Uplink Capacity of OFDM Multi-User MIMO Using Near-ML Detection in a Cellular System

Abstract

Multi-user multi-input multi-output (MIMO) system has been attracting much attention due to its high spectrum efficiency. Non-linear MIMO signal detection methods with less computational complexity have been widely studied for single-user MIMO systems. In this paper, we investigate how a lattice reduction (LR)-aided detection and a maximum likelihood detection (MLD) employing the QR decomposition and M-algorithm (QRM-MLD), which are commonly known as non-linear MIMO signal detection methods, improve the uplink capacity of a multi-user MIMO-OFDM cellular system, compared to simple linear detection methods such as zero-forcing detection (ZFD) and minimum mean square error detection (MMSED). We show that both LR-aided linear detection and QRM-MLD can achieve higher uplink capacity than simple linear detection at the cost of moderate increase of computational complexity. Furthermore, QRM-MLD can obtain the same uplink capacity as MLD.