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.

Feedback strategies for iterative channel estimation in OFDM underwater acoustic communications

The extremely limited bandwidth in underwater acoustic communication makes channel estimation using fewer pilot symbols more challenging. Iterative channel estimation( ICE) can be used to refine channel estimation with limited number of pilots,by coupling the channel estimator with channel decoder. In this paper,various feedback strategies in ICE are discussed. The performance of a decision feedback based on the cost function is improved by modifying the design and another four feedback strategies are summarized,including hard/soft decision feedback and their threshold-controlled versions. Simulation results show that ICE can achieve impressive gains over the non-iterative receiver and the gains are more significant with fewer pilots. Furthermore,soft decision feedback outperforms hard decision feedback; while the feedback based on the cost function and soft decision feedback have quite close performance.

Precoding Based Channel Prediction for Underwater Acoustic OFDM

The life duration of underwater cooperative network has been the hot topic in recent years. And the problem of node energy consuming is the key technology to maintain the energy balance among all nodes. To ensure energy efficiency of some special nodes and obtain a longer lifetime of the underwater cooperative network, this paper focuses on adopting precoding strategy to preprocess the signal at the transmitter and simplify the receiver structure. Meanwhile, it takes into account the presence of Doppler shifts and long feedback transmission delay in an underwater acoustic communication system. Precoding technique is applied based on channel prediction to realize energy saving and improve system performance. Different precoding methods are compared. Simulated results and experimental results show that the proposed scheme has a better performance, and it can provide a simple receiver and realize energy saving for some special nodes in a cooperative communication.

Power optimization algorithm for OFDM underwater acoustic communication using adaptive channel estimation

An adaptive channel estimation algorithm for the channel length is proposed to construct a channel estimation model suitable for orthogonal frequency division multiplexing(OFDM)underwater acoustic communication signals for the dependence of traditional channel estimation algorithms on channel length information.This algorithm can be adopted to evaluate channel estimation quality in real time and to adaptively adjust the channel length of the channel estimation algorithm according to the evaluation result,which satisfies the need of accurate estimation of unknown underwater acoustic channels and communication application;based on the study on the relationship between the OFDM communication bit error rate and the subcarrier signal to noise ratio,a self-adjusting optimization scheme for OFDM subcarrier transmitting power is proposed,which realizes underwater communication with the low bit error rate through higher energy efficiency.The validity of the research content is verified through simulation and field experiments.

Frequency Diversity for OFDM Mobile Communication via Underwater Acoustic Channels

直角的频率部门 multiplexing (OFDM ) 的表演上的主要限制基于在水下声学(UWA ) 通讯是使副载波直角。在这份报纸，与各种各样的差异技术一起的 Doppler 评价和各自的赔偿技术为最好适合的基于 OFDM 的系统被商讨在水下无线信息交换。在实践，为活动通讯，调整并且变换器调节以便得到空间差异是极其困难的。就在 UWA 的相对低的连贯带宽而言，有 Doppler 赔偿功能的频率差异设计这里被详细描述。外场实验活动在水下声学的通讯(UWAC ) 与 0.17 bit/ 基于 OFDM 被执行(s 貇? ?? ? 髧 ??

Inter-Carrier Interference-Aware Sparse Time-Varying Underwater Acoustic Channel Estimation Based on Fast Reconstruction Algorithm

In this paper,a fast orthogonal matching pursuit(OMP)algorithm based on optimized iterative process is proposed for sparse time-varying underwater acoustic(UWA)channel estimation.The channel estimation consists of calculating amplitude,delay and Doppler scaling factor of each path using the received multi-path signal.This algorithm,called as OIP-FOMP,can reduce the computationally complexity of the traditional OMP algorithm and maintain accuracy in the presence of severe inter-carrier interference that exists in the time-varying UWA channels.In this algorithm,repeated inner product operations used in the OMP algorithm are removed by calculating the candidate path signature Hermitian inner product matrix in advance.Efficient QR decomposition is used to estimate the path amplitude,and the problem of reconstruction failure caused by inaccurate delay selection is avoided by optimizing the Hermitian inner product matrix.Theoretical analysis and simulation results show that the computational complexity of the OIP-FOMP algorithm is reduced by about 1/4 compared with the OMP algorithm,without any loss of accuracy.

