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Muskspeak on Cybertruck, Price Cuts, FSD Timing as Tesla Hits New Records in Q2

The US remains the top market for Tesla followed by China and Europe.
Aiming to develop an in-house AI ecosystem, Tesla has started building its own Dojo training supercomputer.
With this growth trajectory, Tesla is expected to achieve sales of around 1.9 million units by the end of 2023.

Tesla achieved remarkable results in Q2 2023, with its revenue growing 47% YoY to reach the record-breaking figure of nearly $25 billion. The company’s vehicle deliveries too hit a record at 466,915, growing 83% YoY. The US retained its position as Tesla’s largest market, contributing to 37.6% of the total sales, while China and Europe followed closely behind. Global price cuts for the Model Y and Model 3, along with tax subsidies in the US and China, were two of the biggest drivers for Tesla’s Q2 sales.

Tesla CEO Elon Musk, during the earnings call, discussed a few key things like the long-awaited Cybertruck deliveries, Tesla’s advantage in competitive pricing of vehicles and the possibilities of attaining complete FSD:

Cybertruck delivery outlook

CEO: “Demand is so – so far, off the hook, you can’t even see the hook. So, that’s really not an issue. I do want to emphasize that the Cybertruck has a lot of new technology in it. Like a lot… So, always very difficult to predict the – the ramp initially, but I think we’ll be making them in high volume next year, and we will be delivering the car this year.”

Soumen Mandal’s analyst take: “Musk is certainly hyping the Cybertruck, not that it needs to anymore, but there is also significant expectation setting with discussions on internal production and supply chain hurdles. Is this another Model Y? That’s a tough act to follow, but the Cybertruck does bring a slew of unique parts and processes. So, longer term, we expect to see another products flywheel off from it.”

Tesla’s price cuts for its vehicles

CEO: “And we, you know — we just — we just course according to what the mood of the of the public is, you know. Buying a new car is a — it’s a big decision for vast majority of people. So, you know, anytime there’s economic uncertainty, people generally pause on new car buying, at least to see to see what happens.

And, you know — and then, obviously, another challenge is the — the interest rate environment. As interest rates rise, the affordability of anything bought with that decreases, so effectively increasing the price of the car. So, when interest rates rise dramatically, we actually have to reduce the price of the car because the — the interest payments increase the price of the car. So — and this is at least — at least up until recently was to believe the sharpest interest rate rise in history. So, we had to do something about that. And if someone’s got a crystal ball for the global economy, I really appreciate it. If I could borrow that crystal ball.”

Soumen Mandal’s analyst take: “Tesla’s strong supply chain and reduced cost of production due to low raw material cost, especially for lithium, has encouraged the company to reduce prices of its vehicles. Alongside what Musk described as ‘interest rate rises’, Tesla’s price reduction has made all variants of the Model 3 and Model Y eligible for IRA tax credit in the US, where it will benefit in the long term. So, macroeconomic policies and geopolitical relations play a crucial role in deciding such price reductions, incentives or discounts.”

Autonomy (FSD): Timing

CEO: “…the reason I’ve been optimistic [on achieving full self-driving] is what it tends to look like is the — we’ll make rapid progress with the new version of — of FSD. But — but then, it will curve over logarithmically. So — so, at first, like, a logarithmic curve looks like, you know, just sort of fairly straight upward line, diagonally up. And so, if you extrapolate that, then you — you have a great thing. But then because it’s actually logarithmic, it curves over. And then, there have been a series of logarithmic curves. Now, I know I’m the boy who cried FSD, but man, I think — I think we’ll be better than human by the end of this year.”

Abhik Mukherjee’s analyst take: “Almost every auto OEMs are spending on autonomy. Tesla is also walking in the same direction and is building an in-house AI service that includes in-house real-time data sets, neural Net training, vehicle hardware and software. Tesla is expecting to reach perfect FSD soon and for this, it is also building a Dojo supercomputer. Early development of FSD will give Tesla a massive first-mover advantage over its competitors. We assume Tesla FSD might also get adopted by other automakers, like Tesla NACS is being adopted.”

