Robust Resource Allocation for RSMA-Based V2X Networks Under Imperfect CSI

Rate-splitting multiple access (RSMA) is a promising technology for enhancing spectral efficiency and managing interference, making it suitable for spectrum-limited vehicle-to-everything (V2X) networks. To this end, we study a robust resource allocation (RA) problem for a RSMA-based V2X network under imperfect channel state information. An energy-efficient maximization RA problem is formulated by jointly optimizing the transmit power, the common stream, and the subchannel selection. To address the mixed-integer nonlinear programming problem with uncertainty sets, we first transform it into a deterministic form by using the worst-case approach. Then, the above problem is transformed into a convex one through the logarithmic approximation, variable relaxation, and variable substitutions. Finally, an iteration-based robust RA algorithm is proposed. Simulation results show that the proposed algorithm can effectively improve energy efficiency by 2.6% compared to the RA algorithm with non-orthogonal multiple access and robustness by 11.5% compared to the non-robust RA algorithm.