Null subcarriers based Doppler scale estimation with polynomial interpolation for multicarrier communication over ultrawideband underwater acoustic channels

This paper addresses the extremal problem of the null subcarriers based Doppler scale estimation in underwater acoustic （UWA） orthogonal frequency division multiplexing （OFDM） communication. The cost function constructed of the total energy of null subcarriers through discrete Fourier transform （DFT） is proposed. The frequencies of null subcarriers are identified from non-uniform Doppler shift at each tentative scaling factor. Then it is proved that the cost function can be fitted as a quadratic polynomial near the global minimum. An accurate Doppler scale estimation is achieved by the location of the global scarifying precision and increasing the computation minimum through polynomial interpolation, without complexity. A shallow water experiment is conducted to demonstrate the performance of the proposed method. Excellent performance results are obtained in ultrawideband UWA channels with a relative bandwidth of 67%, when the transmitter and the receiver are moving at a relative speed of 5 kn, which validates the proposed method.

基于排序码本的水声自适应OFDM通信中信道状态信息反馈研究

水声(UWA)信道时延扩展大等特点导致信道频响(CFR)快衰落,水声通信(UWAC)技术发展受到挑战。发射端获取有效可靠的信道状态信息(CSI)是自适应通信的前提,针对水声自适应正交频分复用(OFDM)通信的需求,该文提出基于排序码本的信道状态信息分组排序拟合反馈算法(CSI-GSFF),包括分组、排序、数据拟合3个步骤。该算法首先将相邻导频子载波分组,以组为反馈单元;然后对各组内的导频子载波按照信道增益值进行排序,以减轻水声信道频响快衰落造成的反馈开销大等不利影响;最后进行多项式拟合,排序操作有效地降低了拟合阶数。通过实测海试时变信道数据仿真,结果表明,该文提出的信道状态信息反馈算法能够基本达到完美信道状态信息情形下的水声自适应OFDM通信系统误码率性能,同时可以有效地减少反馈开销。

OFDM水声通信多普勒估计与跟踪方法

水声通信中传统宽带多普勒估计方法难以准确跟踪时变多普勒因子,从而导致正交频分复用(Orthogonal Frequency Division Multiplexing,OFDM)在变速运动通信场景中补偿性能不佳。针对该问题,文章提出了一种基于空载波的多普勒估计与跟踪算法。首先对三频信号做线性调频Z变换(Chirp-Z Transform,CZT)得到多普勒先验值,然后利用OFDM符号中的空载波结合载波频偏(Carrier Frequency Offset,CFO)搜索补偿技术,把估计的最优CFO值转换为宽带多普勒因子,进而计算当前符号的加速度并预测下一符号的速度。通过更新加速度对预测值进行修正,实现每个OFDM符号的多普勒估计。数值仿真和湖试结果表明,文中算法不仅能有效跟踪多普勒的变化,在匀速和变速条件下都有较好的补偿性能,而且对帧结构设计要求低,对先验误差不敏感,有利于水声通信系统的工程实现。

基于深度学习的OFDM半相干水声通信方法

针对正交频分复用(Orthogonal Frequency Division Multiplexing,OFDM)水声通信中常用的相干和非相干通信分别面临的对多普勒敏感和频谱效率低的问题,提出一种高阶幅度键控调制的半相干通信技术,将OFDM符号时频帧结构中全部频点采用高阶幅度键控调制方式,并利用信号幅度信息完成半相干信道估计。通过两种基于深度学习的算法优化半相干信道估计这一非线性过程,较非相干通信有效提高了频谱效率,较一定信噪比下的相干通信提高了鲁棒性,降低了误比特率和系统复杂度,并利用元学习算法降低深度学习算法对训练数据的依赖。最后,提取海试信道数据,完成OFDM半相干水声通信系统仿真,验证了所提方法在频谱效率和系统误比特率性能方面较非相干和相干通信的优势,当信道长度改变时,基于元学习的算法依然可以获得较好的性能。

基于OFDM和SC-FDE技术的水声通信系统研究

在介绍正交额分复用(OFDM)技术和单载波频域均衡(SC-FDE)技术原理的基础上,分析了两种技术的特点。以克服多途干扰、实现水声通信的高速率传输为目的,研究了在现有水声信道模型中两种技术的可靠性、有效性及抗多径能力。仿真结果表明,它们均具有较强的抗多径干扰能力。正交额分复用和单载波频域均衡技术在现代高速水声通信中应具有很好的发展前景。

