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.     

Pilot design and doubly-selective channel estimation for faster-than-Nyquist signaling

Being capable of enhancing the spectral efficiency (SE), faster-than-Nyquist (FTN) signaling is a promising approach for wireless communication systems. This paper investigates the doubly-selective (i.e., time- and frequency-selective) channel estimation and data detection of FTN signaling. We consider the intersymbol interference (ISI) resulting from both the FTN signaling and the frequency-selective channel and adopt an efficient frame structure with reduced overhead. We propose a novel channel estimation technique of FTN signaling based on the least sum of squared errors (LSSE) approach to estimate the complex channel coefficients at the pilot locations within the frame. In particular, we find the optimal pilot sequence that minimizes the mean square error (MSE) of the channel estimation. To address the time-selective nature of the channel, we use a low-complexity linear interpolation to track the complex channel coefficients at the data symbols locations within the frame. To detect the data symbols of FTN signaling, we adopt a turbo equalization technique based on a linear soft-input soft-output (SISO) minimum mean square error (MMSE) equalizer. Simulation results show that the MSE of the proposed FTN signaling channel estimation employing the designed optimal pilot sequence is lower than its counterpart designed for conventional Nyquist transmission. The bit error rate (BER) of the FTN signaling employing the proposed optimal pilot sequence shows improvement compared to the FTN signaling employing the conventional Nyquist pilot sequence. Additionally, for the same SE, the proposed FTN signaling channel estimation employing the designed optimal pilot sequence shows better performance when compared to competing techniques from the literature.     

水声通信加权反馈双向Turb均衡器

为了提升自适应双向Turbo均衡器的收敛速度及降低误比特率,提出了采用加权反馈的双向Turbo均衡算法。首先在单个均衡器反馈输入中采用后验均值与先验均值混合的反馈方案,有效提升一轮迭代中均衡器输出的准确性;其次通过后验均值与先验均值的加权合并作为另一均衡器反馈的非因果项输入,在提升反馈输入准确性的同时提升了数据的利用率;最后在权值迭代中采用优化的比例归一化最小均方算法,提升训练阶段均衡器收敛速度。千岛湖试验中,在同样3.75 kbps通信速率的情况下,该方法误比特率仅为传统双向Turbo均衡器的1/3。仿真和试验数据表明,均衡器要达到同样的误比特率,本方法所需迭代轮数更少,在时变信道中系统稳定性更好,误比特率更低,提升了水声通信效率。      

Signal processing for high speed underwater acoustic transmission of image

A signal processing method for high-speed underwater acoustic transmission of image is presented. It has two parts. Part 1 introduces signal processing for underwater acoustic coherent communication. Part 1 includes 3 technical points. （1） Doppler shift compensation. Chirp signals are inserted between data packages. A correlation process between two copy correlation functions gives more accurate estimation of the mean Doppler shift. Then it could be compensated by resampling the data. In adaptive decision feedback equalizer （DFE） an adaptive phase compensator with fast self-optimized least mean square （FOLMS） adaptation algorithm is utilized resulting in better motion tolerance than compensators with 2nd order Phase-Lock Loop algorithm. The performance of the combination of mean Doppler shift compensation and adaptive phase compensator is quite good. （2） A diversity combiner （DC） used in advance of equalizer. Both combiner and adaptive DFE are based on FOLMS adaptation algorithm. This results in reduced computation complexity and better performance. （3） Cascaded equalizer and Turbo-Trellis Coded Modulation （TCM） decoder and the iteration algorithm. A new bitsymbol converter based on Soft Output Viterbi Algorithm （SOVA） is studied. Comparing with the traditional decision, coding and mapping algorithm, the new converter can reduce Bit Error Rate（BER） by nearly 2 orders. Part 2 is mainly around a robust image compression algorithm. Based on Discrete wavelet transform and fixed length coding, a robust compression algorithm for acoustic image is studied. The algorithm includes 4 technical points. （1） Utilizes CDF9/7 wavelet bases to transform the images. （2） Analyses the energy distribution of subband coefficients. Suitable transformation layer number is 3. （3） Applies different quantization steps to different subbands in accordance with their energy distribution. （4） Uses fixed length coding to prevent error propagation. The results show the algorithm achieves a balance among image quality, compression rate, and most important, robustness to BER. The compressed bit rate of gray scale acoustic image is 0.85 bit/pixel. Image quality remains good when BER is lower than 10^-3. There are some small dirty points when BER rises to 10^-2. Based on the signal processing techniques above mentioned, an underwater acoustic commumcation system is built. Its operational frequency band is （7.5-12.5） kHz. Its receiving array is an 8 elements uniform linear array. QPSK and 8PSK modulation and iteration algorithm for cascaded equalizer and 1-Turbo-TCM decoder based on hard SOVA are used. The system has been tested in Qiandao Lake. Low BER is achieved in 5.5 km range when data rate is 10 kbps. One gray scale image can be transmitted in 7 s. The product of its communication distance and data rate is 55 km kbps.     

