一种针对小多普勒扩展水声信道的OFDM接收算法

在水声正交频分复用（OFDM）通信系统中,水声信道中的多径时延扩展会带来频域选择性衰落,多普勒效应会带来子载波间干扰（ICI）。传统接收算法需要开展复杂的二维（时延/多普勒）信道估计,再进行复杂的信道均衡和符号检测。针对有限多普勒扩展的信道条件下多普勒矩阵元素变化缓慢、ICI干扰范围有限的特点,借鉴多项式拟合思想,提出了一种创新的接收算法。该算法将多普勒矩阵元素近似为多项式函数,迭代进行多项式拟合和数据符号频域均衡。和传统方法相比,该算法无需进行信道多普勒估计,仅需信道的一维（时延）估计即可实现较好的性能。利用Bellhop产生的水声信道仿真结果验证了该算法的可行性。     

一种基于正交频分复用的高速水声通信技术的研究

OFDM(正交频分复用)是一种适合于在多径衰落和受限带宽信道中进行高速传输的技术。论文把OFDM技术应用于高速水声通信中,设计了一套基于OFDM的高速水声通信系统,阐述了OFDM水声通信系统中同步和信道估计的方法。海上试验证明了系统的有效性。     

一种针对深海远程信道的M元扩频接收算法

深海远程水声信道具有多径时延长、信道非最小相位等特点,当扩频增益不足以抑制多径干扰时,信道均衡是必要的。将双向判决反馈均衡技术应用于M元扩频水声通信系统,减小判决反馈均衡错误传播概率,提高常规符号判决反馈均衡器输出信噪比。通过正交M元扩频解扩结果比较正向和反向信道特性,调整分集合并权重因子。和等增益合并正反向均衡输出结果的传统双向判决反馈均衡方法相比,该算法可进一步提高接收处理增益。通过仿真深海远程水声信道获得的试验结果证实了算法的有效性。     

基于软件无线电技术的高速水声通信实验系统设计

水声信道的频带极其有限和多径干扰严重是目前制约水声通信数据率提高的主要瓶颈。正交频分复用(OFDM)技术因具有抗多径干扰和频谱利用率高等特性而被大量通信标准采用。同时,软件无线电技术可简化系统的硬件结构、节省成本且便于升级。结合两种技术的优势,设计了一种基于软件无线电技术的高速水声通信系统。论文详细描述了系统框架、软硬件设计和信号处理流程。最后通过水声实验,验证了该系统具有可靠的传输性能。     

基于802.11a的OFDM符号起始位置估计算法

OFDM(Orthogonal Frequency Divided Multiplication,正交频分复用)技术具有很高的频谱利用率和较好的抗多径衰落,在WLAN 802.11a/g,Wimax,高清数字电视广播和3Gpp-LTE等通信中都采用OFDM技术。OFDM通过循环前缀来抑制符号间干扰。基于802.11a无线帧结构,提出1种基于相关累加的OFDM符号起始位置估计算法,最大程度抑制OFDM符号间干扰(ISI,Inter Symbol Interfernce)。     

基于复杂多通道带乘性噪声模型的水声通信字符估计算法

水声信道具有复杂随机时变特性并存在严重的多径时延、能量损失和畸变等因素,使得水声信道的建模和估计一直是学界的难点问题。本文基于复杂多通道带乘性噪声模型来刻画随机时变的水声信道,在信道建模基础上利用最优滤波递推算法实现发送字符的估计。该算法在线性最小方差意义下是最优的,能有效克服码间干扰和噪声污染。所建立的信道模型能够刻画复杂快变的水声信道,对应的最优信道估计算法具有计算量小的优点,能够动态跟踪信道增益的随机变化。仿真结果验证了本文算法的有效性。     

OTFS水声通信技术研究现状与展望

正交时频空调制是近年来提出的一种用于高速移动无线通信场景的调制技术,通过将时变多径信道转换到时延–多普勒域,使得所有符号都经历几乎相同且变化缓慢的稀疏信道。与正交频分复用系统相比,正交时频空技术具有较低的峰均功率比,且能够有效抵抗多普勒效应,在高时延、高多普勒的信道条件下具备性能优势。简要介绍了正交时频空技术的基本原理,以及目前无线电及水声通信领域正交时频空技术研究与应用现状,梳理了正交时频空技术在工程应用中亟待解决的关键问题,如波形设计、信道估计和均衡以及接收机结构设计等。最后对正交时频空技术在水声通信系统中面临的挑战和应用前景进行了分析和展望。     

基于训练序列的水声信道多普勒频移估计

由于水声通信媒介(声波)速度远远小于陆地通信媒介(无线电波)速度,水声通信多普勒频移比陆地无线通信多普勒频移要大几个数量级,因此多普勒频移估计是水声通信的一个重要问题。文中提出了一种水声通信系统中基于训练序列的多普勒频移估计方法。在接收端先由已知训练符号构造无噪声干扰下的理论接收信号;再根据理论接收信号与实际接收信号之间的误差平方和最小,得到含有信道衰减因子A和多普勒因子Δ的双变量目标函数,根据此目标函数的曲面图以及对其的分析,发现A的不同取值基本不影响Δ的寻优,从而可将双变量目标函数变成单变量目标函数;然后利用全局优化理论中求解有限区间内多峰值函数最值的区间斜率算法,求解多普勒因子的最小二乘估计值,从而得到多普勒频移的估计值。文中还分析了区间斜率算法的收敛性,且仿真结果显示所提算法优于现有算法。     

