Energy-Efficient Symbiotic Radio Using Generalized Benders Decomposition

This paper investigates the symbiotic radio (SR) system supported by reconfigurable intelligent surfaces (RIS) to provide shared spectrum. SR Stakeholders share the same infrastructure and spectrum resources, but with different quality of service (QoS) requirements. The objective of this study is to develop a low complexity and global optimization algorithm to maximize the energy efficiency (EE) of the secondary receiver (SRx) and under a required signal-to-interference-plus-noise ratio (SINR) constraint for the primary receiver (PRx). Specifically, we formulate the joint optimization of phase shift, transmission power control, and reflection element scheduling of the RIS-assisted SR system as a nonconvex mixed-integer nonlinear program (MINLP) problem. Then, we relax the nonconvex MINLP problem into an equivalent convex MINLP problem. To this end, we propose an efficient and effective method based on the accelerated generalized Benders decomposition (GBD) algorithm to solve the global-optimal and fast convergence goals. Simulation results show that the proposed GBDbased approach efficiently improves the EE by 41.94% compared to the successive convex approximation (SCA).