Paper Info
Title
Iterative MIMO Detection and Channel Estimation Using Joint Superimposed and Pilot-Aided Training.
Abstract
This paper presents a novel iterative detection and channel estimation scheme that combines the effort of superimposed training (ST) and pilot-aided training (PAT) for multiple-input multiple-output (MIMO) flat fading channels. The proposed method, hereafter known as joint mean removal ST and PAT (MRST-PAT), implements an iterative detection and channel estimation that achieves the performance of data-dependent ST (DDST) algorithm, with the difference that the data arithmetic cyclic mean is estimated and removed from data at the receiver's end. It is demonstrated that this iterative and cooperative detection and channel estimator algorithm surpasses the effects of data detection identifiability condition that DDST has shown when higher orders of modulation are used. Theoretical performance of the MRST-PAT scheme is provided and corroborated by numerical simulations. In addition, the performance comparison between the proposed method and different MIMO channel estimation techniques is analyzed. The joint effort between ST and PAT shows that MRST-PAT is a solid candidate in communications systems for multiamplitude constellations in Rayleigh fading channels, while achieving high-throughput data rates with manageable complexity and bit-error rate (BER) as a figure of merit.
Year
DOI
Venue
2016
10.1155/2016/3723862
MOBILE INFORMATION SYSTEMS
Field
DocType
Volume
Telecommunications,Rayleigh fading,Fading,Computer science,Identifiability,Communications system,MIMO,Communication channel,Algorithm,Modulation,Estimator,Distributed computing
Journal
2016
ISSN
Citations 
PageRank 
1574-017X
0
0.34
References 
Authors
25
4
Name
Order
Citations
PageRank
Omar Humberto Longoria-Gandara1466.30
Ramón Parra-Michel243.81
Roberto Carrasco-Alvarez3285.80
Eduardo Romero-Aguirre401.35