Autonomy (FSD): Disruption

CEO: “It’s not about getting more share. It’s just that you can think of every car that we — that we sell or produce that — that — that has a full Autonomy capability as actually something that, in the future, may be worth as much as five times what it is today…If you’ve got an autonomous — if that vehicle is able to operate autonomously and — and use — be used in either dedicated or autonomous or partially autonomous like — like, Airbnb, like maybe sometimes you allow your car to be used by others, sometimes you want to use it exclusively, just like, you know, Airbnb, you know, doing Airbnb with a room in your house… So, I think it’s sort of it would be — I think it — it does make sense to sacrifice margins in favor of making more vehicles because we think, in the not-too-distant future, they will have a dramatic valuation increase. I think the Tesla fleet value increase to the point at which we can upload full self — you know, full self-driving and it’s approved by regulators, will be the single biggest step change in asset value maybe in history.”

Abhik Mukherjee’s analyst take: “Although we are excited about autonomous vehicles, Tesla currently is a bit far from achieving perfect FSD. Incidents involving Tesla vehicles are frequently reported. Currently, Tesla FSD is only available in the US and it will need a lot of approvals from regulators to ensure 100% safety before it can be rolled out to other regions, especially in Europe where regulations are much stricter. Though achieving complete FSD could disrupt the market in future, currently Tesla must work to make its FSD software incident-free.”

Financial highlights

In the automotive segment, Tesla achieved revenue of $21.26 billion, an annual growth of 7%. Around 4% of this revenue was derived from sales of regulatory credits and automotive leasing.
In addition to the automotive segment, Tesla experienced significant growth in its other businesses, such as energy generation and services, with revenues surging by 57% YoY to reach $3.65 billion in Q2 2023. Tesla deployed 7 GWh of energy storage and 66 MWh of solar panels during the quarter.
Tesla achieved a gross profit of $4.53 billion, a 7.1% YoY increase. High vehicle deliveries, low cost of production due to lower raw material costs and IRA tax credits for EVs in the US contributed to this result. But the low ASP of vehicles due to the voluntary global price cuts also hurt Q2 profitability.
Tesla’s Q2 operating profit was 62%, a decline of 1.8 percentage points sequentially. The reduction can be attributed primarily to the significant expenses incurred in ramping up the production for Cybertruck, Tesla’s in-house 4680 cells and the development of AI through its Dojo training computer. Other additional costs were associated with a new ‘Get to Know Your Tesla’ UI and facelifts for the Model 3 and Model Y.

Outlook

With the current growth trajectory, we expect Tesla deliveries will reach around 1.9 million by the end of 2023. Its robust supply chain and vertically integrated production have given Tesla a competitive advantage.

Other growth opportunities are arising from the adoption of Tesla’s NACS charging standard by several OEMs including Ford, GM, Rivian, Volvo, Polestar and Nissan for the North American market. This allows these auto companies to leverage Tesla’s extensive network of charging stations across North America, enhancing the convenience and accessibility of electric vehicle charging for their customers. But it also gives Tesla the option to increase its revenue by charging licensing fees from OEMs adopting its proprietary NACS ports.

5G Rollouts in Emerging Economies Aid Q2 Numbers of Ericsson, Nokia

Ericsson and Nokia’s Q2 2023 results are in line with their revised expectations.
The telecom gear manufacturers are convinced that a few short-term hurdles can be managed to drive growth.
The mobile network segment, the largest contributor to both firms’ revenues, witnessed some slowdown in Q2 2023 due to decreased demand from capex-saturated regions.

Nordic telecom giants Ericsson and Nokia announced their Q2 2023 results last week, which were in line with their revised expectations despite lower revenues. The overall market condition remains challenging due to macro uncertainty, but the telecom gear manufacturers are convinced that a few short-term hurdles can be managed to drive growth both in the short term and long term.

Fast 5G rollouts in emerging nations such as India were highlights for both the vendors as revenue growth in these regions was able to offset the sales decline in North America and North-East Asia where operators slowed down their network expenditures after several quarters of high investment.

