Optimal Relay Selection and Power Control for Energy-Harvesting Wireless Relay Networks

Ambient energy harvesting (EH) has emerged as a promising technique to improve the energy efficiency and reduce the total greenhouse gas emissions for green relay networks. In this paper, we study the joint relay selection and power control problem for the decode-and-forward EH wireless relay network. In particular, the problem formulation is to maximize the end-to-end system throughput by a deadline under the limitations of data and energy storage. To solve the problem under an offline optimization framework, we decompose such an optimization problem into two subproblems: 1) the joint time scheduling and power control subproblem and 2) the relay selection subproblem. Due to the convex nature of the joint time scheduling and power control subproblem, we derive the optimal solution via the primal decomposition. Based on the obtained system throughput, we can quickly select the best relay that achieves the maximum throughput. For the practical implementation, we further design the sub-optimal online joint time scheduling and power control algorithm. Specifically, the best relay is first obtained based on the statistical knowledge of energy arrivals and channel states, and then the best relay decides the time scheduling and power control that maximizes the total throughput according to the instantaneous state of channel fading, energy arrival, and queue data in each time slot. Simulation results show that the proposed offline algorithm can guarantee the maximum system throughput. Moreover, the simulation results show that compared to the optimal offline algorithm, the sub-optimal online algorithm suffers only a small degradation in performance.