Please wait a minute...
浙江大学学报(工学版)  2018, Vol. 52 Issue (9): 1747-1752    DOI: 10.3785/j.issn.1008-973X.2018.09.015
马恒达, 袁伟娜, 伏威
华东理工大学 信息科学与工程学院, 上海 200237
Group sparse channel estimation method based on pilot placement optimization
MA Heng-da, YUAN Wei-na, FU Wei
School of information Science and Engineering, East China University of Science and Technology, Shanghai 200237, China
 全文: PDF(839 KB)   HTML



Channel estimation using group sparsity methods were studied for sparsity of OFDM system. These methods considered both the time-selective fading and frequency-selective fading of the channel. The concept of group sparsity was introduced by the sparse representation of the channel coefficients. The non-zero components of sparse signals tended to cluster in a region. This characteristic could be used to improve the quality of the reconstruction. At the same time, the pilot pattern played an important role in channel estimation. Estimation of distribution algorithm (EDA) was used to optimize pilot pattern in sparse channel estimation. The algorithm is more robust than other methods and unlikely to trap into local minima. Both theoretical analysis and simulation results show that the scheme is more effective than the traditional estimation method. The simulation results indicate the applicability of the scheme by using different reconstruction methods and group sizes.

收稿日期: 2017-06-23 出版日期: 2018-09-20
CLC:  TN929  


通讯作者: 袁伟娜,女,副教授.     E-mail: 袁伟娜,女,副教授
作者简介: 马恒达(1993-),男,硕士生,从事移动通信相关技术研究
E-mail Alert


马恒达, 袁伟娜, 伏威. 基于导频放置优化的组稀疏信道估计方法[J]. 浙江大学学报(工学版), 2018, 52(9): 1747-1752.

MA Heng-da, YUAN Wei-na, FU Wei. Group sparse channel estimation method based on pilot placement optimization. JOURNAL OF ZHEJIANG UNIVERSITY (ENGINEERING SCIENCE), 2018, 52(9): 1747-1752.


[1] ENGELS M. Wireless OFDM systems:How to make them work?[M]. Norwell:Springer Science & Business Media, 2002:33-36.
[2] BERTHOLD U, JONDRAL F K, BRANDES S, et al. OFDM-based overlay systems:a promising approach for enhancing spectral efficiency[Topics in radio communications] [J]. IEEE Communications Magazine, 2007, 45(12):52-58.
[3] DONOHO D L. Compressed sensing[J]. IEEE Transactions on Information Theory, 2006, 52(4):1289-1306.
[4] BAJWA W U, HAUPT J, RAZ G, et al. Compressed channel sensing[C]//200842nd Annual Conference on Information Sciences and Systems. New Jersey:IEEE, 2008:5-10.
[5] BAJWA W U, HAUPT J, SAYEED A M, et al. Compressed channel sensing:a new approach to estimating sparse multipath channels[J]. Proceedings of the IEEE, 2010, 98(6):1058-1076.
[6] TAUBOCK G, HLAWATSCH F, EIWEN D, et al. Compressive estimation of doubly selective channels in multicarrier systems:leakage effects and sparsity-enhancing processing[J]. IEEE Journal of Selected Topics in Signal Processing, 2010, 4(2):255-271.
[7] EIWEN D, TAUBÖCK G, HLAWATSCH F, et al. Group sparsity methods for compressive channel estimation in doubly dispersive multicarrier systems[C]//2010 IEEE 11th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC). Marrakech:IEEE, 2010:1-5.
[8] TROPP J A. Greed is good:algorithmic results for sparse approximation[J]. IEEE Transactions on Information Theory, 2004, 50(10):2231-2242.
[9] HE X, SONG R. Pilot pattern optimization for compressed sensing based sparse channel estimation in OFDM systems[C]//2010 International Conference on Wireless Communications & Signal Processing (WCSP). Suzhou:IEEE, 2010:1-5.
[10] QI C, WU L. Optimized pilot placement for sparse channel estimation in OFDM systems[J]. IEEE Signal Processing Letters, 2011, 18(12):749-752.
[11] QI C, WU L. A study of deterministic pilot allocation for sparse channel estimation in OFDM systems[J]. IEEE Communications Letters, 2012, 16(5):742-744.
[12] QI C, YUE G, WU L, et al. Pilot design schemes for sparse channel estimation in OFDM systems[J]. IEEE Transactions on Vehicular Technology, 2015, 64(4):1493-1505.
[13] QI C, YUE G, WU L, et al. Pilot design for sparse channel estimation in OFDM-based cognitive radio systems[J]. IEEE Transactions on Vehicular Technology, 2014, 63(2):982-987.
[14] NAJJAR L. Pilot allocation by Genetic Algorithms for sparse channel estimation in OFDM systems[C]//21st European Signal Processing Conference (EUSIPCO 2013). Marrakech:IEEE, 2013:1-5.
[15] HE X, SONG R, ZHU W P. Pilot allocation for sparse channel estimation in MIMO-OFDM systems[J]. IEEE Transactions on Circuits and Systems Ⅱ:Express Briefs, 2013, 60(9):612-616.
[16] LARRAÑAGA P., LOZANO J. A. Estimation of distribution algorithms:a new tool for evolutionary computation[M]. New York:Springer Science & Business Media, 2001:58-59
[17] FLANDRIN P. Time-frequency/time-scale analysis[M]. Orlando:Academic Press, 1998:237-240.
[18] FORNASIER M. Theoretical foundations and numerical methods for sparse recovery[M]. New York:Walter de Gruyter, 2010:108-111.

[1] 吴超, 刘元安, 吴帆, 范文浩, 唐碧华. 移动性受限物联网应用中基于图论的高效数据采集策略[J]. 浙江大学学报(工学版), 2018, 52(8): 1444-1451.
[2] 周宇, 王红军, 邵福才, 沙文浩. 无线通信网络电磁态势生成中的信号覆盖探测算法[J]. 浙江大学学报(工学版), 2018, 52(6): 1088-1096.