基于带乘性噪声模型的水声通信字符估计算法研究

水声信道多途效应明显,而且存在衰落、散射、损耗以及随机时变等特性,使得水声通信系统的接收信号存在严重的码间干扰.利用带乘性噪声系统模型来刻画随机信道,在建模基础上利用最优滤波递推算法实现状态估计.由于状态向量中的第一维与接收信号之间存在一一对应关系,进而可实现水声信号的估计.该算法在最小方差意义下是最优的,能有效克服码间干扰和噪声污染.2种信道的仿真结果表明,在信噪比(SNR)为18db时,误码率(BER)均已经降低到10-4数量级,验证了算法的有效性.     

时变多径水声信道的仿真研究

本文针对浅海水声信道的时变特性,基于射线理论引入海洋参数——强度起伏参数Φ、不均匀度参数A,建立有效的时变多径信道模型,并采用Matlab工具进行仿真．仿真结果表明,该模型相比于确定性模型更容易理解、更真实．文中给出的模型和结论能够为实际通信系统中发射接收机深度等的选择和设计提供一定的参考和依据,有助于对水声信道的了解．     

A Variable-Rate Spread-Spectrum System for Underwater Acoustic Communications

A key research area in underwater acoustic (UWA) communication is the development of advanced modulation and detection schemes for improved performance and range-rate product. In this communication, we propose a variable-rate underwater data transmission system based on direct sequence spread spectrum (DSSS) and complementary code keying (CCK), particularly for shallow-water acoustic channels with severe multipath propagation. We provide a suboptimum receiver that consists of a bidirectional decision feedback equalizer (BiDFE) to cancel both postcursor and precursor intersymbol interference (ISI). We also develop iterative signal processing and time-reversal (TR) diversity processing to mitigate the effect of error propagation in BiDFE. We present performance analysis on bit error rate (BER) for different data rates. Our works show that this new variable-data-rate DSSS-CCK is a suitable candidate for UWA communications over varying channel conditions and distance.      

Spatial diversity equalization applied to underwater communications

Underwater acoustic digital communication is difficult because of the nature of the fading multipath channels. Digital signal processing, such as adaptive equalization, is known to greatly improve the communication data rate by limiting intersymbol interference (ISI). However, existing underwater acoustic equalization studies are limited to single-channel techniques, and spatial diversity processing is limited to selection or combining. In this paper, we design minimum mean-square error (MMSE) equalizers jointly among all spatial diversity channels. We call this spatial diversity equalization (SDE). Results are based on a very sparse vertical array in a midrange underwater acoustic channel. We study the effect of element number and placement, the length of the equalization filters, and linear feedforward versus nonlinear decision feedback algorithms. A suboptimum equalizer combiner (EC) is studied to alleviate the computational intensity of JCE. We first design the system for a known acoustic channel; later, some results are verified using adaptive algorithms. Results are presented both in terms of the mean-square error (MSE) and the probability of a symbol error. The latter is important as it is the ultimate interest for a digital communication system. We found that system performance improves rapidly with an increase in the number of spatial channels     

传感器测量衰减下的水下目标纯方位跟踪算法

为解决多传感器水下目标纯方位跟踪中的传感器测量衰减问题,建立水下目标静态多传感器纯方位跟踪模型,将传感器测量衰减建模为统计特性已知的随机变量,基于融合中心接收到的各水声传感器的原始测量值,设计了一种集中式状态估计器结构,利用最小方差方法推导出最优的集中式目标状态估计增益。通过算例仿真可以得出,所提出的算法能够在水声传感器不做机动的前提下跟踪目标,弥补了单个水声传感器观测性不足的缺点,对比传统的集中式Kalman估计器,具有更高的精度,能够有效解决传感器测量衰减问题。     

CSI feedback-based CS for underwater acoustic adaptive modulation OFDM system with channel prediction

In this paper, we investigate the performance of adaptive modulation （AM） orthogonal frequency division multiplexing （OFDM） system in underwater acoustic （UWA） communications. The aim is to solve the problem of large feedback overhead for channel state information （CSI） in every subcarrier. A novel CSI feedback scheme is proposed based on the theory of compressed sensing （CS）. We propose a feedback from the receiver that only feedback the sparse channel parameters. Additionally, prediction of the channel state is proposed every several symbols to realize the AM in practice. We describe a linear channel prediction algorithm which is used in adaptive transmission. This system has been tested in the real underwater acoustic channel. The linear channel prediction makes the AM transmission techniques more feasible for acoustic channel communications. The simulation and experiment show that significant improvements can be obtained both in bit error rate （BER） and throughput in the AM scheme compared with the fixed Quadrature Phase Shift Keying （QPSK） modulation scheme. Moreover, the performance with standard CS outperforms the Discrete Cosine Transform （DCT） method.     

