Distributed Massive MIMO Channel Estimation and Channel Database Assistance

TL;DR

This paper introduces a novel source domain channel estimation method for distributed Massive MIMO systems that leverages a physical environment-based channel database to improve estimation accuracy in near-field scenarios.

Contribution

It proposes a new source domain channel estimation approach and the integration of a channel database to enhance near-field distributed MIMO channel estimation.

Findings

Source domain estimation improves accuracy in near-field MIMO.

Channel database effectively incorporates environmental information.

Methods for generating and using the database are demonstrated.

Abstract

Due to the low per-antenna SNR and high signaling overhead, channel estimation is a major bottleneck in Massive MIMO systems. Spatial constraints can improve estimation performance by exploiting sparsity. Solutions exist for far field - beam domain channel estimation based on angle of arrival estimation. However, there is no equivalent solution for near field and distributed MIMO spatial channel estimation. We present a solution- source domain channel estimation- that is based on source location estimation. We extend this to employ a "Channel Database" incorporating information about the physical scattering environment into channel estimation. We present methods for generation, storage and usage of the Channel Database to assist localization and communication.