In energy-limited networks, battery-powered nodes suffer from energy famine, which can reduce network lifetime and affect the robustness of networks. To alleviate an energy problem, it is possible to harvest energy from ambient radio frequency signals. In this paper, we consider a proportional fair energy efficiency, which jointly considers energy efficiency and fairness in energy-harvesting-based wireless networks. We formulate a nonconvex optimization problem for solving subchannel and power allocation in order to maximize proportional fair energy efficiency. Using nonlinear fractional programming, we transform the optimization problem into a tractable convex problem. We also derive the solution of the transformed problem and propose a resource allocation algorithm using an iterative method. In addition, we prove the convergence of the proposed algorithm in view of a suboptimal point. Through intensive simulations, we compare the performance of our proposed algorithm with those of conventional algorithms. It is shown that the proposed algorithm improves fairness considerably while maintaining energy efficiency, compared with conventional algorithms.

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energyharvestingbased wireless networks iterative method solving subchannel and power allocation robustness suboptimal point ambient radio frequency nonlinear fractional programming fairness lifetime resource allocation algorithm algorithms batterypowered nonconvex optimization problem proportional fair energy efficiency

Byung Chang ChungKisong LeeDong-Ho Cho,.Proportional Fair Energy-Efficient Resource Allocation in Energy-Harvesting-Based Wireless Networks. 12 (3),2106-2116.

Byung Chang ChungKisong LeeDong-Ho Cho,"Proportional Fair Energy-Efficient Resource Allocation in Energy-Harvesting-Based Wireless Networks" 12

Byung Chang ChungKisong LeeDong-Ho Cho,"Proportional Fair Energy-Efficient Resource Allocation in Energy-Harvesting-Based Wireless Networks"