Throughput maximization algorithm for RIS-aided cognitive backscatter communication networks
Yongjun XU, Qinyu Tian, Qianbin Chen, Gongpu WANG, Gang YANG · Scientia Sinica Informationis · 2024
To improve the spectrum utilization and solve the problem of communication performance degradation due to obstacle blocking in backscatter communication, based on the practical non-linear energy harvesting (EH) model, a throughput maximization problem is investigated for reconfigurable intelligent surface (RIS)-aided cognitive backscatter communication networks. Considering the maximum interference power constraint, the minimum EH constraint, and the phase shift of RIS constraint, a multivariate coupled resource allocation model is formulated by jointly optimizing transmission time, transmit power, reflection coefficient, and phase shift of RIS. Then, the original problem is transformed into a convex optimization problem using the variable substitution approach, quadratic transform method, and semi-definite relaxation method, and then an iteration-based resource allocation algorithm for throughput maximization is proposed. Simulation results verify that the average throughput of the proposed algorithm is increased by 15.0% compared with the traditional algorithm with the linear EH, and 22.7% compared with the traditional algorithm without RIS.