Paper Info
Title
Channel estimation in millimeter wave MIMO systems with one-bit quantization
Abstract
We develop channel estimation agorithms for millimeter wave (mmWave) multiple input multiple output (MIMO) systems with one-bit analog-to-digital converters (ADCs). Since the mmWave MIMO channel is sparse due to the propagation characteristics, the estimation problem is formulated as a one-bit compressed sensing problem. We propose a modified EM algorithm that exploits sparsity and has better performance than the conventional EM algorithm. We also present a second solution using the generalized approximate message passing (GAMP) algorithm to solve this optimization problem. The simulation results show that GAMP can reduce mean squared error in the important low and medium SNR regions.
Year
DOI
Venue
2014
10.1109/ACSSC.2014.7094595
ACSSC
Keywords
Field
DocType
expectation-maximisation algorithm,analogue-digital conversion,millimeter wave mimo system,compressed sensing problem,one bit quantization,optimization problem,generalized approximate message passing algorithm,compressed sensing,mimo communication,modified em algorithm,multiple input multiple output system,analog-digital converter,channel estimation,gamp algorithm
Mathematical optimization,Computer science,Expectation–maximization algorithm,MIMO,Communication channel,Mean squared error,Electronic engineering,Quantization (signal processing),Optimization problem,Message passing,Compressed sensing
Conference
ISSN
Citations 
PageRank 
1058-6393
83
2.50
References 
Authors
13
4
Name
Order
Citations
PageRank
Jianhua Mo11945.70
Philip Schniter2162093.74
Nuria González Prelcic3111455.80
Robert W. Heath414415885.64