An Iterative Equalization and Decoding Approach for Underwater Acoustic Communication

In this paper, we present an iterative approach for recovering information sent over a shallow underwater acoustic (UWA) communication channel. The procedure has three main tasks: estimation of channel model parameters (CMPs), channel equalization, and decoding. These tasks are performed cyclicly until the algorithm converges. Information bits are convolutionally encoded, punctured and permuted, mapped into quaternary phase-shift keying (QPSK) symbols, linearly modulated, and transmitted through a downward-refracting ocean waveguide. Training symbols are prepended to the transmitted sequence for initial estimation of CMPs. Our algorithm processes data from a single receive sensor. Data are received on a vertical array and the performance of the algorithm for each sensor in the array is examined. There is negligible Doppler spread in the received data. However, difference between transmitter and receiver clocks as well as slight motion of the receive array produce a nonnegligible compression of the received signals. Consequently, there is observable Doppler “shift.” Nonuniform resampling of the data produces time series we model as the output of a linear time-invariant system. Resampling and CMP estimation are done iteratively, in conjunction with equalization and decoding. The algorithm successfully processes the data to yield few or no information bit errors.      

Underwater Acoustic Communication Based on Pattern Time Delay Shift Coding Scheme

1 .Introduction Underwater acoustic (UWA) communicationis a fast developingfield,and its applicationis notlimitedto military affairs ,but is also extendinginto commercial fields .Catipovic (1990) ,Stojanovic(1996) and Kilfoyle and Baggeroer (2000) pointed…     

Improvement of Time-Reversal Communications Using Adaptive Channel Equalizers

The spatial and temporal focusing properties of time-reversal methods can be exploited for undersea acoustic communications. Spatial focusing mitigates channel fading and produces a high signal-to-noise ratio (SNR) at the intended receivers along with a low probability of interception elsewhere. While temporal focusing (compression) reduces significantly intersymbol interference (ISI), there always is some residual ISI depending upon the number of transmitters, their spatial distribution (spatial diversity), and the complexity of the channel. Moreover, a slight change in the environment over the two-way propagation interval introduces additional ISI. Using multilevel quadrature amplitude modulation (M-QAM) in shallow water, we demonstrate that the performance of time-reversal communications can be improved significantly by cascading the received time series with an adaptive channel equalizer to remove the residual ISI     

水下数据传输Turbo码译码系统的实现

为了在恶劣的水声信道中确保数据的可靠传输,采用性能优异的Turbo码,以6711DSP为核心处理单元构建译码系统。系统采用戈泽尔算法进行跳频的软解调,迭代的软输出维特比译码算法(SOVA)进行译码。系统经过实验室水池的试验,证实能保证译码的实时性及其在恶劣信道中数据传输的正确性,具有相当优异的性能。     

Phase-coherent digital communications for underwater acousticchannels

High-speed phase coherent communications in the ocean channel are made difficult by the combined effects of large Doppler fluctuations and extended, time-varying multipath. In order to account for these effects, we consider a receiver which performs optimal phase synchronization and channel equalization jointly. Since the intersymbol interference in some underwater acoustic channels spans several tens of symbol intervals, making the optimal maximum-likelihood receiver unacceptably complex, we use a suboptimal, but low complexity, decision feedback equalizer. The mean squared error multiparameter optimization results in an adaptive algorithm which is a combination of recursive least squares and second-order digital phase and delay-locked loops. The use of a fractionally spaced equalizer eliminates the need for explicit symbol delay tracking. The proposed algorithm is applied to experimental data from three types of underwater acoustic channels: long-range deep water, long-range shallow water, and short-range shallow water channels. The modulation techniques used are 4- and 8-PSK. The results indicate the feasibility of achieving power-efficient communications in these channels and demonstrate the ability to coherently combine multiple arrivals, thus exploiting the diversity inherent in multipath propagation     

MIMO Underwater Acoustic Communication in Shallow Water with Ice Cover

Although multiple-input multiple-output(MIMO) underwater acoustic(UWA) communication has been intensively investigated in the past years, existing works mainly focus on open-water environment. There is no work reporting MIMO acoustic communication in under-ice environment. This paper presents results from a recent MIMO acoustic communication experiment which was conducted in Bohai Gulf during winter. In this experiment, high frequency MIMO signals centered at 10 kHz were transmitted from a two-element source array to a four-element vertical receiving array at 1 km range. According to the received signal of different array elements, MIMO acoustic communication in under-ice environment suffers less effect from co-channel interference compared with that in open-water environment. In this paper, time reversal followed by a single channel decision feedback equalizer is used to process the experimental data. It is demonstrated that this simple receiver is capable of realizing robust performance using fewer hydrophones(i.e. 2) without the explicit use of complex co-channel interference cancelation algorithms, such as parallel interference cancelation or serial interference cancelation.