Machine learning (ML) is a promising enabler for the fifth-generation (5G) communication
systems and beyond. By imbuing intelligence into the network edge, edge nodes can
proactively carry out decision-making and, thereby, react to local environmental changes
and disturbances while experiencing zero communication latency. To achieve this goal, it is
essential to cater for high ML inference accuracy at scale under the time-varying channel
and network dynamics, by continuously exchanging fresh data and ML model updates in a …

Machine learning (ML) is a promising enabler for the fifth generation (5G) communication
systems and beyond. By imbuing intelligence into the network edge, edge nodes can
proactively carry out decision-making, and thereby react to local environmental changes and
disturbances while experiencing zero communication latency. To achieve this goal, it is
essential to cater for high ML inference accuracy at scale under time-varying channel and
network dynamics, by continuously exchanging fresh data and ML model updates in a …