Swedish giant Ericsson generated net sales of $5.9 billion for the quarter, reporting a 9% YoY decline in organic sales. Ericsson’s Finnish counterpart Nokia generated $6.2 billion in revenue for the quarter, which was flat YoY on a constant currency basis.

Mobile network segment

This segment is based on the core competence of these organizations and is also the largest contributor to both firms’ revenues. It witnessed some slowdown for the two companies in Q2 2023 on the back of decreased demand from capex-saturated regions. Operators in these regions continue to be selective in spending and are depleting their inventories that have been running high after the 2021-2022 boom.

Revenue from Ericsson’s Networks division stood at $3.9 billion. It doubled for emerging markets like India and Southeast Asia but plummeted for regions like North America. India is now Ericsson’s second-biggest market. During the quarter, the company also marked the shipping of 10 million 5G-ready radios.
Revenue from Nokia’s Mobile Networks division stood at $2.85 billion, a slight growth YoY. The increase in revenue due to faster 5G rollouts in India and Europe was able to offset the decline in North America.

Gross margin was impacted for both operators as the sales mix changed drastically. Adapting to changing demand and expecting a recovery in the North American region, both manufacturing firms are looking forward to an improved gross margin by the end of this year.

Cloud software services

Telecom service providers too have been hit by cloud disruption as network evolution has witnessed operators migrating to the cloud. The two Nordic vendors have been at the forefront in assisting operators in transitioning to cloud-native operations, which helps in future-proofing and improving network performance and efficiency.

Ericsson’s revenues from its Cloud and Software Services division stood at $1.39 billion, a marginal increase over the previous year. The sales, for a change, were driven by 5G in the North American region. Ericsson currently leads the global market for 5G Standalone Core deployments with a majority of operators choosing the Swedish company for their cloud-native 5G SA Core. Ericsson’s managed services, however, took a hit.
Nokia registered $806 million in net sales for its Cloud and Network Services division. Unlike its Swedish counterpart, Nokia’s growth came from the Europe and Middle-East and Africa (MEA) regions, while it faced a decline in the North American region. Nokia too has been actively helping operators worldwide to deploy 5G Standalone Core (just behind Ericsson in the number of deployments), which alongside Enterprise Solutions helped boost its revenues in this segment, marginally offset by declines in the Cloud Services and Business Applications.

Ericsson’s enterprise segment, network APIs and IPR licensing

Last year, Ericsson acquired Vonage, which contributed revenues of nearly $390 million during the quarter, a 12% increase YoY. The company strongly believes that the enterprise segment will continue to grow as it redefines how the capabilities of 5G networks are utilized and paid for by the customers.
Ericsson will also continue to digitize the ecosystem for CSPs by maintaining its investments to build the Global Network Platform (network Application Program Interfaces or APIs). With time, a variety of global network APIs will complement the existing communication APIs like video, voice and SMS to help CSPs better monetize their 5G networks, accelerate 5G network rollout and improve network capex.
The company also signed a 5G IPR licensing agreement during this quarter to help validate its IPR portfolio strength.

Nokia’s diverse portfolio – Networks infrastructure and enterprise

Despite facing some short-term challenges and macroeconomic uncertainty, which resulted in a YoY revenue decline, Nokia’s Network Infrastructure segment generated $2.15 billion in revenues and continued to gain market share across the globe.
- The IP networks grew in Europe with increasing sales to enterprise customers.
- The optical networks unit registered a double-digit growth driven by increasing broadband penetration in India.
- The fixed networks unit witnessed a decline on the back of slowing FWA deployments in North America.
Nokia’s revenue from its enterprise customers grew by almost 30% YoY. The company added 90 new enterprise customers this quarter. Its private wireless business reached more than 635 customers.
Nokia also signed a long-term patent license agreement with Apple. Multi-year revenue recognition might start in January 2024.
Nokia also struck an important deal with Red Hat this quarter, where the latter will serve as the primary reference platform to develop, test and deliver core network applications in an attempt to rebalance Nokia’s portfolio.

