Constant Modulus Semi-Blind Equalizer Based on Structure Risk Minimum Criterion

doi:10.13190/jbupt.200905.93.369

JOURNAL OF BEIJING UNIVERSITY OF POSTS AND TELECOM ›› 2009, Vol. 32 ›› Issue (5): 93-98.doi: 10.13190/jbupt.200905.93.369

• Reports • Previous Articles Next Articles

Constant Modulus Semi-Blind Equalizer Based on Structure Risk Minimum Criterion

SONG Heng1,MAO Zhong-yang1,WANG Hong-xing1,MA Shi-ping2

(1. Department of Electronic Information Engineering, Naval Aeronautical and Astronautical University, Shandong Yantai 264001, China;
2. School of Engineering, Air Force Engineering University, Xi'an 710038, China)

Received:2009-01-19 Revised:2009-07-09 Online:2009-10-28 Published:2009-10-28
Contact: SONG Heng

Abstract

Abstract:

According to the track performance of adaptive filters with poor performance in
rapid fading channel, an adaptive filter principle based on capability control a
nd semiblind technology is presented. And a semi-blind equalizer based on con
stant modulus characteristic and structure risk minimum (SCM-SRM) criterion is
designed. The information of communication signals learning should sufficiently be dug. On the other hand, the structure information of oneself of filters shoul
d also sufficiently be dug (by use of a capability control method). In a word, t
he track performance of filters is improved by maximizing amount of learning information. Simulation is carried out that compared with a typical recursive l
east squares equalizer and a constant modulus semi-blind equalizer, SCM-SBE has better track performance in much less training data, and adapts for wireless motion communications.

Key words: equalization, filter, capability control, semi-blind, constant modulus

SONG Heng1,MAO Zhong-yang1,WANG Hong-xing1,MA Shi-ping2. Constant Modulus Semi-Blind Equalizer Based on Structure Risk Minimum Criterion[J]. JOURNAL OF BEIJING UNIVERSITY OF POSTS AND TELECOM, 2009, 32(5): 93-98.

References

[1] Haykin S. Adaptive filter theory [M]. 4th ed. New Jersey: Pearson Education Inc, 2002.
[2] Bapat J L. Partially blind estimation: ML-based approaches and Cramer-Rao bound[J]. Signal Processing, 1998, 71(3): 265-277.
[3] Rousseaux O, Leus G, Stoica P, et al. Gaussian maximum-likelihood channel estimation with short training sequences[J]. IEEE Trans on Wireless Communications, 2005, 4(6): 2945-2955.
[4] Buchoux V, Cappe O, Moulines E, et al. On the performance of semi-blind subspace-based channel estimation[J]. IEEE Trans on Signal Processing, 2000, 48(6): 1750-1759.
[5] Muquet B, de Courville M, Duhamel P. Subspace-based blind and semi-blind channel estimation for OFDM systems[J]. IEEE Trans on Signal Processing, 2002, 50(7): 1699-1712.
[6] Pora W, Chambers J A, Constantinides A G. Combination of Kalman filter and constant modulus algorithm with variable stepsize for the equalization of fast-fading channels[J]. Electronics Letters, 1998, 34(18): 1718-1719.
[7] Vapnik V N. 统计学习理论的本质[M]. 张学工, 译. 北京: 清华大学出版社, 2000: 63-68.
[8] Sebald D J, Bucklew J A. Support vector machine techniques for nonlinear equalization[J]. IEEE Trans on Signal Processing, 2000, 48(10): 3217-3226.
[9] Chen S, Gunn S, Harris C J. Decision feedback equalizer design using support vector machines[J]. IEE Vision, Image, Signal Processing, 2000, 147(3): 213-219.
[10] ?Albu F, Martinez D. The application of support vector machines with Gaussian kernels for overcoming co-channel interference//Proceedings of the 9th IEEE International Workshop Neural Networks Signal Processing. Madison: IEEE Press, 1999: 49-57.
[11] ?Chen S, Samingan A K, Hanzo L. Support vector machine multiuser receiver for DS-CDMA signals in multipath channels[J]. IEEE Trans on Neural Networks, 2001, 12(5): 604-611.
[12] ?Santamaría I, Pantaleon C, Vielva L, et al. Blind equalization of constant modulus signals using support vector machines[J]. IEEE Trans on Signal Processing, 2004, 52(6): 1773-1782.
[13] ?宋恒, 林雪原, 王红星,等. 采用SRM准则的盲均衡器[J]. 北京邮电大学学报, 2008, 31(4): 6-9. Song Heng, Lin Xueyuan, Wang Hongxing, et al. A blind equalizer based on SRM rule[J]. Journal of Beijing University of Posts and Telecommunications, 2008, 31(4): 6-9.
[14] ?Moustakides G V. Study of the transient phase of the forgetting factor RLS[J]. IEEE Trans on Signal Processing, 1997, 45(10): 2468-2476.
[15] ?Agee B G. The least-squares CMA: a new technique for rapid correction of constant modulus signals//Proceedings of IEEE ICASSP. Tokyo: IEEE Press, 1986: 953-956.

