浅水时变多途信道特性分析与模型实验研究

时变多途水声信道是影响水声通信性能的一个重要因素,深入了解水声信道挣性并对水声信道进行建模具有重要的研究意义。本文在分析传统时变信道模型基础上,从时域角度出发,提出采用AR(ρ)模型对已有的浅水时变多途信道模型中的小尺度衰落分量进行修正。然后基于莲花湖实测信道数据,分析了时变信道各个路径的幅度、时延、时间相干系数、系统传递函数等特性,并对修正模型进行了验证正。从仿真结果来看,修正模型与试验结果拟合的很好。本文从多个方面对水声信道特性进行了分析,有助于对水声信道的深入了解,同时为水声通信系统性能评估提供了一种仿真信道模型。     

时变水声信道的动态压缩感知估计

水声多径信道具有的稀疏特性已被应用于设计稀疏估计方法提高信道估计性能。然而,水声信道具有的快速时变特性,给传统稀疏信道估计方法带来了很大的困难。考虑到水声信道除了高时变性多径,还存在着相对静止,缓慢变化的直达径或者海底反射径,通过将水声信道建模为由静态和时变稀疏支撑集组成,把时变水声信道估计转化为动态压缩感知问题。结合卡尔曼滤波和压缩感知理论,并采用原始对偶追踪算法求解Dantzig selector模型,从而实现对复数域基于卡尔曼滤波器的压缩感知稀疏求解问题的处理。信道时变条件下的数值仿真及基于信道估计的判决反馈均衡器的海上实验结果表明,该算法相对经典的正交匹配追踪和最小二乘QR分解算法具有较明显的性能改善。从而说明,通过对时变水声信道进行动态压缩感知估计可有效提高估计性能。     

时变信道下的被动时间反转扩频水声通信

本文研究了时变信道条件下采用被动时间反转的直接序列扩频水声通信方案。多通道被动时间反转可通过对信道多径进行时间、空间聚焦实现信道匹配,但低信噪比、时变特性造成的信道特性失配对被动时间反转处理的性能造成严重影响。在垂直阵接收的基础上,本文采用码片级信道估计获取水声信道特性并进行周期性更新,并采用已判决码元产生的扩频码片作为信道估计训练序列,结合应用稀疏信道估计算法抑制零值抽头上的估计噪声,从而可有效改善时变、低信噪比条件下的被动时间反转处理的时、空多径聚焦效果,提高扩频通信性能。通过湖试实验比较了采用稀疏信道估计、传统信道估计算法的时反扩频接收机,以及经典直扩接收机的通信性能,实验结果表明：本文方案可在低信噪比获得较好的性能,并有效抑制时变信道对时反扩频通信性能的影响。     

深海远程正交频分复用水声通信块间迭代稀疏信道估计方法

在深海远程正交频分复用(OFDM)水声通信中,信道时延长、频率选择性衰落严重,传统的块独立压缩感知稀疏估计需要较高导频插入密度才能保证一定的估计性能,通信频谱利用率较低。提出了一种基于信道稀疏时变建模的块间迭代信道估计方法,利用深海信道在两个相邻OFDM数据块之间的时间相关性建立块间信道稀疏多途结构的时变关系,在此基础上,对传统稀疏信道估计算法中的候选字典矩阵的字典原子进行删减并改进优化方程,实现了对前一数据块所估信道信息的有效利用,显著降低了信道估计所需的导频插入密度。在深海不同接收深度、不同距离条件下开展了海试验证,实验结果表明,与传统稀疏信道估计方法相比,本方法在导频插入密度减半的条件下可达到优于传统方法的估计性能。     

混合稀疏水声信道的动态区分性压缩感知估计

由于水声传播过程中同时存在声信号直达、静态或动态边界反射的现象,水声信道会呈现不同动态特性的多径,形成具有混合稀疏的结构,即多径由静态或相对缓变的平稳多径分量和快速时变的动态多径分量混合组成。对于混合稀疏信道,经典的稀疏信道估计算法未考虑混合稀疏性,将导致算法失配、性能下降;以时变稀疏集为模型,动态压缩感知(DCS)结合卡尔曼滤波(KF-CS)可提高对时变多径分量的估计精度,但KF对静态稀疏分量的估计无法充分挖掘其稀疏性。通过将混合稀疏水声信道建模为由静态和时变支撑集所组成的稀疏集,提出一种动态区分性压缩感知(DDCS)方法。该算法首先结合同步正交匹配追踪(SOMP)和正交匹配追踪(OMP)将混合稀疏多径进行区分,分解为静态分量和时变分量;然后,分别用KF-CS和同步正交匹配追踪算法估计时变和静态多径的幅度;最后,将静态分量和时变分量的估计结果整合以得到整个水声信道的冲激响应。通过海试实验把所提DDCS算法与经典信道估计算法、压缩感知算法和DCS算法进行了比较,验证了所提算法的有效性。结果表明,对混合稀疏水声信道进行区分性稀疏估计可改善信道估计性能,进而可通过信道估计均衡器提升水声通信质量。      

