Abstract
Optical communication systems (with visible light communication as an example) have emerged as a promising candidate for supporting high throughput requirements. Such high data rates can be achieved in a sustainable manner when energy harvesting devices are adopted for the optical transmitters. However, the existing research lacks a thorough investigation on the maximum achievable capacity for optical networks under dynamic energy conditions. This is especially true when photon counter detectors are implemented at the receiver side, and hence, optical Poisson channels are considered. To address this limitation, we develop in this paper optimal energy scheduling algorithms for optical Poisson channels with energy harvesting devices. The objective is to maximize the channel sum-rate, assuming that the side information of energy harvesting states for {K} time slots is known a priori , and the battery capacity and the maximum energy consumption in each time slot are bounded. The problem is formulated as a convex optimization program with {{\mathcal{ O}}(K)} constraints, making it hard to solve using a general convex solver since the computational complexity of a generic convex solver is exponential in the number of constraints. This paper proposes an efficient energy scheduling algorithm that has a reduced computational complexity of {{\mathcal {O}}(K^{2})} . The proposed algorithm is also proven to be optimal. The developed energy schedule is piece-wise constant, which changes when the battery overflows or depletes. Numerical results depict significant improvement of the optimal strategy over benchmark strategies.