On the Spectral Efficiency of Full-Duplex Small Cell Wireless Systems

TL;DR

This paper explores the spectral efficiency of full-duplex small cell wireless systems, proposing algorithms to optimize beamforming and demonstrate significant performance gains over half-duplex systems.

Contribution

It introduces two convergent algorithms for joint beamformer design in full-duplex small cell systems, addressing nonconvex optimization challenges.

Findings

Full-duplex systems outperform half-duplex in spectral efficiency.

Proposed algorithms effectively solve complex beamforming optimization.

Numerical results confirm substantial performance gains.

Abstract

We investigate the spectral efficiency of full-duplex small cell wireless systems, in which a full-duplex capable base station (BS) is designed to send/receive data to/from multiple halfduplex users on the same system resources. The major hurdle for designing such systems is due to the self-interference at the BS and co-channel interference among users. Hence, we consider a joint beamformer design to maximize the spectral efficiency subject to certain power constraints. The design problem is first formulated as a rank-constrained optimization one, and the rank relaxation method is then applied. However the relaxed problem is still nonconvex, and thus optimal solutions are hard to find. Herein, we propose two provably convergent algorithms to obtain suboptimal solutions. Based on the concept of the difference of convex functions programming, we approximate the design problem by a determinant maximization program in each iteration of the first algorithm. The second method is built upon the sequential parametric convex approximation method, which allows us to transform the relaxed problem into a semidefinite program in each iteration. Extensive numerical experiments under small cell setups illustrate that the full-duplex system with the proposed algorithms can achieve a large gain over the half-duplex one.