  In this paper, we study the downlink multiuser scheduling problem for systems
with simultaneous wireless information and power transfer (SWIPT). We design
optimal scheduling algorithms that maximize the long-term average system
throughput under different fairness requirements, such as proportional fairness
and equal throughput fairness. In particular, the algorithm designs are
formulated as non-convex optimization problems which take into account the
minimum required average sum harvested energy in the system. The problems are
solved by using convex optimization techniques and the proposed optimization
framework reveals the tradeoff between the long-term average system throughput
and the sum harvested energy in multiuser systems with fairness constraints.
Simulation results demonstrate that substantial performance gains can be
achieved by the proposed optimization framework compared to existing suboptimal
scheduling algorithms from the literature.
