AccelerComm has announced a joint development project with an unnamed tier-one mobile network operator to reduce energy consumption in 5G radio access networks (RAN) through artificial intelligence-based monitoring and control of base station processing resources.
The collaboration will focus on developing an AI-enabled telemetry and control interface connecting the physical-layer processing infrastructure of 5G base stations with higher-level network management systems. The proposed architecture will allow AI applications to monitor computational workloads and dynamically adjust hardware resource allocation according to changing network conditions.
The technology is intended to improve processing efficiency, power consumption and hardware utilisation by balancing workloads and reducing peak resource requirements. By adapting computing resources to actual traffic demand, the companies aim to maintain network performance while reducing the amount of processing hardware and energy required to operate 5G infrastructure.
AccelerComm's approach builds on Open RAN principles, using interfaces designed to support interoperability between base station processing systems and AI-driven network management platforms. The company also intends to develop technical outputs suitable for submission to industry standardisation bodies, potentially supporting broader adoption across different RAN equipment suppliers and network architectures.
The project extends AccelerComm's existing work in 5G physical-layer processing and non-terrestrial network (NTN) technologies into AI-controlled infrastructure optimisation. Although the initial focus is terrestrial 5G base stations, the underlying techniques could also have applications in satellite communications systems, where processing efficiency and power consumption are particularly important.