On Channel Estimation for Spatial Modulated Systems Over Time-Varying Channels

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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

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Publicly Funded

No
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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.

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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
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OpenCitations Citation Count
11

Source

Digital Signal Processing

Volume

37

Issue

Start Page

43

End Page

52
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CrossRef : 4

Scopus : 12

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Mendeley Readers : 17

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