Proportional Fair Resource Allocation in Energy Harvesting-Based Wireless Networks

In this paper, we try to solve the imbalance problem of communication data service and energy supply among receivers in energy harvesting based wireless networks, with receivers equipped with modules that could either decode information or harvest energy from radio frequency signals. We formulate a biconvex optimization problem and find the solutions for subchannel and power allocation. Based on the obtained solutions, we propose a proportional fair resource allocation algorithm using an iterative method, and also show the convergence of the proposed algorithm to the partial optimum solution. Simulation results show that the proposed algorithm improves, to a remarkable extent, fairness among the receivers in terms of both the data rate and the harvested energy. At the same time, the proposed algorithm is found to lead to a negligible loss of system throughput compared with other conventional algorithms.