稀疏水声信道判决反馈盲均衡算法研究

张艳萍; 赵俊渭; 李金明

稀疏水声信道判决反馈盲均衡算法研究

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出版历程
- 收稿日期: 2004-10-21
- 修回日期: 2005-04-21
- 刊出日期: 2006-06-19

For Sparse Underwater Acoustic Channel Equalization

摘要

摘要: 针对高速水声通信中信道的稀疏特性，提出了一种基于常数模准则的稀疏水声信道判决反馈盲均衡算法。该算法将改进的常数模算法与一种变化的判决反馈均衡器结构(部分反馈均衡器)有机结合，利用水声信道的稀疏特性，不但很好地实现了稀疏水声信道的盲均衡，而且简化了计算，易于算法的硬件实现。用典型稀疏水声信道进行了计算机仿真。结果表明，该算法性能稳定，计算量小，稳态均方误差低，整体性能与基于自适应LMS的稀疏迭代算法接近。该研究为高速水声通信中稀疏信道的均衡提供了一种可实现的方法。
- 水声通信;稀疏信道;盲均衡;判决反馈
Abstract: A blind equalization algorithm based on constant modulus and sparse underwater acoustic channel is presented according to the sparse characteristic of the high rate underwater acoustic communications. The algorithm combines the improved constant modulus algorithm with a variation of the decision feedback equalizer, namely the partial feedback equalizer, and uses the sparse characteristic of the underwater acoustic channel. It can not only achieve better equalization of the sparse underwater acoustic channel , but also calculate effectively and use easily hardware to carry out the algorithm . Simulation tests are dynamically conducted using the typical sparse underwater acoustic channel model. Simulation results show that the proposed algorithm has the advantages of robustness, calculation-efficient, lower steady state mean squared error, as compared to the self-adaptive LMS algorithm based sparse iteration.

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参考文献(1)

高路，贺志强等．高速水声通信系统仿真研究．声学学报，2003；28(1)：33 .39.[2]Chatha H S, Kumar A, Bahl R.Simulation studies of underwater communication system in shallow oceanic channel [J].Oceans '02 MTS/IEEE , Oct. 29-3.2002, Vol.4:2401-[3]Lopez M J, Singer A C, Whitney S L, Edelson G S．A DFE coefficient placement algorithm for underwater digital acoustic communications．OCEANS '99 MTS/IEEE. Riding the Crest into the 21st Century , 13-16 Sept., 1999, Vol.2: 996.1001.[4]Geller B, Capellano V, Jourdain G．Equalizer for real time high rate transmission in underwater communications. International Conference on Acoustics, Speech, and Signal Processing, 1995,Vol.5: 3179.3182.[5]Kocic M, Brady D, Merriam S．Reduced-complexity RLSestimation for shallow-water channels．Proceedings of the 1994Symposium on Autonomous Underwater Vehicle Technology, 1994: 165.170.[6]Kocic M, Brady D, Stojanovic M．Sparse equalization for real-time digital underwater acoustic communications．Oceans '95 Conference Proceedings, 1995,Vol.3: 1417.1422.[7]Rontogiannis A A, Berberidis K．Efficient decision feedback equalization for sparse wireless channels．IEEE Trans. on Wireless Communications, 2003, 3(2) : 570.581.[8]De Parthapratim, Bao Jay, Poon T.A calculation-efficient algorithm for decision feedback equalizers[J].IEEE Trans. on Consumer Electronics.1999, 45(3):526-[9]王峰，赵俊渭，李洪升等．一种混合常数模水声信道盲均衡新算法的研究．声学学报，2003, 28(2)：137.140.[10]Geller B, Capellano V, Brossier J.Equalizer for video rate transmission in multipath underwater communications[J].IEEE Journal of Oceanic Engineering.1996, 21(2):150-[11]AIDA first year Tech. Rep., MAST 2/CT92/0017.

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