DocumentCode :
643635
Title :
Threshold based most significant taps detection for sparse channel estimation in OFDM system
Author :
Hui Xie ; Andrieux, Guillaume ; Yide Wang ; Diouris, J.F. ; Suili Feng
Author_Institution :
Sch. of Electron. & Inf. Eng., South China Univ. of Technol., Guangzhou, China
fYear :
2013
fDate :
5-8 Aug. 2013
Firstpage :
1
Lastpage :
5
Abstract :
This paper addresses the effective sparse channel estimation based on the most significant taps (MST) selection with high spectral efficiency and moderate computational complexity for orthogonal frequency division multiplexing (OFDM) systems. The main goal of this paper is to obtain an efficient time domain threshold and achieve the channel estimation performance approaching the least squares (LS) method with exact sparsity (exact number of non-zero channel taps) without using prior knowledge of both channel statistics and noise standard deviation. Firstly, classical LS method is used to get an initial channel impulse response (CIR) estimate. Then a novel effective threshold, estimated from the noise coefficients of the initial estimated CIR, is proposed. Finally, the obtained threshold is used to select the most significant taps. Simulations show that the proposed method is able to achieve good channel estimation performances for sparse channel within a comparatively wide range of sparsity with small number of pilots and moderate computational complexity.
Keywords :
OFDM modulation; channel estimation; computational complexity; least squares approximations; statistical analysis; time-domain analysis; transient response; CIR estimation; MST selection; OFDM system; channel impulse response estimation; channel statistics; classical LS method; computational complexity; effective sparse channel estimation; least square method; noise standard deviation; orthogonal frequency division multiplexing systems; sparse channel estimation; spectral efficiency; threshold-based most significant tap detection; time domain threshold; Channel estimation; Estimation; OFDM; Signal to noise ratio; Standards; Vectors; Sparse channel estimation; least squares (LS); orthogonal frequency division multiplexing (OFDM); threshold;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Signal Processing, Communication and Computing (ICSPCC), 2013 IEEE International Conference on
Conference_Location :
KunMing
Type :
conf
DOI :
10.1109/ICSPCC.2013.6663907
Filename :
6663907
Link To Document :
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