Sum-Rate Maximization of Cooperative Rate-Splitting for Massive IoT

This letter proposes a downlink cooperative rate splitting (CRS) system for massive Internet of Things (IoT) to mitigate inter-user interference of high-frequency channels and improve sum-rate performance. Specifically, we mitigate inter-user interference by dynamically adjusting user grouping, which reshapes interference patterns and enhances cooperative link data rates. To achieve sum-rate maximization, we introduce a CRS framework that leverages cross-entropy optimization (CEO) for user grouping and weighted minimum mean square error (WMMSE)-based beamforming to effectively mitigate interference. Simulation results demonstrate that the proposed approach outperforms conventional user grouping and multiple access schemes in maximizing the sum-rate in massive IoT networks.