Sub-Array Selection in Full-Duplex Massive MIMO for Enhanced Self-Interference Suppression

• Published in: IEEE Global Communications Conference (Online) pp. 5835 - 5840
• Main Authors: Mahmood, Mobeen, Koc, Asil, Nguyen, Duc Tuong, Morawski, Robert, Le-Ngoc, Tho
• Format: Conference Proceeding
• Language: English
• Published: IEEE 04.12.2023
• Subjects: Array signal processing; Interference cancellation; Optimization; Particle measurements; Perturbation methods; Radio frequency; Synthetic aperture sonar
• ISSN: 2576-6813
• DOI: 10.1109/GLOBECOM54140.2023.10436977

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.