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.

Huawei Intelligent RAN Solutions

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.


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.

Related Posts

US October Spectrum Auction to be Crucial for AT&T, Dish

Applications are in and a date is set. On October 5, the Federal Communications Commission of the US will hold another mid-band spectrum auction, following last year’s Citizens Broadband Radio Service (CBRS) spectrum auction and the record-setting C-band auction that took place in early 2021. While the bidding this time around won’t reach near the levels seen at the C-band auction, it will be pivotal for players like AT&T and Dish, which need to shore up their spectrum holdings to keep up with competitors.

AT&T is likely to be the most aggressive bidder in the upcoming auction. While AT&T and Verizon have both expanded their mmWave networks in 2021, they are facing significant pressure from T-Mobile, which enjoys a major advantage due to the 160 MHz of 2.5 GHZ spectrum obtained through its merger with Sprint. T-Mobile has since been rolling out its mid-band 5G network that now covers over 165 million Americans. This far outpaces AT&T and Verizon and has left them scrambling to catch up.

Verizon largely addressed its mid-band spectrum needs in February’s C-band auction, where it spent a remarkable $45 billion to more than double its mid-band holdings. AT&T was a distant second, spending about $23 billion. With T-Mobile’s substantial existing mid-band network and Verizon’s spectrum lead, AT&T has some catching up to do.

Counterpoint Research

Source: Raymond James, Counterpoint Analysis

Despite its network lead, some are expecting T-Mobile to emerge as the second-highest bidding operator on October 5. T-Mobile’s lead in terms of spectrum holdings was significantly cut down following the C-Band auction and the operator may be looking to try and build its lead back up. Meanwhile, Verizon is not expected to participate beyond driving up prices. With its gargantuan spend in the C-band auction, Verizon has little need for more spectrum and instead must focus on building out its network infrastructure and delivering mid-band 5G to consumers.

Top Spenders at Mid-band Spectrum Auctions

Outside of the major carriers, it is expected that Dish will make a play for more spectrum as it works towards building out its own 5G network over the next several years. After sitting out of the C-band auction and its 5G network launch later this year in Las Vegas, Dish will have to shore up its holdings to compete with the major operators.

Conspicuously absent from the application list for the 3.45 GHz auction are Comcast, Charter and Altice. Each of these MVNOs sat out of the C-band auction but were major players in the CBRS auction in 2020. While each would likely benefit from greater spectrum holdings, it seems they are still in the process of operationalizing their CBRS spectrum, which could take until 2023. Since it will be a while until these players have the resources to establish significant networks of their own, they have little need for more spectrum until then.

With all of this said, the upcoming 3.45 GHz auction won’t be the massive auction that the C-band auction was. But it will play a significant role in the competition between the major carriers, as well as Dish’s ability to create an effective 5G network. AT&T, T-Mobile and Dish are likely to be the top spenders, while Verizon could creep into the mix if it tries to bid up prices.

10 Predictions for LATAM Smartphone, Devices Ecosystem in 2021

The LATAM smartphone and devices ecosystem has been one of the least impacted by the COVID-19 pandemic. Many of the trends mentioned below started in 2020 and will further strengthen in 2021. The pandemic has shown that technology and devices are essential allies through a calamity and will thus contribute to steering the LATAM economy back to growth.

  1. LATAM will have at least 22 operators launching 5G networks. But all of them will have limited coverage, with most of them being non-standalone (NSA) networks. These 22 will be in addition to the nine operators which launched 5G services during 2020.
  2. At least six LATAM countries will auction 5G compatible spectrum. Brazil, Chile, Colombia, Costa Rica, Dominican Republic, Mexico, and Peru have announced plans to auction spectrum that will enable operators to deploy stand-alone (SA) networks and offer commercial 5G plans.
  3. 5G smartphones will start to take off in 2021, but not quite. 5G phones will unlikely bag more than 5% share in the region. Apple and Samsung will drive the growth of this segment in LATAM during 2021. Although 5G technology will reach the $150-$200 price band smartphones, buyers under this band will instead focus on having a better camera, a bigger screen, or more memory. 5G will not drive smartphone replacement in the region.


Exhibit 1: LATAM Technology Share, 2018-2021

Counterpoint Research LATAM Technology Share, 2018-2021
Source: Counterpoint Research Market Monitor and Market Outlook, Q3 2020
  1. The market will see double digit growth in 2021. Although the overall economy will continue to struggle, smartphone sales in 2021 are expected to grow more than 19% YoY. Even if there is a second or third wave of COVID-19, the demand will not decline. It will decline only when there is some disruption in the supply chain.
  2. Chinese brands’ participation will grow, but slowly. Huawei’s share will continue to decline. Despite the regime change in the US, the trade ban on the company is unlikely to be lifted soon. Many Chinese brands are entering the region, seeking to grab the share shed by Huawei.
  3. Smartphone ASP might return to growth.In 2020, the ASP decreased slightly but consistently each quarter. The entry of newcomers with aggressive plans may trigger a price war. This will benefit consumers and convince them to spend slightly more while acquiring a new smartphone.
  4. Several countries will increase taxes on smartphones. As COVID-19 left many economies shuttered and some governments broke, smartphones will come under the tax scanner in many countries. Although the OEMs might absorb a part of the increased cost, it will ultimately impact the overall smartphone market ASP.
  5. Online channels will see an increase in smartphone sales. Online sales are here to stay. In 2020, online sales in LATAM increased by at least 60% YoY. This growth will continue in 2021 but at a slower pace, trapped by the reality that only 55% of the region’s adult population has access to the banking system (according to the Alliance for Financial Inclusion), compared to 95% in Europe.
  6. Contactless payment technology to see increasing adoption. COVID-19 accelerated the adoption of this technology in LATAM. All leading banks in LATAM are now launching an NFC (near-field communication) payment platform. Companies like Samsung, Mercado Libre and Facebook are also looking to tap into this trend. On the other end, an increasing number of stores are acquiring contactless payment technology. As the pandemic is still on, this trend will grow.
  7. IoT devices will surge in the region. With the pandemic, many businesses have realized that it is essential to accelerate digital transformation to stay efficient. On the other hand, operators are pushing IoT solutions while looking for a new stream of revenue. At the consumer level, as many people continue to remain stranded at home, smart home and hearable devices will receive an extra boost. In particular, devices related to security, home entertainment and household tasks will be in demand.

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