Blind Passive Beamforming for MIMO System

TL;DR

This paper introduces a blind passive beamforming method for MIMO systems that does not require channel state information, using a statistical approach to learn environmental features from received signals, validated by 5G field tests.

Contribution

It presents a novel blind beamforming technique that operates without CSI, addressing practical phase shift constraints in IS-aided MIMO systems.

Findings

Outperforms existing methods in 5G field tests

Effective without channel state information

Handles discrete phase shift constraints

Abstract

Passive beamforming for the intelligent surface (IS)-aided multiple-input multiple-output (MIMO) communication is a difficult nonconvex problem. It becomes even more challenging under the practical discrete constraints on phase shifts. Unlike most of the existing approaches that rely on the channel state information (CSI), this work advocates a blind beamforming strategy without any CSI. Simply put, we propose a statistical method that learns the main feature of the wireless environment from the random samples of received signal power. Field tests in the 5G commercial network demonstrate the superiority of the proposed blind passive beamforming method.