一种混合常数模水声信道盲均衡新算法的研究

针对常数模算法(CMA)与符号误差常数模算法(SECMA)的不足,本文提出了一种新的混合常数模算法(CCMA),并将该算法应用于水声信道的盲均衡。通过判决条件对输出信号作判决,使得该算法的迭代过程在CMA和SECMA之间自动切换,其性能较SECMA稳健,运算量小于CMA,特别有利于水声信息的实时恢复。通过多种水声信道盲均衡算法的仿真实验,进一步验证了该算法的有效性。     

一种新的适用于水声信道的常模类盲均衡算法

为了缓解常数模盲均衡算法收敛速度缓慢、稳态误差大的问题,考虑到初始化权值对CMA算法的重要影响,本文利用遗传算法对CMA算法进行了有效改进,引入了小样本重用的思想,给出了一种新的适用于水声信道的常模类盲均衡算法。计算机仿真研究证明,该算法不仅大大加快了收敛速度,而且有效地降低了稳态误差。     

一种快速收敛的符号回归常数模盲均衡算法

为了加快符号回归常数模算法(SRCMA)的收敛速度,本文提出了一种适合于BPSK信号 的快速算法。该算法用新的误差函数替代SRCMA中的误差函数,新误差函数针对BPSK信号而 设计。新算法采用分数间隔均衡模型,有效地加快了SRCMA算法的收敛速度。水声信道仿真实验 表明,该算法性能稳定,收敛速度快,适用于快速变化信道的盲均衡和水声通信数据的实时恢复。     

基于判决导引的水声信道混合盲均衡算法研究

提出了一种适用于正交幅度调制(QAM)信号的混合盲均衡算法,该算法在初始模式中分别对QAM信号的同相分量和正交分量进行均衡,利用方形环判决域对均衡器输出信号进行判决,当误码率降到足够低的水平时自动切换到判决导引最小均方误差算法。最后利用水声信道仿真模型,对该算法的性能进行了验证。结果表明:该算法性能稳健,收敛后均方误差小,有效降低了高速水声通信的误码率,提高了水声信道均衡的稳定性,且有良好的冷启动和重新启动能力。     

遗传优化神经网络的水声信道盲均衡

不需要训练序列的盲均衡技术可以有效地节省水声通信带宽，消除码间干扰，提高水声通信效率和质量。以前馈神经网络（FNN）作为盲均衡器，既适用于最小相位信道，也适用于非最小相位信道，包括非线性信道，但是前馈神经网络在实际的应用中其网络拓扑结构的选取和初始权重的确定缺乏理论依据，且其训练主要依靠BP算法，存在收敛速度慢、容易陷入局部极值及“过学习”的问题。为此，本文提出了一种遗传优化神经网络的水声信道盲均衡算法（GA—BP），对前馈神经网络拓扑结构和网络权重同时优化，有效地克服了传统前馈神经网络盲均衡的缺陷，提高了前馈神经网络盲均衡的泛化性能并加强了跟踪时变信道的能力和对信道突变的适应能力。水池试验结果证明了文中提出的遗传优化神经网络水声信道盲均衡算法的有效性，与直接前馈神经网络盲均衡相比较，均衡性能明显得到了提高。     

超指数判决反馈水声信道盲均衡算法实验研究

利用超指数算法收敛速度快的优点,对判决反馈盲均衡算法的前向权向量的迭代式进行了修正,提出了一种新的判决反馈盲均衡算法。该算法具有收敛速度快,跟踪性能好等特点。通过水池实验,获得了符合盲均衡算法统计特性的BPSK数据,对所提出的算法与自适应判决反馈均衡算法,常数模盲均衡算法等进行了对比分析。结果表明,该算法可以有效的降低误码率,且收敛速度要优于其他算法,可靠实现了对多途水声信道的均衡。     

一种能有效消除水声信道相位连续旋转的分数间隔盲均衡算法研究

针对信道均衡过程中的均衡器输出相位连续旋转问题,提出一种带有二阶数字锁相环的分数间隔超指数迭代盲均衡算法。该算法利用分数间隔超指数迭代算法加强对信道多途的抑制,利用二阶数字锁相环消除均衡器输出信号连续相位旋转,从而实现对原始发射信号的正确恢复。水池实验结果表明:该算法相对于常规盲均衡算法,收敛速度快,剩余均方误差小,能够有效地消除均衡器输出信号相位连续旋转,从而降低水声通信系统的误码率。     

改进支持向量机和常数模算法水声信道盲均衡

针对盲均衡算法收敛速度较慢的问题,提出一种结合改进支持向量机和常数模算法的水声信道盲均衡算法。该算法首先利用具有优异小样本学习能力的支持向量机进行盲均衡器权系数初始化,在完成初始化后切换至运算量较小的常数模算法。考虑到支持向量机本身非自适应运算的限制,在时变水声信道条件下利用经典支持向量机获得的均衡器初始权向量与切换后的信道仍然存在失配。因此,本文导出时变条件下的改进支持向量机用于盲均衡器初始化,改善算法切换时的权系数失配,并结合分数间隔结构和内嵌数字锁相环进一步提高盲均衡算法性能。仿真和湖试实验结果表明:在时变水声信道条件下,本文算法的收敛性能优于经典支持向量机盲均衡算法。     