Adaptive RAKE receiver in chaos based pilot-added DS-CDMA system

This paper presents the theoretical analysis of adaptive multiuser RAKE receiver scheme in frequency selective fading channel for direct-sequence code division multiple access (DS-CDMA) system. Least mean square (LMS) algorithm is used to estimate the channel coefficients. Chaotic sequences are used as spreading sequence and corresponding bit error rate (BER) in closed form is derived for imperfect channel estimation conditions. Performances of chaotic sequences are compared with pseudorandom noise (PN) sequences. Under perfect synchronization assumption, various simulation results are shown to investigate the performance of the proposed system.     

Widely linear equalization for IQ imbalance contaminated multicarrier systems

In a multicarrier modulated (MCM) wireless communication system, the received bandpass signal is downconverted to the baseband signal for ease of receive processing. During downconversion, a slight mismatch in the amplitude and phase of locally generated sinusoidal signal in the In-Phase and Quadrature (IQ) branches of downconverter results in IQ imbalance of the baseband signal. The IQ imbalance leads to mirror interference between subcarriers of an MCM system and degrades the performance. To compensate for the effects of IQ imbalance, this paper presents widely linear minimum mean square error (WL-MMSE) based equalization technique and compares it with the traditionally used linear minimum mean square error (L-MMSE) based equalization technique. A performance comparison between WL-MMSE and L-MMSE based estimation techniques in terms of mean square error (MSE) and bit error rate (BER) suggests that the former outperforms the latter in the presence of IQ imbalance.     

混沌通信系统中非线性信道的自适应组合神经网络均衡

针对混沌通信系统的非线性信道干扰问题,基于混沌信号重构理论和函数型连接神经网络理论,提出了一种横向滤波器与函数型连接神经网络组合(combination of transversal filter and functional link neural network,CFFLNN)的自适应非线性信道均衡器,并给出基于低复杂度归一化最小均方(NLMS)的自适应算法,并对该均衡器的稳定性以及收敛条件进行了分析.该非线性自适应均衡器充分利用了横向滤波器的快速收敛,以及函数型连接神经网络通过增大输入空间提高非线性逼近能力的特点,进一步提高均衡器的收敛速度和降低稳态误差.仿真研究表明：所提出的非线性自适应均衡器能够有效地消除线性和非线性信道干扰,均衡器输出信号能反映出混沌信号的特性,具有良好的抗干扰性能;且该均衡器的结构简单,收敛稳定性较好,易于工程实现. 关键词： 非线性信道 自适应均衡器 混沌吸引子 神经网络     

Joint passive-phase conjugation with adaptive multichannel combining for coherent underwater acoustic communications