基于正交频分复用的水声自适应通信系统性能仿真研究

本文从平均谱效率的角度分析并讨论了基于正交频分复用(Orthogonal Frequency Division Multiplex,OFDM)技术的水声自适应通信系统的通信性能。在两种典型的水声统计信道假设下,根据信道状态信息的不同精确程度,针对不同的调制方式,对水声自适应通信系统的平均谱效率进行了理论推导,并给出了部分性能函数的解析形式,而后从多个角度给出了较为全面的数值仿真分析结果。仿真结果显示:当目标误码率为10-3时,水声自适应通信系统可以在相同发射功率下,显著地改善通信性能(约3 bit/s/Hz);在同样的目标误码率下,如果维持传输性能不变,自适应通信系统可以显著节省发射功率(约10 dB)。在信道状态信息不确知的情况下,当信道估计误差大于-15 dB,或多普勒补偿后信道的扩展因子大于0.03时,自适应系统的性能才会显著劣化。此外,在统计意义上,自适应通信方法对于系统性能的改善程度随通信距离的增加而增大。     

水声多途信道的维纳误差限信道质量量化分析方法

提出了一种定量分析不同多途结构的时不变水声信道对单载波水声通信系统性能影响程度的方法。该方法利用水声信道下信号线性均衡的残留均方误差与通信系统误比特率性能相关性强的特点,计算信号线性均衡的残留均方误差极限,并将其表示为只与信道冲激响应有关的变量,称之为维纳误差限(WEB),将此作为多途信道质量量化指标来评估多途信道对通信性能的影响。为验证方法性能,对比分析了大量海试实测水声信道下,线性均衡、判决反馈均衡以及Turbo均衡等单载波通信中3种常用信道均衡方法的误比特率与多种水声信道质量量化指标的相关性,利用Spearman相关系数对相关性进行量化分析,实验结果表明,相比于时延扩展、相干带宽、频谱衰落深度和信号多径比等传统信道多途特性量化指标,维纳误差限与均衡后误比特率的Spearman相关系数更高,平均相关系数可达0.71。利用维纳误差限可有效量化和分类不同质量的多途信道,定量体现不同水声信道多途结构对于通信性能的影响程度。     

一种基于DFT时域插值的OFDM水声信道估计改进方法

信道估计作为OFDM通信系统中的重要部分,其性能关系到整个系统的误比特率。本文提出了一种基于DFT时域插值的信道估计改进方法,用于OFDM水声通信系统。该方法利用噪声门限抑制多径之间的信道估计噪声,计算简单,达到较好的信道估计效果。对该方法进行了理论分析,仿真实验以及海试。在海试中得到传输距离2km,有效数据率2.8kbit/s,证明该方法可以用于中短程浅海水声通信。     

基于高阶统计的水声信道盲辨识

本文给出了基于ARMA模型的水下通信系统模型,将一种基于三阶统计的算法应用到水声信道盲辨识领域,在不需要训练序列的条件下估计得到信道传输函数。与基于二阶统计特性方法相比,该算法具有较强的抗噪性,更适合信噪比低于12dB条件下水声信道的辨识。通过对水声信道盲辨识的计算机仿真,验证了该算法具有较高的辨识精度。     

高速水声通信系统仿真研究

水声信道是较复杂的数据通信环境。本文设计了3种高速水声通信的系统结构,并通过系统的、全面的仿真比较了他们的性能。建立了包括时变衰落、多途和加性干扰的水声信道模型。3种方案都采用相位相干的QPSK调制技术,接收端采用空时联合的自适应均衡(内置DPLL)接收;前向纠错编码译码器分别采用3种方案:卷积码,串行级联码(卷积码+RS码),并行级联卷积码(Turbo码)。通过仿真研究了不同数目水声接收机的接收分集下的系统性能,研究了3种编码方案下的系统性能。     

基于LMS/SOLMS算法的时变多径水声信道估计方法

缓变信道下基于LMS算法的信道估计算法具有较好的跟踪性能,但对快变信道,LMS算法跟踪性能下降。SOLMS算法具有比LMS算法更好的跟踪性能,尤其是在快变的信道下。但由于SOLMS算法在收敛阶段的振荡性,这时收敛速度较LMS算法慢。本文提出一种收敛模式下用LMS算法获得信道的参数,收敛后则切换成SOLMS算法跟踪信道的变化的信道估计方法。新方法结合了LMS算法收敛快和SOLMS算法跟踪性能好的优点。对时变多径水声信道估计的计算机仿真实验证明了该方法的有效性。     

