Rate-Splitting Multiple Access in Cell-Free Massive MIMO-URLLC Systems: Achievable Rate Analysis and Optimization

Rate-splitting multiple access (RSMA) has emerged as a potent paradigm shift in wireless communications, demonstrating resilience to channel state information (CSI) inaccuracies and significant rate enhancements. This work investigates RSMA's application within the context of ultra-reliable and low-latency communication (URLLC) for the forthcoming Internet-of-Everything networks. Specifically, we integrate RSMA with a cell-free massive multiple-input multiple-output (MIMO) architecture to support URLLC demands. Considering the imperfect CSI, attributable to pilot contamination and thermal noise, we derive rigorous lower-bound expressions for the downlink achievable rates. These expressions are applicable to short-packet communication scenarios and RSMA strategy over spatially correlated Rician fading channels. Utilizing these analytical expressions, we perform an exhaustive rate performance evaluation, varying system parameters such as the numbers of pilots, access points (APs), devices, and antennas per AP, alongside different multiple access techniques. Furthermore, we address the power control coefficient design for both common and private streams, framing it as an optimization problem aimed at maximizing the weighted sum-rate and enhancing URLLC service quality. To tackle this non-convex challenge, we introduce a geometric programming-based path-following algorithm, which iteratively converges to the solution. The theoretical underpinnings and the efficacy of the proposed power optimization algorithm are corroborated through extensive simulation results.