Capacity-Achieving Iterative LMMSE Detection for MIMO-NOMA Systems

TL;DR

This paper introduces an iterative LMMSE detection method for MIMO-NOMA systems that achieves optimal capacity and capacity region coverage, significantly reducing computational complexity while maintaining high performance.

Contribution

It presents matching conditions and area theorems for iterative detection, demonstrating that proper design achieves the sum capacity and entire capacity region of MIMO systems.

Findings

Achieves the optimal sum capacity of MU-MIMO systems

Can realize all maximal extreme points in the capacity region

Enables the entire capacity region of two-user MIMO systems

Abstract

This paper considers a iterative Linear Minimum Mean Square Error (LMMSE) detection for the uplink Multiuser Multiple-Input and Multiple-Output (MU-MIMO) systems with Non-Orthogonal Multiple Access (NOMA). The iterative LMMSE detection greatly reduces the system computational complexity by departing the overall processing into many low-complexity distributed calculations. However, it is generally considered to be sub-optimal and achieves relatively poor performance. In this paper, we firstly present the matching conditions and area theorems for the iterative detection of the MIMO-NOMA systems. Based on the proposed matching conditions and area theorems, the achievable rate region of the iterative LMMSE detection is analysed. We prove that by properly design the iterative LMMSE detection, it can achieve (i) the optimal sum capacity of MU-MIMO systems, (ii) all the maximal extreme points in the capacity region of MU-MIMO system, and (iii) the whole capacity region of two-user MIMO systems.