Joint Active Beamforming Design and Performance Analysis for Active RIS-Aided Cognitive Multigroup Multicast Systems

This paper considers design optimization for an active reconfigurable intelligent surface (active RIS)-aided cognitive multigroup multicast communication system. To minimize the sum of the weighted power of the cognitive radio base station (CRBS) and active RIS, the joint design problem of CRBS matrix and active RIS reflection coefficients is discussed, satisfying the constraints of the received signal-to-interference-plus-noise ratio (SINR), the maximum gain constraints of the active RIS, and the interference constraints on the primary users (PUs). Due to the complex coupling and non-convex nature of decision variables in the objective function and constraints, the decision variables were decoupled using the alternate optimization (AO) method, and then methods such as the successive convex approximation (SCA), Schur complement, and penalty convex–concave procedure (PCCP) were utilized to transform the non-convex constraints into tractable convex forms. Finally, an efficient algorithm based on AO for the cognitive multigroup multicast system was proposed, which can reduce total system power consumption by at least 9% compared to a passive RIS (P-RIS). Numerical results identify the system parameter conditions under which the designed system and the proposed algorithm outperform the benchmarks and portray how the system performance is affected by changes to the system parameters.