Network Massive MIMO for Cell-Boundary Users: From a Precoding Normalization Perspective

TL;DR

This paper explores network massive MIMO systems supporting cell-boundary users, analyzing precoding normalization techniques and deriving bounds on achievable sum rates to optimize system performance.

Contribution

It introduces a novel network massive MIMO architecture with analytical insights into precoding normalization and optimal switching strategies for enhanced cell-boundary user support.

Findings

Vector normalization outperforms for ZF precoding.

Matrix normalization is superior for MF precoding.

Optimal switching points depend on active user count.

Abstract

In this paper, we propose network massive multiple- input multiple-output (MIMO) systems, where three radio units (RUs) connected via one digital unit (DU) support multiple user equipments (UEs) at a cell-boundary through the same radio resource, i.e., the same frequency/time band. For precoding designs, zero-forcing (ZF) and matched filter (MF) with vector or matrix normalization are considered. We also derive the formulae of the lower and upper bounds of the achievable sum rate for each precoding. Based on our analytical results, we observe that vector normalization is better for ZF while matrix normalization is better for MF. Given antenna configurations, we also derive the optimal switching point as a function of the number of active users in a network. Numerical simulations confirm our analytical