Optimizing Spectral and Energy Efficiency of Quantized Multiuser MISO-RSMA Systems With Imperfect CSIT

Employing low-resolution quantizers increases energy efficiency (EE) while reducing spectral efficiency (SE) and deteriorating channel estimation accuracy, which induces higher inter-user interference. To overcome these drawbacks, we develop a rate-splitting multiple access (RSMA) precoding method in the low-resolution quantization system with imperfect channel state information at the transmitter (CSIT), which optimizes a balance between two critical yet often competing aspects: maximization of the SE to increase data rate and the EE to manage the power consumption. We first average the sum rate to properly define the SE and EE with the imperfect CSIT and error covariance matrices. Then we formulate a weighted SE and EE optimization problem and divide it into two sub-problems adopting a Dinkelbach approach: precoding direction and transmit power optimization. For precoding direction, we derive the first-order optimality condition. Casting the condition to a generalized eigenvalue problem, we propose an algorithm to identify the principal eigenvector which corresponds to the superior stationary point. Furthermore, we utilize a gradient method for transmit power optimization and update the precoding direction and transmit power alternately. Simulations validate the benefits of the proposed method in enhancing the SE and EE trade-off and reveal the superiority of RSMA over spatial-division multiple access.