards like eMBB/URLLC and LPWAN. 5G RedCap chipset is already available in the market but we can expect commercial rollout by the first half of 2024. According to Counterpoint Research’s Global Cellular IoT Module Forecast, 5G RedCap modules will constitute 18% of total cellular IoT module shipments by 2030, indicating a significant market potential, particularly in developing nations where the cost is key to wide technology adoption for digital transformation.

The subsequent 5G eRedCap is planned for a 2024 introduction, with commercial availability likely by 2026. Expected to bring further innovations to the IoT segment, 5G eRedCap modules are projected to contribute 8% to the total cellular IoT module shipments by 2030.

During the transition phase, network operators will maintain IoT device support through the existing 4G network while focusing on 5G high-end applications like routers/CPE, XR/VR devices and automotive.

By the end of the decade, cellular IoT will generally migrate to 5G, driven by new use cases offered by the 5G network, with 4G serving as a fallback. The industry is already preparing for this shift, moving away from legacy technology towards newer standards.

5G RedCap ecosystem and applications

We can see a flurry of new announcements from ecosystem players to adopt the 5G RedCap standard. Module and chipset players are forging partnerships to capture the opportunity which will be created by 5G RedCap. Qualcomm always has been at the forefront when it comes to adopting new technologies with big potential. We can see that with its launch of the industry’s first SDX35 5G RedCap modem. Qualcomm’s early entry and partnerships with major module vendors will help it to grab more market share in 5G when the mass adoption of 5G RedCap will take place.

5G RedCap will serve the use cases in industrial, enterprise and consumer applications, like smart wearables, medical devices, XR glasses, health monitors, video surveillance cameras, wireless industrial sensors, utility/smart grid applications and even Fixed Wireless Access (FWA) and customer premises equipment (CPEs).

5G eRedCap is likely to be preferred for the applications served by 4G Cat 1, such as tracking devices, charging stations, micro-mobility and battery-powered sensors.

Conclusion

5G RedCap promises to broaden the 5G ecosystem, facilitating more connections. It fills the gap between LPWA and URLLC, simplifying 5G integration in IoT applications. 5G RedCap and eRedCap modules will be cost-effective, enabling OEMs to manufacture less complex, low-cost devices with lower power consumption, something that standard 5G cannot offer.

Though 5G at the IoT level is a few years out, vendors can create devices operable over LTE, with an easy switch to RedCap by changing the communication module. This allows immediate product deployment, with an easy future transition to 5G RedCap as the standard evolves.

5G RedCap’s flexibility and network advantages, including lower latency and higher speeds compared to previous LTE generations, position it as a superior choice for future mass IoT deployment. Numerous potential connections across consumer, industrial and enterprise verticals such as FWA, CPE and vehicle connectivity will greatly benefit, accelerating IoT adoption on a massive scale.

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Netgear Q2 Gets Premium Push, Inventory Stabilization Seen in Q3

Netgear’s Q2 2023 revenue declined 22.3% YoY to $173.4 million.
Inventory correction in H1 2023 totaled $66 million.
Orbi, Nighthawk, 5G mobile hotspots and Pro AV will drive revenues in Q3 2023.
Netgear expects the Q3 2023 revenues to be in the range of $175-$190 million.

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Netgear’s revenue declined 22.3% YoY in Q2 2023 to $173.4 million, coming at the higher end of the guidance primarily due to an increase in orders from the service provider channel. The company experienced an inventory correction worth $29 million in Q2 2023, taking the H1 2023 inventory corrections to $66 million. As the inventory levels begin to stabilize, we expect the inventory spills will be 20% lower in H2 2023 compared to H1 2023.

