Zero Taps Detection-Based Sparse Channel Estimation Method for OFDM Systems

Xue Jiao Zheng; Jian Jiao

doi:10.4028/www.scientific.net/AMM.513-517.2577

Paper Titles

Research and Design of Lead-Acid Battery Manufacturing Execution System Based on Barcode Scanning
p.2560

Algorithm Research Based on Distributed Water Multi-Level Resources Scheduling
p.2565

The Studies of Modeling Method for Three Dimension Iterated Function System
p.2569

Research and Application of Reordering of the Chinese NP “A+(de)+B+(de)+C”
p.2573

Zero Taps Detection-Based Sparse Channel Estimation Method for OFDM Systems
p.2577

Research on Modular Construction and Evaluation of the Green Building Technique System
p.2583

Study on Drilling and Completion Techniques of Horizontal well for Coalbed Methane
p.2586

Heavy Rail Spray Quenching Wind Heat Stress and Residual Stress Analysis
p.2590

Chemical Reaction Optimization for Earliness-Tardiness Scheduling Problem
p.2594

HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 513-517Zero Taps Detection-Based Sparse Channel...

Zero Taps Detection-Based Sparse Channel Estimation Method for OFDM Systems

Abstract:

The channel whose impulse response contains a large number of zero taps is sparse. Exploiting the sparsity of the channel, the estimation problem can be converted into an on-off keying (OOK) detection problem. Therefore, a sparse channel estimation algorithm was proposed. First, with an initial estimate, posed a detection problem by casting the determination of non-zero taps into an OOK communication problem; then took precise evaluation against the established non-zero taps position. In the simulation, the proposed algorithm was compared to the standard LSE via simulations in terms of MSE and BER. The results show that, the proposed algorithm can provide the best performance while maintaining moderate complexity.

You might also be interested in these eBooks

View Preview

Info:

Periodical:

Applied Mechanics and Materials (Volumes 513-517)

Pages:

2577-2580

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.513-517.2577

Citation:

Cite this paper

Online since:

February 2014

Authors:

Xue Jiao Zheng*, Jian Jiao

Keywords:

Channel Estimation, Sparsity, Sphere Decoding, Zero Taps

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

* - Corresponding Author

References

[1] ZHOU Y, WANG J, SAWAHASHI M. Downlink transmission of broadband OFCDM systems —Part I: Hybrid detection [J]. IEEE Transactions Communications, 2005, 53(4) , pp.718-729.

DOI: 10.1109/tcomm.2005.844962

Google Scholar

[2] Simeone O，Bar-Ness Y，Spagnolini U．Subspace based methods for channel estimation in OFDM systems[A]． European Conference on Wireless Technology [c]．Milan：ECWT，2002, pp.26-27.

Google Scholar

[3] Li Yue，etc. A Channel Estimation Method for Orthogonal Division Multiplexing system by Tracking Delay-Subspace [J]. Journal of Shanghai Jiao Tong University, 2005, （9）, pp.1494-1499.

Google Scholar

[4] Shen Feng， Wang Hui. DFT based LS Channel Estimation Algorithm for MIMO-OFDM Systems [J]. Communications technology, 2011, ( 9) , pp.13-14，17.

Google Scholar

[5] CZINK N, YIN X, OZCELIK H, et al. Cluster characteristics in a MIMO indoor propagation environment [J]. IEEE Trans Wireless Co mmun, 2007, 6(4) , 1465-1475.

DOI: 10.1109/twc.2007.348343

Google Scholar

[6] VUOKKO L, KOLMONEN V M, et al. Measurement of large-scale cluster power characteristics for geometric channel models [J]. IEEE Trans Antennas Propagat, 2007, 55(11) , 3361-3365.

DOI: 10.1109/tap.2007.908844

Google Scholar

[7] Zhu Hangtao etc. Study on sparse channel estimation algorithm based on matching pursuit for OFDM systems [J]. Journal of Chongqing University of Posts and Telecommunications, 2008 , 2 , pp.11-14.

Google Scholar

[8] VITERBOE, BOUltROS J. A universal lattice code decoder for fading chanels[J]．IEEE Tran- sactions on Information Theory. 1999, 45(5) , pp.1639-1642.

DOI: 10.1109/18.771234

Google Scholar