On Channel Estimation for Spatial Modulated Systems Over Time-Varying Channels
Loading...
Date
2015
Authors
Acar, Yusuf
Doğan, Hakan
Panayırcı, Erdal
Journal Title
Journal ISSN
Volume Title
Publisher
Academic Press Inc Elsevier Science
Open Access Color
Green Open Access
Yes
OpenAIRE Downloads
OpenAIRE Views
Publicly Funded
No
Abstract
Spatial Modulation (SM) has been proposed recently for multiple-input multiple-output (MIMO) systems to cope with the interchannel interference and to reduce the detection complexity as compared to the conventional MIMO systems. In SM system the data symbols are transmitted by a randomly selected active antenna of a MIMO transmitter to the receiver through a wireless channel. The information is carried both by the data symbol from any signal constellation such as M-ary phase shift keying (M-PSK) or M-ary quadrature amplitude modulation (M-QAM) by the index of the selected antenna. The channel estimation is a critical process at the receiver during the coherent detection of the transmitted symbol and the antenna index randomly selected. Recently the channel estimation of channel for SM systems has been investigated by the recursive least square (RLS) algorithm for only quasi-static fading channels. In this paper a novel channel estimation is proposed for SM systems in the presence of rapidly time-varying channels. The Bayesian mean square error (MSE) bound has been derived as a benchmark and the performance of the proposed approaches is studied in terms of MSE and bit-error rate (BER). Computer simulation results have confirmed that the proposed iterative channel estimation technique has significant BER/MSE performance advantages compared with existing channel estimation algorithm proposed earlier in the literature. (C) 2014 Elsevier Inc. All rights reserved.
Description
Keywords
Spatial modulation, Iterative channel estimation, Recursive least square, Curve fitting, Time-varying channel, Capacity, Matrix, Performance, Spatial modulation, Assisted modulation, Time-varying channel, 003, Iterative channel estimation, Equalization, Curve fitting, Recursive least square, Rayleigh-fading channels, Model
Fields of Science
05 social sciences, 02 engineering and technology, 0508 media and communications, 0202 electrical engineering, electronic engineering, information engineering
Citation
WoS Q
Q2
Scopus Q
Q2

OpenCitations Citation Count
11
Source
Digital Signal Processing
Volume
37
Issue
Start Page
43
End Page
52
PlumX Metrics
Citations
CrossRef : 4
Scopus : 12
Captures
Mendeley Readers : 17
Google Scholar™


