Rate-Splitting for the Weighted Sum Rate Maximization under Minimum Rate Constraints in the MIMO BC

Abstract

It has been shown that rate-splitting multiple access (RSMA) promises high data rates with superior performance especially under imperfect channel state information (CSI) and the possibility to fulfill various quality of service constraints. In this work, we use the 1-layer rate-splitting (1ℓ-RS) approach for the weighted sum rate (WSR) maximization under minimum rate constraints in the multi-user multiple-input multiple-output broadcast channel (MIMO BC). We adapt the iterative weighted minimum mean squared error (IWMMSE) approach to the 1ℓ-RS weighted sum rate optimization problem in the MIMO BC. Furthermore, a more efficient 1ℓ-RS approach is proposed, where the common stream is optimized first and private streams are allocated successively in addition to the common stream with the goal to increase the WSR and to be able to fulfill high minimum rate constraints. Numerical simulations show that much larger minimum rate constraints can be satisfied with the proposed 1ℓ-RS approaches than with pure multicasting. Additionally, the two 1ℓ-RS approaches are compared regarding their computational complexity.