Constant Modulus Semi-Blind Equalizer Based on Structure Risk Minimum Criterion

PDF

Knowledge

Abstract

Cite this article

share this article

References

Related Articles 15

Recommended Articles

Metrics

Comments

[1]	LIU Jinming, ZHANG Biling, ZHANG Yuyan. Adaptive federated filtering algorithm based on multi-sensor redundant data cooperative tracking [J]. Journal of Beijing University of Posts and Telecommunications, 2023, 46(4): 21-26.
[2]	ZHANG Yifan, WU Yongle, WANG Qing, WANG Weimin. Design of a High-Selectivity Absorptive Dual-Band Balanced Bandpass Filter [J]. Journal of Beijing University of Posts and Telecommunications, 2023, 46(4): 1-8.
[3]	XIN Yu, XU You, ZHANG Huaijin, BAO Tong, KONG Dejin. High Time-Frequency Efficiency Generalized Filter Banks Frequency Division Multiplexing Modulation Scheme [J]. Journal of Beijing University of Posts and Telecommunications, 2023, 46(4): 109-115.
[4]	LIU Yang, TENG Yinglei, NIU Tao, ZHI Jialin. Filter Pruning Algorithm Based on Deep Reinforcement Learning [J]. Journal of Beijing University of Posts and Telecommunications, 2023, 46(3): 31-36.
[5]	ZHANG Haoge, SHAO Yubin, LONG Hua, PENG Yi, ZHOU Dachun. Language Recognition Based on Log Gammatone-Scale Filter Bank Energies Spectrograms [J]. Journal of Beijing University of Posts and Telecommunications, 2023, 46(1): 38-43.
[6]	LIU Jinming, ZHANG Yuyan, ZHANG Biling. Trajectory Estimation Algorithm for Unmanned Aerial Vehicle Based on LSTM-KF [J]. Journal of Beijing University of Posts and Telecommunications, 2022, 45(5): 121-128.
[7]	SHI Zicheng, LI Xin, TANG Ying, HUANG Shanguo. Optical Packet Filtering System Based on All-Optical Pattern Matching [J]. Journal of Beijing University of Posts and Telecommunications, 2022, 45(3): 96-101.
[8]	HUO Yuanlian, GONG Qi, QI Yongfeng, AN Yaqi. Adaptive Kernel RBFNN Based on Normalized Least Mean Square Algorithm [J]. Journal of Beijing University of Posts and Telecommunications, 2022, 45(2): 29-35.
[9]	HUO Yuanlian, LIAN Peijun, QI Yongfeng, WANG Danfeng. A New Fast Convex Combination Affine Projection Sign Algorithm for S-type Functions [J]. Journal of Beijing University of Posts and Telecommunications, 2022, 45(1): 102-107.
[10]	SONG Cheng, JIN Tong, HE Jun-yi. A Multi-Value Prediction Location Privacy Protection Mechanism [J]. Journal of Beijing University of Posts and Telecommunications, 2021, 44(6): 103-108.
[11]	YANG Yu-hao, WU Yong-le, WANG Wei-min. Design and Realization of a Filtering Gysel Power Divider [J]. Journal of Beijing University of Posts and Telecommunications, 2021, 44(6): 122-128.
[12]	CHEN Jian-mei, QIU Hong-bing, ZHENG Lin, YANG Chao. Non-Data-Aided Estimation and Compensation of Amplitude, Frequency and Phase for Spectrum Combination [J]. Journal of Beijing University of Posts and Telecommunications, 2021, 44(5): 35-40.
[13]	LI Xing-hua, LIU Xiao-ping, WANG Gang, ZHAO Yun-long, LI Yong-wei. An Adaptive Hybrid Filter Algorithm for Attitude Estimation [J]. Journal of Beijing University of Posts and Telecommunications, 2021, 44(3): 79-86.
[14]	SHAO Yu-bin, LIU Jing, LONG Hua, DU Qing-zhi, LI Yi-min. Language Identification Based on Vocal Tract Spectrum Parameters [J]. Journal of Beijing University of Posts and Telecommunications, 2021, 44(3): 112-119.
[15]	WANG Yong, YIN En-min, RAN Xun. Differential Privacy-Preserving Recommendation Algorithm Based on Bhattacharyya Coefficient Clustering [J]. Journal of Beijing University of Posts and Telecommunications, 2021, 44(2): 81-88.