DocumentCode
2169633
Title
A Low Complexity Channel Estimation Algorithm for TDS-OFDM System
Author
Hu Feng ; Li Jianping
Author_Institution
Sch. of Inf. Eng., Commun. Univ. of China, Beijing, China
fYear
2009
fDate
17-19 Oct. 2009
Firstpage
1
Lastpage
5
Abstract
LMMSE algorithm is one of the best linear channel estimations for time domain synchronous orthogonal frequency division multiplexing (TDS-OFDM) system. The research on the computational complexity reduction of LMMSE algorithm remains to be a challenging topic. Since the combination of fast Fourier transform with singular value decomposition (FFT-SVD) simplify the channel autocorrelation matrix computation in frequency domain, an improved LMMSE algorithm based on FFT-SVD is proposed in this paper to achieve the similar MSE performance with lower computational complexity. The simulation results show that by using the improved LMMSE algorithm, the time spending in calculation can be reduced to 70% compared with the conventional one when adopting 256 PN sequence in TDS-OFDM system over Rayleigh fading channels.
Keywords
OFDM modulation; channel estimation; computational complexity; correlation methods; fast Fourier transforms; frequency-domain analysis; least mean squares methods; singular value decomposition; time-domain analysis; LMMSE algorithm; Rayleigh fading channel; TDS-OFDM system; channel autocorrelation matrix computation; computational complexity; fast Fourier transform; frequency domain; linear channel estimation algorithm; orthogonal frequency division multiplexing; singular value decomposition; time domain synchronous; Autocorrelation; Channel estimation; Computational complexity; Computational modeling; Fading; Fast Fourier transforms; Frequency domain analysis; Matrix decomposition; OFDM; Singular value decomposition;
fLanguage
English
Publisher
ieee
Conference_Titel
Image and Signal Processing, 2009. CISP '09. 2nd International Congress on
Conference_Location
Tianjin
Print_ISBN
978-1-4244-4129-7
Electronic_ISBN
978-1-4244-4131-0
Type
conf
DOI
10.1109/CISP.2009.5304623
Filename
5304623
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