Energy Efficiency Maximization Via Joint Sub-Carrier Assignment and Power Control for OFDMA Full Duplex Networks

TL;DR

This paper proposes an energy-efficient resource allocation method for OFDMA full-duplex networks, optimizing power control and sub-carrier assignment to significantly improve energy efficiency while ensuring quality of service.

Contribution

It introduces a novel iterative algorithm combining fractional programming, Dinkelbach method, and majorization-minimization to solve the non-convex resource allocation problem in IBFD OFDMA networks.

Findings

Achieves up to 75% increase in energy efficiency compared to half-duplex systems.

Develops a convergent algorithm for joint sub-carrier assignment and power control.

Demonstrates the effectiveness of IBFD with efficient SI cancellation techniques.

Abstract

In this paper, we develop an energy efficient resource allocation scheme for orthogonal frequency division multiple access (OFDMA) networks with in-band full-duplex (IBFD) communication between the base station and user equipments (UEs) considering a realistic self-interference (SI) model. Our primary aim is to maximize the system energy efficiency (EE) through a joint power control and sub-carrier assignment in both the downlink (DL) and uplink (UL), where the quality of service requirements of the UEs in DL and UL are guaranteed. The formulated problem is non-convex due to the non-linear fractional objective function and the non-convex feasible set which is generally intractable. In order to handle this difficulty, we first use fractional programming to transform the fractional objective function to the subtractive form. Then, by employing Dinkelbach method, we propose an iterative algorithm in which an inner problem is solved in each iteration. Applying majorization-minimization approximation, we make the inner problem convex. Also, by introducing a penalty function to handle integer sub-carrier assignment variables, we propose an iterative algorithm for addressing the inner problem. We show that our proposed algorithm converges to the locally optimal solution which is also demonstrated by our simulation results. In addition, simulation results show that by applying the IBFD capability in OFDMA networks with efficient SI cancellation techniques, our proposed resource allocation algorithm attains a 75% increase in the EE as compared to the half-duplex system.