Achieving low-complexity maximum-likelihood detection for the 3D MIMO code

Ming Liu,Maryline Hélard,Matthieu Crussière,Jean-François Hélard

doi:10.1186/1687-1499-2014-20

Abstract

Abstract The 3D Multiple-input multiple-output (MIMO) code is a robust and efficient space-time block code (STBC) for the distributed MIMO broadcasting but suffers from high maximum-likelihood (ML) decoding complexity. In this paper, we first analyze some properties of the 3D MIMO code to show that the 3D MIMO code is fast decodable. It is proven that the ML decoding performance can be achieved with a complexity of O(M 4.5) instead of O(M 8) in quasi-static channel with M-ary square QAM modulations. Consequently, we propose a simplified ML decoder exploiting the unique properties of the 3D MIMO code. Simulation results show that the proposed simplified ML decoder can achieve much lower processing time latency compared to the classical sphere decoder with Schnorr-Euchner enumeration.

Highlights

Multiple-input multiple-output (MIMO) is a promising technique that can bring significant improvements to the wireless communication systems
MIMO has been widely employed in the latest wireless communication standards such as IEEE 802.11n, 3GPP Long Term Evolution (LTE), WiMAX, and Digital Video Broadcasting- Generation Handheld (DVB-NGH)
A so-called space-time-space (3D) MIMO code [3] was proposed for future TV broadcasting systems, in which the services are delivered by the MIMO transmission in a single-frequency network (SFN)

Summary

Introduction

Multiple-input multiple-output (MIMO) is a promising technique that can bring significant improvements to the wireless communication systems. Polonen and Koivunen described a STBC with less decoding complexity based on orthogonal basis [16] Such a code does not achieve full diversity or full rate for 4×2 MIMO transmissions and performs worse than the 3D MIMO code. A ‘punctured version’ of the 3D MIMO code that possesses full rate with low decoding complexity has been proposed [17] It does not achieve full diversity and is less robust in harsh channel conditions. We propose a reduced-complexity ML decoder for the 3D MIMO code which exploits the embedded orthogonality in the codeword. Based on the unique properties of the new form of 3D MIMO codeword, we propose a novel implementation of the simplified decoder that achieves a lower average complexity in terms of time latency without losing the ML optimality.

Notations

System model

Proposed implementation of the simplified ML decoder

Simulation results

Findings

Conclusion