Summary Bullets:
• RAN vendors are exploring how AI can improve RAN operations, including through the use of both RAN-specific AI operations and multi-agent coordination to assess faults and recommend improvements.
• AI RAN is also being used to support new services, as equipment vendor ZTE illustrated with an AI-enhanced small-cell solution in a car dealership that supports livestreaming in the building.
RAN vendors are pushing further toward achieving a RAN that makes greater use of AI – to support new services and to improve network operations, including by coordinating with AI in other parts of the network.
Some vendors have begun proposing the use of multi-agent AI platforms to improve network performance. For example, training separate AI agents to analyze performance degradation in different areas of the network – RAN, core, and transport – may allow those agents to develop specialized areas of expertise to maximize their accuracy. These specialized agents could each work directly with a coordinating agent tasked with overseeing and orchestrating their activities and findings.
ZTE is one of the equipment vendors proposing such a model. And it is exploring other ways to improve RAN operations and support new services using AI. This year, ZTE began marketing its AIR Engine solution to make better use of AI in the RAN. The solution includes a general-purpose server card inserted into an otherwise traditional baseband unit – the processing unit of a mobile base station. (ZTE had previously introduced a similar offering aimed more at private networks; AIR Engine primarily targets public mobile-broadband networks.) AIR Engine is designed to use AI to enhance RAN performance by, for example, improving power efficiency and spectral efficiency as well as beamforming – closely tracking users’ movements, identifying the applications they’re using and applying the best network resources for those specific applications. The solution doesn’t currently use graphics processing units (GPUs), which have been widely deployed for AI tasks but have thus far been deemed by many telecom-industry members to be too expensive for distributed deployments in mobile base stations.
ZTE has also discovered a real-world use case applying AI RAN to small cells. The vendor has deployed its QCell distributed indoor small-cell solution at a car dealership that regularly hosts auto-industry influencers who want to stream videos from inside its showrooms. In addition to providing 5G connectivity, this version of QCell uses AI – running on a general-purpose compute plug-in card – to support live streaming in three ways: It optimizes the network for streaming (including supporting uplink speeds), it minimizes the impact of the streaming on other network users and it uses self-learning to reduce power consumption.
Mobile operators taking such a solution to market are likely to face some familiar challenges, including (a) understanding specific enterprise verticals well enough to know how AI-enhanced 5G could add value and (b) confronting the clash between traditional telco business models – which benefit from highly scalable offerings like consumer mobile broadband – and enterprise solutions like the one described above, which may require high customization without offering high scalability.
Mobile operators should also explore whether enterprise AI RAN solutions work better as virtual RAN solutions. ZTE’s use of a plug-in card for AI compute could impose some limits on capacity. Could a solution that uses general-purpose compute across AI and RAN workloads alike be more efficient? ZTE, which does not embrace vRAN in its RAN strategy generally, argues that using vRAN in the case of the car dealership could drive up the cost of the solution for a use case that is quite cost-sensitive.
Whatever challenges these new models present, vendors are increasingly taking them on and engaging the learning process to move further toward visions of a more AI-centric RAN, which is expected to be a significant defining characteristic of the next generation of mobile networks in a few years, when the 6G era arrives.