基于子载波间干扰深度估计的MIMO-OFDM水声通信接收机

多输入多输出正交频分复用(MIMO-OFDM)水声通信系统中,由于子载波间干扰(ICI)对信号的影响程度未知,导致接收处理时干扰消除不完全或计算复杂度高。针对这一问题,该文提出一种迭代的基于子载波间干扰深度估计的MIMO-OFDM接收机。该接收机使用导频频域相关对每个发射信号的子载波间干扰深度进行估计,信道估计时利用估计出的干扰深度重建各个信道的频域矩阵,避免对不同信道选择相同的干扰深度,在自适应信道变化的同时降低了计算复杂度。此外,将判决反馈均衡引入MIMO-OFDM水声通信系统,利用已均衡出的符号信息消除子载波间干扰。仿真结果表明,该接收机相比于干扰深度渐进的接收机,译码成功所需的时间更短。

A criterion based adaptive RSIC scheme in underwater communication

Multi-access interference(MAI)is the main source limiting the capacity and quality of the multiple-input multipleoutput orthogonal frequency division multiplexing(MIMO-OFDM)system which fulfills the demand of high-speed transmission rate and high quality of service for future underwater acoustic(UWA)communication.Therefore,multi-user detection(MUD)is needed at the receiver of the MIMO-OFDM system to suppress the effect of MAI.In this research,MUD is achieved by using a criterion based adaptive recursive successive interference cancellation(RSIC)scheme at the receiver of a MIMO-OFDM system whose transceiver model in underwater communication is implemented by using the Bellhop simulation system.The proposed scheme estimates and eliminates the MAI through user signal detection and subtraction from received signals at the receiver of the MIMO-OFDM system in underwater environment.The bit error rate(BER)performance of the proposed scheme is analyzed by using weight filtering and weight selection criteria.By Matlab simulation,it is shown that the BER performance of the proposed scheme outperforms the conventional matched filter(MF)detector,the adaptive successive interference cancellation(SIC)scheme,and the adaptive RSIC scheme in the UWA network.

Denoising enabled channel estimation for underwater acoustic communications:A sparsity-aware model-driven learning approach

It has always been difficult to achieve accurate information of the channel for underwater acoustic communications because of the severe underwater propagation conditions,including frequency-selective property,high relative mobility,long propagation latency,and intensive ambient noise,etc.To this end,a deep unfolding neural network based approach is proposed,in which multiple layers of the network mimic the iterations of the classical iterative sparse approximation algorithm to extract the inherent sparse features of the channel by exploiting deep learning,and a scheme based on the Sparsity-Aware DNN(SA-DNN)for UAC estimation is proposed to improve the estimation accuracy.Moreover,we propose a Denoising Sparsity-Aware DNN(DeSA-DNN)based enhanced method that integrates a denoising CNN module in the sparsity-aware deep network,so that the degradation brought by intensive ambient noise could be eliminated and the estimation accuracy can be further improved.Simulation results demonstrate that the performance of the proposed schemes is superior to the state-of-the-art compressed sensing based and iterative sparse recovery schems in the aspects of channel recovery precision,pilot overhead,and robustness,particularly under unideal circumstances of intensive ambient noise or inadequate measurement pilots.

针对浅海水声通信的极化码构造与应用研究

为了实现浅海环境中高速率和高可靠通信,研究了极化码编译码技术在浅海水声通信中的性能。针对基于射线声学理论建立的时不变、准静止和时变3种浅海水声信道模型,采用蒙特卡罗构造算法完成相应极化码的构造,并分别与信道极化和信道退化构造算法、基对称扩展极化权重构造算法进行了复杂度和性能比较。将构造的极化码作为文中基于正交频分复用的水声通信系统的信道编码方案,译码方案使用循环冗余校验辅助的串行抵消列表译码算法。通过仿真模拟分析了上述3种信道中极化码的性能,并与码长和码率相同的低密度奇偶校验码的性能进行对比分析;结果显示在这3种信道中,在关注的信噪比范围内极化码相对于低密度奇偶校验码约有0.5 dB~1.2 dB的增益。3种信道仿真对比结果表明,基于信道构造编码的极化码相比低密度奇偶校验码在恶劣的信道环境中有更好的增益效果,且极化码有更低的编译码复杂度,证明了极化码在能量和资源受限的浅海水声通信中具有广阔的应用前景。

