Solving Indefinite Communication Reliability Optimization for RIS-Aided Mobile Systems by an Improved Differential Evolution

This paper exploits the applications of evolutionary algorithms
to solve a challenging category of optimization problems in 6G
mobile networks, particularly focusing on communication reliability
with modulated signals of reconfigurable intelligent surface
(RIS)-assisted multiple input multiple output (MIMO) systems. By
deriving the analytical downlink symbol error rate (SER) of each
user as a multivariate function of both the phase-shift and beamforming
vectors, we introduce a novel average SER minimization
problem subject to the transmitted power budget and phase shift
coefficients, which is NP-hard. By incorporating the differential
evolution (DE) algorithm as a pivotal tool and an efficient local
search to overcome the local optimum for optimizing the intricate
active and passive beamforming variables, the non-convexity of
the considered SER optimization problem can be effectively handled.
Numerical results indicate that the proposed joint active and
passive beamforming design is superior to the other benchmarks.