Distributed ADMM-based approach for total harvested power maximization in non-linear SWIPT system

Abstract

In this paper, the distributed alternating direction method of multipliers (ADMM)-based approach is investigated for total harvested power maximization (THPM) in multiple-input single-output transceiver pairs with simultaneous wireless information and power transfer. The power-splitting architecture and practical non-linear energy harvesting are utilized at each receiver. The highly non-convex THPM problem is formulated under requirements for the data rate, the amount of harvested power, and with limited power at the transmitters. First, semidefinite relaxation (SDR) and sequential parametric convex approximation are exploited to convert the non-convex THPM to a series of convex subproblems. Then, slack variables replacing interference are introduced to allow decomposing into distributed subproblems via ADMM. The interesting point is that optimal precoding matrices of the local subproblems satisfy the rank-1 constraints of SDR. Finally, the numerical experiments present the convergence of the proposed algorithm, obtaining results similar to the centralized approach, as well as comparing it with some baseline schemes.