Energy-Efficient Joint Resource Allocation With Reconfigurable Intelligent Surfaces in Symbiotic Radio Networks

Abstract

Reconfigurable intelligent surface (RIS) assisted symbiotic radio communication (SRC) emerges as a novel technology that alleviates spectrum and energy demand of Internet-of-Things (IoT) applications. RIS concurrently backscatters IoT messages and strengthens radio links of primary user (PU) with intelligent passive beamforming. However, in the scenario of multiple RISs co-located, backscatter links may interfere with each other. Moreover, RIS consumes extra power for phase shifting compared to conventional backscatter device (BD), which may degrade energy efficiency (EE). To handle these issues, this paper proposes to maximize EE by jointly optimizing power allocation for PUs and passive beamforming for RISs. Alternating optimization (AO) algorithm is used to decompose the non-convex original problem into two subproblems which are respectively solved with semi-definite relaxation (SDR) and Dinkelbach’s algorithm. To comprehensively study the pros and cons of RIS passive beamforming, joint optimization problem of power allocation and backscatter coefficients design is modeled under the conventional SRC scenario with BDs. Besides AO and SDR, successive convex approximation is used to handle the non-convexity caused by inter BDs interference. Simulation results show that RIS effectively reduces outages and improves EE compared to BD under certain conditions.