Sub-Array Selection in Full-Duplex Massive MIMO for Enhanced Self-Interference Suppression
Abstract
This study considers a novel full-duplex (FD) massive multiple-input multiple-output (mMIMO) system using hybrid beamforming (HBF) architecture, which allows for simultaneous uplink (UL) and downlink (DL) transmission over the same frequency band. Particularly, our objective is to mitigate the strong self-interference (SI) solely on the design of UL and DL RF beamforming stages jointly with sub-array selection (SAS) for transmit (Tx) and receive (Rx) sub-arrays at base station (BS). Based on the measured SI channel in an anechoic chamber, we propose a min-SI beamforming scheme with SAS, which applies perturbations to the beam directivity to enhance SI suppression in UL and DL beam directions. To solve this challenging nonconvex optimization problem, we propose a swarm intelligence-based algorithmic solution to find the optimal perturbations as well as the Tx and Rx sub-arrays to minimize SI subject to the directivity degradation constraints for the UL and DL beams. The results show that the proposed min-SI BF scheme can achieve SI suppression as high as 78 dB in FD mMIMO systems.
Cite
@article{arxiv.2309.03317,
title = {Sub-Array Selection in Full-Duplex Massive MIMO for Enhanced Self-Interference Suppression},
author = {Mobeen Mahmood and Asil Koc and Duc Tuong Nguyen and Robert Morawski and Tho Le-Ngoc},
journal= {arXiv preprint arXiv:2309.03317},
year = {2023}
}
Comments
This paper has been accepted for publication in IEEE Globecom 2023