Multi-Objective Energy Efficient Resource Allocation and User Association for In-band Full Duplex Small-Cells

TL;DR

This paper proposes a novel energy-efficient resource allocation framework for in-band full-duplex small-cell networks, optimizing user association, subchannel assignment, and power control to enhance network energy efficiency while maintaining quality of service.

Contribution

It introduces a multi-objective optimization approach with an $ ext{epsilon}$-constraint method and transforms a complex MINLP problem into a solvable form, addressing the NP-hardness of the problem.

Findings

Achieves up to 69% EE improvement over half-duplex systems.

Effectively balances throughput and energy consumption.

Demonstrates the benefits of IBFD in practical residual self-interference scenarios.

Abstract

In this paper, we develop a framework to maximize the network energy efficiency (EE) by optimizing joint user-base station~(BS) association,~subchannel assignment, and power control considering an in-band full-duplex (IBFD)-enabled small-cell network. We maximize EE (ratio of network aggregate throughput and power consumption) while guaranteeing a minimum data rate requirement in both the uplink and downlink. The considered problem belongs to the category of mixed-integer non-linear programming problem (MINLP), {\color{black} and thus is NP-hard}. To cope up with this complexity and to derive a trade-off between system throughput and energy utilization, we first restate the considered problem as a multi-objective optimization problem (MOOP) aiming at maximizing system's throughput and minimizing system's energy consumption, simultaneously. This MOOP is then tackled by using $\epsilon$-constraint method. To do so, we first transform the binary subchannel and BS assignment variables into continuous ones without altering the feasible region of the problem and then approximate the non-convex rate functions through majorization-minimization (MM) approach. Simulation results are presented to demonstrate the effectiveness of our proposed algorithm in improving network's EE compared to the existing literature.~Furthermore, simulation results unveil that by employing the IBFD capability in OFDMA networks, our proposed resource allocation algorithm achieves a $69\%$ improvement in the EE as compared to the half-duplex system for practical values of residual self-interference.