Exploiting joint sparsity for underwater acoustic MIMO communications

MIMO communication has been recognized as a potential solution for high speed underwater acoustic communication, which unfortunately encounters significant difficulties posed by simultaneous presence of multipath and Co-channel interference (CoI). Sparsity contained in the multipath structure of underwater acoustic channels offers an effective way for improving channel estimation quality and thus enhancing the communication performance in the form of time reversal or channel estimation based equalization. However, for MIMO channels with extensive multipath and CoI, the performance gain achieved by classic sparsity exploitation channel estimation methods such as orthogonal matching pursuit (OMP) is still not enough to yield satisfactory performance. Under quasi-stationary assumption, underwater acoustic channels of adjacent data blocks exhibit correlated multipath structure, namely, multipath arrivals with similar time delay but different magnitude, which has not been exploited. In this paper, a joint sparse recovery approach is proposed to exploit the sparse correlation among adjacent data blocks to improve the performance of channel estimation. Under the framework of distributed compressed sensing (DCS), a joint sparse model which treats the multipath arrivals as sparse solutions with common time support is adopted to derive a joint sparse recovery algorithm for efficient channel estimation, the results of which are used to initialize and periodly update a channel estimation based time reversal receiver. Finally, underwater MIMO communication experimental results obtained in a shallow water channel are provided to demonstrate the effectiveness of the proposed method, compared to the same type of receiver that do not exploit the joint sparse.     

A high-frequency warm shallow water acoustic communications channel model and measurements

Underwater acoustic communication is a core enabling technology with applications in ocean monitoring using remote sensors and autonomous underwater vehicles. One of the more challenging underwater acoustic communication channels is the medium-range very shallow warm-water channel, common in tropical coastal regions. This channel exhibits two key features-extensive time-varying multipath and high levels of non-Gaussian ambient noise due to snapping shrimp-both of which limit the performance of traditional communication techniques. A good understanding of the communications channel is key to the design of communication systems. It aids in the development of signal processing techniques as well as in the testing of the techniques via simulation. In this article, a physics-based channel model for the very shallow warm-water acoustic channel at high frequencies is developed, which are of interest to medium-range communication system developers. The model is based on ray acoustics and includes time-varying statistical effects as well as non-Gaussian ambient noise statistics observed during channel studies. The model is calibrated and its accuracy validated using measurements made at sea.     

参量阵差分Pattern时延差编码冰下水声通信方法（英文）

In order to meet the demands of underwater acoustic communication in under ice environment,a differential Pattern time delay shift coding underwater acoustic communication method based on parametric array is introduced in this paper.The under ice underwater acoustic channel is characterized by heavy multipath transmission.Under this model,a parametric array emission method of Pattern signal is derived and the system performance is analyzed.A broadband low frequency sound waves with narrow beam-pattern,which will reduce the interface reflections and suppress the effects of multipath transmission,can be obtained by the emission method.The Songhua River under ice trial results show that there is an anti-multipath property and a higher data rate in the under-ice acoustic channel in proposed approach.     

参量阵差分Pattern时延差编码冰下水声通信方法

为提高差分Pattern时延差编码水声通信方法的通信速率以及抗多途能力,使其能有效适用于冰下水声环境,提出了基于参量阵的差分Pattern时延差编码水声通信方法,推导了Pattern码的参量发射原理,分析了参量阵发射对该方法性能的影响,利用参量阵发射产生低频宽带窄指向性声柬,减少了声线触碰上下边界的次数,提高了系统抗多途的能力。冰下水域外场试验结果表明:本方法可有效抑制多途效应,同时低频宽带特性提高了系统通信速率。      

Time reversal acoustic communication receivers: DSP implementation and fast channel estimation

A communication system is implemented on digital signal processors (DSPs) for the underwater acoustic environment. The implemented receiver uses time reversal multi-channel combining followed by a single-channel decision feedback equalizer. Periodic channel estimation is employed to track the channel fluctuations. These techniques are used to mitigate time-varying inter-symbol interference, which is the main challenge in the underwater acoustic channel at operating frequencies greater than 10 kHz. Various optimization tasks are performed to reduce the receiver computational complexity. A fast implementation of the matching pursuit algorithm is tested on the DSP platform. Its performance, in terms of accuracy and run-time, is compared with that of the basic matching pursuit algorithm. Experimental results of the transmission and demodulation of binary phase-shift keying signals at three different symbol rates were obtained in the local Delaware Bay. The low bit error rates demonstrate the effectiveness of our implementation.     

采用时反和时频差分OFDM的水声语音通信方法

针对水声信道多径、时变、多普勒等恶劣传输特点对水声语音通信的严重影响,本文采用多通道时间反转和时频差分OFDM进行水声语音通信技术方案设计,该方法首先通过多通道时间反转进行时间域和空间域多径聚焦,进而结合时频差分OFDM调制解调抑制残留多径的影响。由于无需采用信道估计和均衡算法,系统实现方便、复杂度低,同时对信道具有一定程度的稳健性。该方法语音压缩编码采用混合激励线性预测编码。仿真实验和海试实验表明了本文方案的有效性。     

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。