Signal Characterization and Receiver Design

In this work, we present a novel precoder design for multiuser massive multiple input multiple output (MU-mMIMO) systems impaired by nonlinear effects at the transmitter. By exploiting the rate splitting multiple access (RSMA) technique for user messages, we develop an analytical precoding framework based on the multilinear generalized singular value (ML-GSVD) decompositions for two or more matrices. This framework provides a robust statistical characterization of transmitted signals and enables accurate performance evaluation of precoding techniques in the presence of nonlinearities. Moreover, we introduce an iterative GSVD distortion cancellation (GSVD-DC) receiver for scenarios with strong nonlinear effects. Numerical results demonstrate that the proposed approach achieves substantial improvements in bit error rate (BER) compared to conventional precoders, for both linear and nonlinear cases, with moderate complexity increase, and without relying on successive interference cancellation (SIC). This makes the GSVD-DC receiver a promising solution for efficient and robust communications in nonlinear environments.