Optimal Energy-Bandwidth Allocation for Energy-Harvesting Networks in Multiuser Fading Channels.

In this paper, we develop optimal energy-bandwidth allocation algorithms in fading channels for multiple energy harvesting transmitters. We first assume that the side information of both the channel states and the energy harvesting states is known for $K$ time slots a priori, and the battery capacity and the maximum transmission power in each time slot are bounded. The network consists of N$ transmitter-receiver pairs and the objective is to maximize the sum-rate of all communication links over the K$ time slots by assigning the transmission power and bandwidth for each transmitter in each slot. The problem is formulated as a convex optimization problem with constraints, where N$ is the number of the receivers, making it hard to solve with a generic convex solver. An iterative algorithm is proposed based on efficiently solving two subproblems in each iteration, that has an overall complexity of {\cal O}(NK^2). The convergence and the optimality of this algorithm are also shown. Moreover, a heuristic algorithm is also proposed for energy-bandwidth allocation based on causal information of channel and energy harvesting states. Simulation results show that the proposed causal and noncausal algorithms can make efficient use of the harvested energy and the available bandwidth. And they achieve significantly higher rates than some heuristic policies for energy and bandwidth allocation. [ABSTRACT FROM AUTHOR]