Decentralized WSEE Optimization for Massive MIMO Two-Way Half-Duplex AF Relaying

Abstract

Design of energy-efficient wireless systems has recently attracted attention to reduce their carbon footprint. This paper optimizes non-convex weighted sum energy efficiency (WSEE) of a multi-pair two-way amplify-and-forward half-duplex massive multiple-input multiple output relay system. We optimize it by developing a two-layer decentralized successive convex approximation optimization framework. The first layer approximates the non-convex WSEE either as a generic convex program (GCP) or as a second order cone program (SOCP). The second layer decentrally solves the approximated problem using alternating direction method of multipliers. We show that the proposed iterative algorithm yields a Karush-Kuhn-Tucker point of the original WSEE problem. We numerically analyze the effect of weights on the energy efficiency (EE) of individual users, and show that the proposed framework enable us to meet the heterogeneous EE requirements. We also analytically and numerically show that the decentralized algorithm has lesser complexity than its centralized counterpart, but yields the same WSEE.