Analyst outlook

Network equipment vendors and software providers are looking to transform obstacles into opportunities. Both Ericsson and Nokia are expecting their business performance to improve towards Q4 2023 and to continue improving in the coming years. Inventory correction by operators has been the prime reason for the revenue decline this quarter. But network sales have been able to weather the slowdown as operators need to increase the capacity of their networks.

Counterpoint Research believes that 5G investment has not yet peaked. Over the next few years, the industry will witness the advent of 5G Advanced starting with 3GPP Release 18, operators transitioning to 5G SA, an increase in the number of monetizable 5G use cases, FWA going global, and increased 5G investments in mid-band and mmWave bands. The entire mobile industry is bullish about private networks, which present a significant opportunity for operators and vendors alike. Amid the growing geopolitical turbulence, with the West hardening its stand on the “rip and replace” of Chinese networking equipment, Nokia and Ericsson might even see other markets opening up for them. Reducing internal costs and streamlining internal operations remains a challenge for both suppliers. The two should benefit from growing confidence in the enterprise segment. Nokia expects to leverage its leadership in the network infrastructure business and attain market leadership in the fixed-broadband space with its wide variety of ONTs, OLTs and FWA CPEs.

NVIDIA and Softbank Developing AI-Based 5G MEC Telco Network

NVIDIA and Softbank recently announced that they had developed a dual-purpose AI-driven 5G MEC and vRAN distributed platform based on NVIDIA’s new GH200 Grace Hopper superchip. The two partners intend to deploy a network of regional data centres across Japan later this year to capitalize on the demand for accelerated computing and generative AI services. The shared multi-tenant platform will also offer a range of 5G vRAN applications and Softbank is creating 5G applications for autonomous driving, AI factories, augmented and virtual reality, computer vision and digital twins.

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

Table of Contents:

Snapshot
Key Highlights
– 5G MEC Telco Network
– Grace Hopper Superchip
– Leveraging Software Resources
– Performance Details
– Use Case and Deployment Options
– Key Partners
– Competitors
Analyst Viewpoint
– Platform Limitations
– Benefits of RAN-in-the-Cloud
– Eliminating RAN hardware dependency
– The Intel vs ARM battle
– Leveraging GPUs in the RAN
– A Crowded Market

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Related Reports and Blogs

Open RAN Networks – Layer 1 Acceleration Strategy Will Be Key To Operator Success

In-line, PCIe-based accelerator cards will be essential to process latency-sensitive, Layer 1 workloads in COTS-based massive MIMO open RAN networks.
Accelerator card energy efficiency will be a key differentiator among vendors as could the degree of Layer 1 stack openness.

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

Cloud RAN – Waiting for a Viable Business Plan?

The Emerging Cloud RAN Ecosystem – Players and Solutions

Cloud RAN – Technology Review and Market Challenges

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

AI/ML Key in Enhancing 5G Network Efficiency, Reducing Complexity

5G network has seen steady growth in deployment globally, with the total number of subscribers of 5G services crossing the billion mark. Although most of the deployment has been through the Non-Standalone (NSA) mode, the Standalone (SA) core will see big commercial deployment in the years to come to explore the full potential of 5G, including venturing into newer 5G applications such as Network Slicing. To provide high bandwidth and low-latency connectivity with processing capabilities at the Edge to support enterprise and mission-critical use cases, it becomes important to manage the network effectively and autonomously, and AI/ML can help in this case. As the algorithm is advancing every day, AI/ML can help automate most of the tasks. The huge amount of data collected by network vendors and operators can be used to train an effective algorithm, thereby helping in the effective management of resources.

Some of the verticals where AI/ML will be useful in network management are:

Intelligent Network Automation

5G networks are complex and managing them is a difficult and expensive task. AI/ML can provide intelligent algorithms that can automate various network management tasks, thus reducing the time and resources required to manage the network. AI can help in managing the network traffic, as an increasing number of devices connected to a network makes it harder for an operator to monitor the usage, and the algorithm can monitor the network traffic pattern and optimize it, and allocate resources based on the devices’ bandwidth requirements, thus ensuring the efficient use of resources.

