Subcarrier-Pairing-Based Resource Optimization for OFDM Wireless Powered Relay Transmissions With Time Switching Scheme

• Published in: IEEE transactions on signal processing 2017-03, Vol.65 (5), p.1130-1145
• Main Authors: Shen, Yanyan, Huang, Xiaoxia, Kwak, Kyung Sup, Yang, Bo, Wang, Shuqiang
• Format: Article
• Language: English
• Subjects: decode-and-forward relay; Energy consumption; Energy harvesting; non-convex optimization; OFDM; Optimization; Relay networks (telecommunications); Resource management; time switching; Wireless information and power transfer
• ISSN: 1053-587X; 1941-0476
• DOI: 10.1109/TSP.2016.2628351

In this paper, we investigate the joint resource optimization for orthogonal frequency division multiplexing relay transmissions, where the relay uses time switching (TS) scheme for wireless information and power transfer. We aim to maximize the total rate under several constraints by adjusting the subcarrier pairing (SP), the source transmission power, the relay transmission power, and the TS factor. Different from most of the previous works that ignore the energy consumption for signal receiving and processing at relay, we take into account a realistic energy consumption model. We formulate the joint resource allocation problem as a mixed integer nonlinear programming problem, which is generally difficult to solve. First, we give the feasible condition of the considered problem. Based on this condition, we prove the ordered SP is the optimal SP, and thus SP and the rest of the resource allocation problem (RRAP) can be separately solved without loss of optimality. Then, a searching algorithm is proposed to find the global optimal solution to the RRAP. To improve the efficiency, a method is proposed to reduce the searching region to a smaller one, which is proven to contain the optimal solution. Next, to further reduce the computational complexity, we subtly transform the RRAP to an equivalent problem, where the objective function is a D.C. function (difference of concave functions). By exploiting the partial convex structure, we propose an efficient and fast algorithm. Finally, simulations verify the superior performance of the proposed algorithms comparing with related ones in terms of total rate.