Soft Actor-Critic Reset for RIS-assisted MU-MISO Symbiotic Radio Systems Learning Curves

We investigate a reconfigurable intelligent surface (RIS)-assisted multiuser multiple input single output (MU-MISO) symbiotic radio system in which the RIS undergoes hardware impairments. We aimed at solving the optimization problem to maximize the primary transmission rate while guaranteeing the rate of the secondary transmission in the RIS-assisted MU-MISO system. To this end, we formulate an optimization model that considers the transmit power and RIS phase shift constraints as well as the rate constraint of the secondary transmission.To address this issue, we transform the original optimization problem into a Markov decision process with a mixed-signal reward function. To achieve a higher reward, we propose a novel algorithm based on soft actor-critic (SAC) reset. Simulation results show that the SAC-reset can achieve a higher average reward compare with the conventional SAC schemes.