Pervasive AI has the potential to drastically shape the new 6G network.
6G and Artificial Intelligence & Machine Learning
As the fifth generation (5G) technology deployment rate increases and standards continue toward steady state, researchers have turned their attention toward 6G. New use cases and the potential of performance shortfalls have started the research buzz. Early efforts center on key fundamental research that will support target goals such as 1 Tbps peak data rate, 1 ms End-to-End latency, and up to 20yr battery life for this next generation of communication networks.
To support this research, international conferences have sprung up; for instance, 6G wireless summits and 6G symposiums where several key research topics have started to rise to the top. Topics include THz communications, quantum communications, big data analytics, cell-free networks, and pervasive artificial intelligence (AI).
In this paper we focus on pervasive AI, which has the potential to drastically shape the new 6G network. To achieve the faster rates and lower latency performance gains, an efficient network will be required. The network must dynamically allocate resources, change traffic flow, and process signals in an interference-rich environment.
Pervasive AI is a leading candidate to accomplish these tasks. AI and machine learning (ML) will play an important role as an enabler of 6G technology by optimizing the networks and designing new waveforms. Discussions and research have already focused on applying AI to various parts of the proposed network, which can be best summarized by mapping AI applications to the standard Open Systems Interconnection network layers model. All layers including physical, data link, network, and applications appear to be early research targets.
Novel approaches to dynamic security and network slice management are also being considered. All of these thrusts are leading toward an intelligent ecosystem. Also, 6G technology itself will enable further advances in AI/ML, such as exploiting the data that is local to the 6G sensor by efficiently transporting the (AI/ML) algorithms. Despite being in the early phase of development,6G shows potential evolutionary changes poised to enrich users’ experiences and enable new use cases.