Premium offerings, Pro AV switches shine amid revenue declines in both segments

Connected home and SMB (small and medium business) segments suffered declines of 24% and 21% YoY, respectively, in Q2 2023 primarily due to inventory corrections at channel partners.
Gross margin continued to be above 30% in the second quarter as premium product sales grew and freight costs went down.
However, the operating margin continued to be in the negative region as inventory correction amounted to over $29 million. It is expected to improve in Q3 with an improved mix of higher-ASP products in the connected home and SMB segments.
The retail market is starting to stabilize with consumer demand increasing toward premium networking equipment as the number of Wi-Fi-enabled devices continues to increase. As home networks become more crowded with bandwidth-hungry devices, the demand for Mesh routing devices will increase with time to ease out home networks.

The end consumer devices have become more feature-rich, especially with AI (artificial intelligence) which now requires more bandwidth, low latency and more reliable Wi-Fi connection. This has led to strong consumer demand for premium routers offering such features.
The Orbi and Nighthawk series of routers continued to perform well for Netgear along with 5G mobile hotspots and experienced a YoY increase in shipments in Q2 2023.
Pro AV-managed switches continued to outperform other end devices in the SMB segment to deliver a growth of more than 40% YoY in Q2 2023. Netgear is significantly committed to building leadership in IP-over-AV switches and continues to invest more to grow this segment.
Other SMB products experienced a major drop in sales due to macroeconomic headwinds affecting enterprise spending in the past couple of quarters, delaying the upgrades to newer Wi-Fi technologies.

Revenues from service providers, in APAC and Europe decline significantly

Though service provider revenue increased sequentially in Q2 2023 to $25 million, it suffered a decline of 30% YoY. Revenues were at the higher end of the guidance due to an increase in orders from a major service provider.
Netgear shipped around 6 million units of wired and wireless networking devices, compared to 2.2 million in the same period last year. It shipped around 426,000 units of all types of routers and gateways.
Sales in APAC and Europe declined 20% and 40% YoY, respectively, due to an economic slowdown in these regions, especially Greater China and South Korea.

Paid subscribers to reach 875,000 by year-end, inventory corrections to stabilize

Netgear is on the path to achieve a paid subscriber base of 875,000 by the end of 2023 as it touched 800,000 in Q2 2023. Revenue from subscriptions grew 8% YoY in Q2 2023 to end at $10.3 million.
With concerns about internet security on the rise, especially with a growing number of smart devices, online internet security software is expected to gain momentum in the second half of this year.

Netgear expects the revenue to be in the range of $175 million to $190 million in Q3 2023, as inventory correction is expected to ease out. However, it will still take two more quarters for Netgear to bring down inventory-carrying levels to less than 10 weeks.

Key takeaways

Counterpoint expects an increase in shipments for 5G mobile hotspots in H2 2023 as the consumer demand for such products is on the rise. Netgear is expected to launch a couple of Wi-Fi 7 Orbi Mesh routers and quadband Nighthawk routers in Q3 2023.
However, Wi-Fi 7 upgrade cycle is expected to begin sometime in mid-2024, as IEEE is yet to announce the schedule of the certification program for Wi-Fi 7. Therefore, Wi-Fi 6/6E is expected to form more than 50% of the market in the next two years.
Netgear is expected to open more company-owned premium retail outlets which will help it to provide a better customer experience and a competitive edge in the market.
Consumer awareness around online internet security remains low. Netgear can play a part in increasing consumer awareness through its D2C (direct-to-consumer) communication channels.
Macroeconomic headwinds have slowed down enterprise spending, thus delaying the Wi-Fi upgrade cycle toward Wi-Fi 6/6E.
5G FWA market has been performing well across most of the regions. With more regions opting to reduce the digital divide through FWA, the market promises to offer further growth and become a challenger to fixed broadband technologies.

Related Research

5G Advanced and Wireless AI Set To Transform Cellular Networks, Unlocking True Potential

The recent surge in interest in generative AI highlights the critical role that AI will play in future wireless systems. With the transition to 5G, wireless systems have become increasingly complex and more challenging to manage, forcing the wireless industry to think beyond traditional rules-based design methods.

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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