水声通信中脉冲干扰和载波频偏联合估计算法的研究  

Joint Impulsive Noise and Carrier Frequency Shift Estimation in Underwater Acoustic Communication

作　　者：李程程[1] 李有明[1] 吕新荣[1] 季彪 

机构地区：[1]宁波大学通信技术研究所,浙江宁波315211

出　　处：《信号处理》2015年第11期1473-1478,共6页Journal of Signal Processing

基　　金：国家自然科学基金(61571250);宁波市自然科学基金(2015A610121)

摘　　要：脉冲噪声和载波频率偏移严重影响正交频分复用(OFDM)水声通信系统性能。本文提出了基于稀疏贝叶斯学习(SBL)理论联合脉冲干扰和载波频偏估计算法。该算法在每次迭代中首先依据所有载波和频域信号的后验分布得到脉冲噪声最小均方误差(MMSE)估计值,然后根据该值估计出相应的载波频偏并对接收信号进行补偿,以降低脉冲噪声和载波频偏之间的相互影响。仿真结果表明,与已有分步估计算法相比较,新方法有效的降低了系统误比特率(BER),且该联合算法在非高斯背景下具有更好的稳定性。The impulsive noise and carrier frequency shift affected and limited the performance of underwater acoustic system based on orthogonal frequency division multiplexing（ OFDM） seriously. A new algorithm based on sparse Bayesian learning（ SBL） was presented to estimate the impulse noise and carrier frequency offset jointly. In each iteration of the proposed method,the corresponding carrier frequency shift value was estimated and then taken to have a compensation for the received signals by using null tones,according to the minimum mean square error（ MMSE） estimate of impulse noise,which was firstly got by all the tones and a posterior probability of the received frequency domain signals,and this way could reduce the influence between these two kinds of common interference availably. The simulation results verify that the new algorithm has lower bit error ratio（ BER） compared to the several existing separate estimation algorithms,and improves the robustness of underwater acoustic communication system in the presence of non-Gaussian noise.

关 键 词：水声通信 脉冲噪声 载波频偏 联合估计 稀疏贝叶斯学习 

分 类 号：TN929.3[电子电信—通信与信息系统]