Outage-Constrained Throughput Maximization for MISO Symbiotic Radio Systems

Symbiotic radio (SR) has recently been proposed to improve the spectrum efficiency and energy efficiency of the Internet of Things. Therefore, the resource allocation (RA) algorithm has always been a research hotspot in SR systems. However, most of the current RA algorithms have assumed only one backscatter device or perfect channel state information (CSI), which is unrealistic in practical SR systems. In this paper, we formulate a robust RA problem for a downlink SR system with imperfect CSI to maximize the system throughput and decrease transmission outages. Specifically, a throughput-maximization robust RA problem is formulated subject to the outage rate constraints of both the primary users and backscatter devices. To address the non-convex optimization problem, we design an iterative-based robust RA algorithm that exploits Bernstein-type inequality, successive convex approximation, S-procedure, and alternating optimization methods. Numerical results demonstrate that the proposed algorithm has a 16.41% throughput increment compared to the non-symbiotic algorithm. Moreover, the actual outage probability of the proposed algorithm is reduced by 65.15% compared to the non-robust algorithm.