Energy Efficiency Fairness for Multi-Pair Wireless-Powered Relaying Systems

TL;DR

This paper investigates energy efficiency fairness in multi-pair wireless-powered relay networks, proposing optimization algorithms that account for realistic power consumption models and nonlinear energy harvesting to improve overall system performance.

Contribution

It introduces a comprehensive energy consumption model and develops monotonic descent algorithms for joint optimization of data rates, power, and harvesting time under practical constraints.

Findings

Joint optimization significantly improves energy efficiency.

Realistic power consumption modeling impacts system performance.

Proposed algorithms outperform baseline methods.

Abstract

We consider a multi-pair amplify-and-forward relay network where the energy-constrained relays adopting time-switching protocol harvest energy from the radio frequency signals transmitted by the users for assisting user data transmission. Both one-way and two-way relaying techniques are investigated. Aiming at energy efficiency (EE) fairness among the user pairs, we construct an energy consumption model incorporating rate-dependent signal processing power, the dependence on output power level of power amplifiers' efficiency, and nonlinear energy harvesting (EH) circuits. Then we formulate the max-min EE fairness problems in which the data rates, users' transmit power, relays' processing coefficient, and EH time are jointly optimized under the constraints on the quality of service and users' maximum transmit power. To achieve efficient suboptimal solutions to these nonconvex problems, we devise monotonic descent algorithms based on the inner approximation (IA) framework, which solve a second-order-cone program in each iteration. To further simplify the designs, we propose an approach combining IA and zero-forcing beamforming, which eliminates inter-pair interference and reduces the numbers of variables and required iterations. Finally, extensive numerical results are presented to validate the proposed approaches. More specifically, the results demonstrate that ignoring the realistic aspects of power consumption might degrade the performance remarkably, and jointly designing parameters involved could significantly enhance the energy efficiency.