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PARALLEL STACK DECODING FOR MIMO SCHEMES

IP.com Disclosure Number: IPCOM000185674D
Publication Date: 2009-Jul-30
Document File: 6 page(s) / 199K

Publishing Venue

The IP.com Prior Art Database

Related People

Samuel Guillouard: AUTHOR

Abstract

Classical ML decoders of multiple input multiple output (MIMO) systems like the sphere decoder, the Schnorr-Euchner algorithm, the Fano and the stack decoders suffer from high complexity for high number of antennas and large constellation sizes. In this paper, we investigate the use of parallel processing for stack decoding, to decode signals transmitted on linear MIMO channels to reduce time consumption of hardware architecture. It will be shown that the parallel stack decoder allows a 50% of run time compared to the classical stack decoder.

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PARALLEL STACK DECODING FOR MIMO SCHEMES

Abdellatif Salah , Samuel Guillouard , Ghaya Rekaya Ben Othman

†TELECOM ParisTech - 46, rue Barrault, 75013 Paris, France salah,rekaya@enst.fr

‡Thomson Corporate Research Cesson Sévigné France samuel.guillouard@thomson.net

  Abstract- Classical ML decoders of multiple input multiple output (MIMO) systems like the sphere decoder, the Schnorr- Euchner algorithm, the Fano and the stack decoders suffer from high complexity for high number of antennas and large constellation sizes. In this paper, we investigate the use of parallel processing for stack decoding, to decode signals transmitted on linear MIMO channels to reduce time consumption of hardware architecture. It will be shown that the parallel stack decoder allows a 50% of run time compared to the classical stack decoder.

 Index Terms - MIMO Antennas, Space Time Decoding, Sphere Decoding, Stack Decoding.
I. INTRODUCTION

 Space time paradigm on wireless communications has seen a great explosion by a huge amount of both research oriented and applications papers. Many authors have considered combi- nations of space time codes with existing technologies such as Orthogonal Frequency Division Multiplexing (OFDM), LDPC codes and turbo codes, extension to frequency selective chan- nels, multiple access channels and time varying channels, or performance studies under more realistic channel conditions. These are important avenues of research, especially since the WiMAX (IEEE 802.16) standard specifies an optional STBC Alamouti, and Golden Code transmission mode. Keep- ing the same usual standard linear system model, it's clear that the MIMO channel creates the opportunity for diversity and multiplexing gains but also increases the complexity to recover the transmitted symbols. Research community was been very active to establish detection strategies of QAM- modulated signals observed at the output of linear MIMO channels. Many popular leading algorithms were conceived such as the sub-optimal V-BLAST scheme, the ML sphere decoder (SD) and the ML Schnorr-Euchner (SE). Exhaustive Maximum Likelihood decoding is an optimal detection of signals transmitted over MIMO Channels, but a huge com- plexity is associated with this type of decoding since it's well known to be an NP-hard problem. SD and SE provide ML detection at a reduced computational complexity but it stays huge in practice and with expensive cost. The present paper is intended to improve another recently proposed decoder for MIMO schemes which is the stack decoder [6]. Here, we exploit a specific lattice representation to define stack decoding with parallel processing. Then, many instructions are carried out simultaneously which is not possible with SE and SD. This accelerates the decoder and permit to reach the ML point in less time.

          
II. SYSTEM MODEL
Consider a MIMO system that has M and N antenna elements at the transmitter and the receiver...