一种水声信道均衡器的混合算法

水声高速相干通信中使用自适应均衡对抗信道在接收信号中产生的码间串扰。目前,1/2分数间隔采样的判决反馈均衡器结构得到了广泛的应用。本文分析了几种自适应算法在此种均衡器结构下的性能,结合浅海水声信道的特点,提出了一种快速卡尔曼滤波和快速自优化最小均方的混合算法,模拟及海试结果表明,该混合算法在计算复杂度、收敛速度以及稳定性方面都有很好的性能,已经应用到了水声实时高速通信系统当中。     

水声信道线性均衡的研究

本文在对LMS和稀疏权自适应均衡算法进行分析的基础上，将其引入到水声数据传输中，利用LMS算法对时不变信道和慢变信道进行了仿真实验；利用稀疏权自适应均衡算法对深海信道进行了仿真实验，并获得了仿真结果。     

Adaptive and efficient nonlinear channel equalization for underwater acoustic communication

We investigate underwater acoustic (UWA) channel equalization and introduce hierarchical and adaptive nonlinear (piecewise linear) channel equalization algorithms that are highly efficient and provide significantly improved bit error rate (BER) performance. Due to the high complexity of conventional nonlinear equalizers and poor performance of linear ones, to equalize highly difficult underwater acoustic channels, we employ piecewise linear equalizers. However, in order to achieve the performance of the best piecewise linear model, we use a tree structure to hierarchically partition the space of the received signal. Furthermore, the equalization algorithm should be completely adaptive, since due to the highly non-stationary nature of the underwater medium, the optimal mean squared error (MSE) equalizer as well as the best piecewise linear equalizer changes in time. To this end, we introduce an adaptive piecewise linear equalization algorithm that not only adapts the linear equalizer at each region but also learns the complete hierarchical structure with a computational complexity only polynomial in the number of nodes of the tree. Furthermore, our algorithm is constructed to directly minimize the final squared error without introducing any ad-hoc parameters. We demonstrate the performance of our algorithms through highly realistic experiments performed on practical field data as well as accurately simulated underwater acoustic channels.     

Bandwidth-efficient frequency-domain equalization for single carrier multiple-input multiple-output underwater acoustic communications

This paper proposes a single carrier (SC) receiver scheme with bandwidth-efficient frequency-domain equalization (FDE) for underwater acoustic (UWA) communications employing multiple transducers and multiple hydrophones. Different from the FDE methods that perform FDE on a whole data block, the proposed algorithm implements an overlapped-window FDE by partitioning a large block into small subblocks. A decision-directed channel estimation scheme is incorporated with the overlapped-window FDE to track channel variations and improve the error performance. The proposed algorithm significantly increases the length of each block and keeps the same number of training symbols per block, hence achieving better data efficiency without performance degradation. The proposed scheme is tested by the undersea data collected in the Rescheduled Acoustic Communications Experiment (RACE) in March 2008. Without coding, the 2-by-12 MIMO overlapped-window FDE reduces the average bit error rate (BER) over traditional SC-FDE schemes by 74.4% and 84.6% for the 400 m and 1000 m range systems, respectively, at the same data efficiency. If the same BER performance is required, the proposed algorithm has only 8.4% transmission overhead, comparing to over 20% overhead in other existing UWA OFDM and SC-FDE systems. The improved data efficiency and/or error performance of the proposed FDE scheme is achieved by slightly increased computational complexity over traditional SC-FDE schemes.     

水声通信中基于信道辨识的盲turbo均衡方法

水声信道多途效应明显,造成接收信号存在严重的码间干扰(ISI,Intersymbol interference)。基于最小均方误差(MMSE,Minimum mean square error)准则的turbo均衡器级联了均衡和信道译码,能够有效去除ISI,并获得优良的性能。由于水声信道的时变性,传统MMSE-turbo均衡需要周期性的训练序列,以实现连续可靠的通信。训练序列虽然提高了通信的可靠性,但降低了信息的有效传输速率。因此,为提高通信效率,本文提出了一种盲turbo均衡方法,该方法通过引入新的盲信道辨识器来同时获得信道估计响应和已去除部分ISI的初步均衡输出信号,并为turbo均衡提供初始的响应参数和比特软信息。与水声通信中应用较多的盲判决反馈均衡器(DFE,Decision feedback equalizer)相比,海上实验结果证明本文提出的盲turbo均衡方法抗信道多途衰落的能力较强,并且与传统MMSE-turbo均衡相比无需训练序列,因此提高了信息的有效传输速率。     

Bidirectional equalization for underwater acoustic communication

The bidirectional decision feedback equalizer (BiDFE) that combines the outputs of a conventional decision feedback equalizer (DFE) and backward DFE can improve the performance of the conventional DFE by up to 1-2 dB based on simulations. In this letter, the BiDFE concept is extended to multichannel time reversal communications involving a DFE as a post-processor. Experimental data collected in shallow water (10-20 kHz) show that the performance can be enhanced by 0.4-1.8 dB in terms of output signal-to-noise ratio. In particular, a larger improvement (e.g., 1.8 dB) is achieved for time-varying channels where the channel diversity in opposite directions is more profound.