基于OFDM信号的自适应水声信道估计算法

建立适用于OFDM水声通信信号的信道估计模型,对MP算法进行改进,引入路径门限调整机制克服虚假路径造成的不良影响,通过重要路径权系数的迭代修正降低非正交性引入的估计误差,以较小计算量取得了与OMP算法相当的估计精度;针对传统信道估计算法对信道长度信息的依赖问题,提出了一种信道长度自适应信道估计算法,该算法能够对信道估计质量进行实时评价,并根据评价结果实现信道估计算法预估信道长度的自适应调整,满足未知水声信道精确估计及通信应用的需要;基于OFDM导频元素个数与信道估计效果的关系研究,提出了OFDM导频序列自调整的通信方案,以较小的带宽损失保证了可靠的水声通信。通过仿真和实地试验,验证了该文研究内容的有效性。

OFDM水声通信中基于压缩传感的稀疏信道估计

针对正交频分复用(orthogonal frequency division multiplexing,OFDM)水声通信中常规的最小均方(least square,LS)信道估计方法需要大量训练导频且得不到较高估计精度的问题,提出了一种基于压缩传感原理的OFDM稀疏水声信道估计方法。该方法首先以正交短时傅里叶基构成的训练波形为OFDM的导频来"感知"信道,然后利用压缩传感技术的稀疏重构算法来对信道进行重构。基于实测水声信道的仿真结果表明,在相同估计精度前提下,基于压缩传感的信道估计方法较常规的LS算法所需训练导频数得到大幅度减小,传输效率得以提高,且对噪声的鲁棒性增强,较好地适应了双扩展稀疏水声信道,尤其适用于动平台OFDM水声通信系统。

M元扩频OFDM水声通信新方法

扩频水声通信能够抗信道衰落、多径干扰,具有传输距离远、可靠性高、被截获性低的优点。然而,水声通信可用带宽很窄,导致其数据率低。文章在伪随机序列扩频水声通信和OFDM水声通信研究及湖上成功实验的基础上,提出了一种基于M元伪随机序列组和OFDM技术的新型扩频OFDM(MSS-OFDM)水声通信方法。该方法能使得扩频水声通信数据率提高2.(log2M).(log2Q)倍。从理论上分析了M元扩频OFDM在高斯白噪声信道(AWGN)下的误码率性能,并通过仿真验证了其较强的稳健性。利用湖试测量得到的多径信道参数模型,分析比较了OFDM、SS-OFDM以及MSS-OFDM的水声通信误码率性能,结果表明:M元扩频OFDM具有双重抗多径干扰的优点,即使在没有保护间隔的情况下,也能获得较好的通信效果;由于采用了伪随机序列组,该方法也可用于水声网络通信。

Turbo码在水声OFDM通信中的应用研究

为了增强高速水声通信中信息传输的可靠性,采用了性能优越的Turbo码和OFDM相结合的方法,并与传统的卷积码进行了性能比较.仿真结果表明,在水声通信可以接受的信噪比范围内,采用Turbo码的误码性能明显优于无信道编码和卷积编码;在带宽利用率相同时使用该方案的水声通信系统性能优于无信道编码和卷积码.因此,把Turbo码与OFDM相结合的传输体制可以明显提高水声通信系统的传输速率和可靠性,从而在水声通信中具有良好的应用前景.

消除冗余循环前缀的水声信道OFDM频域均衡算法

针对OFDM传统频域均衡算法依赖较长冗余循环前缀,造成水声信道利用率下降的问题,依据OFDM的调制解调原理,在对水声信道多径效应造成影响进行数学建模的基础上,引入多级缓冲机制和判决反馈机制,提出了新型的判决反馈OFDM频域均衡算法。对算法计算量进行了简化,并给出均衡器阶数自适应选择方案。通过仿真和水池实验,证明新算法可以在完全没有循环前缀参与情况下,实现对多径效应的有效补偿,保证了有限水声信道带宽条件下的高速、低误码率的可靠通信。