AI can also be used to get insights into network behavior, which can be used to identify bottlenecks and anomalies in the network that can cause security issues.

RAN Enhancement

AI can help improve network energy savings by managing energy usage. The algorithm can optimize the transmission power of base stations for the devices based on their proximity. Another application can be the activation of sleep mode to reduce energy consumption when there is less network load on the base station or it is idle.

AI can also be used for precision planning in small-cell deployments. The ever-increasing demand for data is congesting the network in some areas, especially in urban and compact spaces such as stadiums. To solve the problem, small cells are required to be deployed. AI can analyze the data on network traffic and latency, and identify the black spots where small cells can be deployed. It can also help in identifying suitable locations for small-cell deployment so that not many cells are deployed at a site.

Source: Huawei

Huawei has launched intelligent RAN solutions iFaultCare and iPowerStar. The company claims that its iPowerStar AI-based intelligent RAN solutions can generate power savings of 25% and reduce OPEX by 20 million KWh per year, whereas iFaultCare can improve troubleshooting efficiency by 40%.

Network Management

One of the major use cases of automation will be network management. The algorithms can monitor the network metrics, such as load factor, traffic and latency, and adjust them to optimize the performance. Another way in which AI can help is by improving network reliability through the prediction of issues that may arise. The algorithm can analyze the network data to identify patterns that may lead to outages, thus allowing time for preventive action.

Network Security

In 5G, we are going to see an increasing number of connected devices along with an increasing volume of data transmitted across the network. With an increasing number of devices, the potential for cyberattacks also increases, and operators must enhance cybersecurity to prevent a possible attack on the network. Critical use cases such as private networks are more prone to cyberattacks, which can result in revenue losses to the enterprise. AI can come in handy in preventing cyberattacks. It can help identify potential threats, such as malware or phishing attacks, and respond quickly to mitigate the risk. Besides, AI can play a significant role in 5G network security by detecting, analyzing, and responding to security threats in real-time. With the past dataset provided to analyze network behavior, the algorithm can identify patterns and anomalies that may lead to cyberattacks. AI algorithms, for instance, can recognize a potential security breach if a certain device is transmitting an unusually large volume of data. It can then take appropriate steps to prevent any damage.

MIMO

AI can help in effective MIMO management. The algorithm can analyze the network and adjust the number of MIMO antennas to be used for optimized device performance. AI can also be helpful in beamforming, a technique that allows the transmitter to focus its energy in a specific direction to improve network coverage and capacity. The algorithm can identify from where the demand is coming and ensure that sufficient bandwidth is provided to the device. By effective use of beamforming, operators can provide high-speed, low-latency services to different devices and applications.

Network Slicing

Network slicing is one of the most discussed topics in the industry. It is being touted as one of the important use cases for 5G networks. Network slicing is a technique that allows operators to create multiple virtual networks on top of a shared physical infrastructure. Each virtual network can be designed to meet the specific requirements of a particular use case, such as high-speed data transfer and low latency. AI can be of immense help in network slicing, as it can automate most of the prerequisite tasks, such as:

Preparing the network: The algorithm can use past data to predict the demand that might come from the user.
Resource reservation: The algorithm, after predicting the demand, can slice the network and reserve it for the task which the network might be getting.
Resource allocation: Once the requirements come from the user, the reserved resource can be allocated to the user.

5G Advanced

Networks are becoming complex and AI/ML-based solutions are being used to reduce the complexity and make the network more intelligent. Introduced with Release 15, and with subsequent enhancements in Releases 16 and 17, AI/ML is being used for different use cases, such as network energy savings, network load balancing and mobility optimization.

Release 18 will be looking to incorporate more enhancements for automating the network and predicting the network behavior to make it efficient. Different areas are being looked into to study the potential of AI/ML for different elements of air interface, such as beam management, mobility, and position accuracy.

