Maximum-Likelihood Sequence Detection of Multiple Antenna Systems over Dispersive Channels via Sphere Decoding

Haris Vikalo,Babak Hassibi

doi:10.1155/s1110865702204011

Abstract

Multiple antenna systems are capable of providing high data rate transmissions over wireless channels. When the channels are dispersive, the signal at each receive antenna is a combination of both the current and past symbols sent from all transmit antennas corrupted by noise. The optimal receiver is a maximum-likelihood sequence detector and is often considered to be practically infeasible due to high computational complexity (exponential in number of antennas and channel memory). Therefore, in practice, one often settles for a less complex suboptimal receiver structure, typically with an equalizer meant to suppress both the intersymbol and interuser interference, followed by the decoder. We propose a sphere decoding for the sequence detection in multiple antenna communication systems over dispersive channels. The sphere decoding provides the maximum-likelihood estimate with computational complexity comparable to the standard space-time decision-feedback equalizing (DFE) algorithms. The performance and complexity of the sphere decoding are compared with the DFE algorithm by means of simulations.

Highlights

Multiple antenna wireless communication systems are capable of providing data transmission at potentially very high rates [1]
When transmitting over noisy dispersive channels, the received signal at each receive antenna is the combination of the transmitted signals perturbed by noise, intersymbol interference (ISI), and by interuser interference (IUI)
We have proposed sphere decoding for maximum-likelihood sequence detection of multiple antenna systems over frequency-selective channels

Summary

INTRODUCTION

Multiple antenna wireless communication systems are capable of providing data transmission at potentially very high rates [1]. When transmitting over noisy dispersive channels, the received signal at each receive antenna is the combination of the transmitted signals perturbed by noise, intersymbol interference (ISI), and by interuser interference (IUI). In this case, the optimal receiver structure is the multichannel maximum-likelihood sequence estimation (MLSE). We propose an algorithm that yields the optimal MLSE performance on dispersive multiple-input multiple-output (MIMO) channels with finite impulse response (FIR). We consider the so-called sphere decoding, an algorithm for solving integer least-squares problems, which, in the communication context, provides the ML estimate of the transmitted data sequence.

FIR MIMO MODEL DESCRIPTION

PROBLEM STATEMENT

Sphere decoding

SIMULATION RESULTS

DISCUSSION AND CONCLUSION