Optimal Multiuser Scheduling Schemes for Simultaneous Wireless Information and Power Transfer

TL;DR

This paper develops optimal multiuser scheduling algorithms for SWIPT systems that balance throughput and energy harvesting, using convex optimization to improve performance over existing methods.

Contribution

It introduces a novel optimization framework for scheduling in SWIPT systems that accounts for fairness and energy constraints, providing optimal solutions.

Findings

Significant throughput and energy harvesting improvements over existing algorithms.

The tradeoff between throughput and harvested energy is characterized.

Convex optimization techniques effectively solve the non-convex scheduling problems.

Abstract

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.