Drawbacks of AI/ML

Although AI offers lots of benefits in effectively managing the network and automating most of the tasks, it also has some deficiencies. One of the biggest problems faced in writing an effective algorithm is getting a large amount of reliable and relevant training data. Bigger players have access to large amounts of data and resources to train their models, whereas smaller players lack them and have to rely on other players to get the algorithms, which might not be relevant for their use cases. A lack of appropriate training data can make the model less reliable and relevant, and it might produce undesired outcomes.

Some of the challenges which an AI algorithm can face are:

Complexity: Implementing AI technology in 5G is a complex task and it requires significant investments in resources. Besides, the AI algorithm needs to be effectively trained and tested before being deployed, to ensure that it provides the desired outcome.
Bias: AI algorithms are trained on the data they get. If the data on which they are trained is biased or skewed towards one side, then it can generate biased results and could lead to the wrong label of false positives or false negatives.
Privacy: Privacy has become one of the most important issues today for AI algorithms, as the algorithm needs data to be trained upon, but some of the data might contain sensitive information. Privacy laws must be in place to ensure that sensitive information is not used for inappropriate purposes.

Ericsson's Cradlepoint Launches NetCloud Private Networks Solution

Last week, Cradlepoint announced the launch of its subscription-based NetCloud Private Networks solution, an SME-type enterprise solution targeted at office buildings, retail outlets, stadiums, hospitality venues, smart city, schools, etc. It will complement Ericsson’s Private 5G product which is designed primarily for industrial applications such as manufacturing, energy and utilities, etc, where low-latency, high reliability and business-critical capabilities are essential.

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.

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

India 5G Smartphone Shipments to Cross 4G Shipments in 2023

Cumulative 5G smartphone shipments will cross the 100-million mark in Q2 2023 and exceed 4G smartphone shipments by the end of 2023.
India’s 5G smartphone shipments are estimated to grow 81% YoY in 2022 driven by their expanding presence in lower price bands (<INR 20,000 or ~$244) and rollout of 5G networks.
5G share in lower price bands (<INR 20,000 or ~$244) is gradually increasing, from 4% in 2021 to 14% in 2022.

India’s smartphone shipments are projected to witness a yearly decline in 2022 due to macroeconomic factors affecting consumer demand in the entry and budget segments. However, 5G has been a driving force and will continue to push smartphone demand in 2023 as well. India’s 5G smartphone shipments are estimated to grow 81% YoY in 2022 driven by their expanding presence in lower price bands (<INR 20,000 or ~$244) and rollout of 5G networks in the latter half of the year.

According to Counterpoint’s India Market Outlook, cumulative 5G smartphone shipments will cross the 100-million mark in Q2 2023 and exceed 4G smartphone shipments by the end of 2023. Our latest consumer study also reveals that 5G is the third most important factor for future smartphone purchases.

India 5G vs 4G Smartphone Shipment Penetration

Source: Counterpoint Research India Smartphone Outlook, November 2022

5G share in lower price bands (<INR 20,000 or ~$244) is gradually increasing, from 4% in 2021 to 14% in 2022. It is expected to reach 30% in 2023. The cost of an entry-level 5G smartphone came down to below INR 10,000 (~$122) in 2022 with the launch of the Lava Blaze 5G. The availability of cheaper 5G chipsets from Qualcomm and MediaTek has enabled OEMs to launch more 5G devices in the lower price segment, while the commercial rollout of 5G services has also driven demand for the same.

Source: Counterpoint Research India Smartphone Outlook, November 2022

However, the growth here has been limited due to component supply shortages, inflation, geopolitical conflicts and other macroeconomic issues, which have delayed 5G device launches in the budget segment. Though OEMs have brought more 5G devices for lower price bands (<INR 20,000 or ~$244), they have done so by dropping or downgrading other key features like display or fast charging to lessen the impact of increasing component costs. This, in turn, has affected the consumer demand for 5G within this price tier. The limited availability of 5G networks has also affected the demand.

We expect these constraints to ease by the end of 2023, leading to the mass adoption of 5G. Better availability of networks in major areas will also facilitate 5G smartphone growth in 2023, which is estimated to be 62% YoY.

Counterpoint Research Forecasts Private Networks Market To Reach $21.8 billion by 2030

Counterpoint Research forecasts that the global LTE/5G private networks infrastructure market will increase from approximately $2.5 billion revenues at the end of 2022 to reach $21.8 billion at the end of 2030, representing a CAGR of 30.7% over the forecast period (Exhibit 1).

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

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Private Networks – High Expectations Amid and Expanding Ecosystem

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Private Cellular Networks – Devices Key To Growth in Unlicensed Spectrum

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

TELUS Picks Up Subscribers in Q3 After Rogers’ Network Outage

TELUS had an excellent third quarter with YoY growth across all segments. The earnings call focused on the lack of churn in this quarter and the dependability of TELUS’ network, with no direct reference to the Rogers nationwide outage that caused a standstill in the country at the beginning of July. But the mobile gross additions during Q3 2022 were at their highest for TELUS since before the pandemic. Even as TELUS saw great success in its mobile segment, its other segments like IoT, TV and wireline also saw significant growth this quarter.

Information Source: TELUS

TELUS continues to keep churn low; Expands 5G Coverage by 23%

While emphasizing on customer loyalty and lower churn, TELUS highlighted that this was the eighth quarter out of the last 11 where the postpaid churn was below 0.80%. The quarter saw 0.73% churn for the postpaid segment and 0.95% when combined with the prepaid segment.
Mobile phone ARPU increased 2.3% YoY. This was attributed to the adoption of 5G+ plans that customers are upgrading to. The early launch of the iPhone 14 series would also help boost ARPU as carriers are a dominant sales channel for these devices.
Service revenue was up 4.2% YoY. Mobile network revenue was also up 6.8%. Roaming revenues continued to increase to approach pre-pandemic levels as people continued to travel and absorb roaming fees. The upgrade to 5G+ plans also contributed to the increase in mobile network revenue.
5G expansion has been progressing fast for TELUS, with the total 5G population coverage increasing 22.8% to 29.6 million as against LTE’s 37 million.

Information Source: TELUS

Growth in connected devices category slowed down

Connected devices have been a large growing segment for TELUS in the past year, with the sales of smartwatches, tablets and other IoT devices increasing at the carrier. Connected device sales saw an increase of 15.1% from Q3 2021.
Wireline saw 36,000 internet net additions, not as strong as the 46,000 net additions last year. Total internet subscribers saw a YoY increase of 6.3% in Q3 2022.
TV net additions saw large growth at 18,000, up 8,000 from last year to result in a 4.9% increase YoY.

TELUS continues to strengthen its position in Healthcare and Security

Healthcare has been a growing focus for TELUS outside the wireless industry as COVID-19 proved the need for better connectivity within the healthcare system. TELUS has been able to add 1.7 million virtual healthcare members to its Lifeworks network in the past year. It can accommodate up to 60.4 million people.
Security devices and memberships have also seen a spike this year for TELUS, with total subscribers to the service now reaching 950,000, a 22.9% increase YoY. Ecosystem OEMs like Google have developed smart doorbells and house cameras with connectivity to smartphones, which has boosted this segment significantly.
New global metrics show a 19.3% revenue increase for the technology and games segments of TELUS. With cloud and mobile gaming gaining popularity, these metrics will invite an increased focus from carriers.

Overall, TELUS has had great success this year, not only boosting its wireless market but also quickly expanding its other businesses in sectors like healthcare and security. Apple iPhone 14 series significantly contributing the the late Q3 success of device sales, as per Counterpoints North America Channel Share Tracker. TELUS is on track to meet the 2022 guidance it had set at the end of last year. TELUS has already reached the goal of 10% growth in adjusted EBITDA and 9.9% growth in operating revenues YoY. The consolidated targets are attainable in Q4 as strong sales of flagship devices continue to drive the market and roaming fees continue to climb with travel becoming easier the world over with the gradual lifting of COVID-19 curbs.

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