This paper presents a receiver structure which exploits spatial diversity by adaptive multichannel combining, which improves the performance of passive time reversal communications realized by passive-phase conjugation (PPC). PPC processing achieves pulse compression for the time delayed arrivals at the receiver, and this property is used for coherent communications to reduce the computational load. The presented structure takes advantage of pulse compression and performs adaptive multichannel combining, where the number of taps for adaptive multichannel processing is significantly reduced in order to decrease the computational load. With a previous output mean square error (MSE), the adaptive combining minimizes current output MSE, where spatial diversity is exploited by the adaptive combining. This structure improves performance of the passive time reversal approach, even though the taps for combining span one symbol interval. The performance improvement is demonstrated by a set of real data collected in a recent sea experiment, which was conducted in a range dependent acoustic channel over a range of 4 km.     

Indoor positioning modeling by visible light communication and imaging

This letter presents a model of an indoor light positioning system(LPS) based on white LEDs and a camera.The position of an LPS receiver is determined through both its relative position to LEDs according to their images captured by the camera and LEDs' absolute position information in the navigation frame, obtained through a visible light communication(VLC) link. The error performance of the proposed LPS is analyzed.The mean error and mean square error(MSE) of estimated receiver position using least squares(LS) and weighted least squares(WLS) estimators are both derived in the presence of non-uniform measurement bias and white Gaussian noise. The effects of communication data rate on the positioning accuracy are also studied through BER performance.     

Performance analysis of adaptive equalization for coherent acoustic communications in the time-varying ocean environment

Equations are derived for analyzing the performance of channel estimate based equalizers. The performance is characterized in terms of the mean squared soft decision error (sigma2(s)) of each equalizer. This error is decomposed into two components. These are the minimum achievable error (sigma2(0)) and the excess error (sigma2(e)). The former is the soft decision error that would be realized by the equalizer if the filter coefficient calculation were based upon perfect knowledge of the channel impulse response and statistics of the interfering noise field. The latter is the additional soft decision error that is realized due to errors in the estimates of these channel parameters. These expressions accurately predict the equalizer errors observed in the processing of experimental data by a channel estimate based decision feedback equalizer (DFE) and a passive time-reversal equalizer. Further expressions are presented that allow equalizer performance to be predicted given the scattering function of the acoustic channel. The analysis using these expressions yields insights into the features of surface scattering that most significantly impact equalizer performance in shallow water environments and motivates the implementation of a DFE that is robust with respect to channel estimation errors.     

混沌通信系统中非线性信道的自适应神经Legendre正交多项式均衡

针对混沌通信系统中非线性信道干扰问题，基于混沌信号重构理论和Legendre正交多项式结构，提出了一种自适应神经Legendre正交多项式信道均衡器，并给出相应的归一化最小均方算法. 仿真研究表明：所提出的自适应神经Legendre正交多项式信道均衡器能有效地消除线性和非线性信道干扰，均衡器输出信号能反映出混沌信号的特性，具有良好的抗干扰性能.该均衡器的结构简单，权系数参数较少，收敛稳定性较好. 关键词： Legendre 正交多项式 信道均衡 混沌吸引子 神经网络     

Closed-form analysis for indirect learning digital pre-distorter for wideband wireless systems

Indirect learning architecture (ILA) for digital pre-distortion (DPD) is commonly used to linearize power amplifiers (PA). To the author’s best knowledge, most of the DPD results in the literature obtain the matrix form of the least-square solution in order to get the DPD coefficients numerically. There exists no explicit closed-form for these coefficients that can be used as plug-and-play in simulations, or used for further closed-form analysis of important measures such as signal-to-noise ratio (SNR) and mean square error (MSE), bit-error rate (BER), …etc. In this paper, we analyze the ILA-DPD system for general memory-polynomial PA models. We provide a closed-form solution for the DPD coefficients. We first present the analytical methodology for deriving the mathematical expressions for each DPD coefficient and then introduce an open-access code that generates the DPD coefficients in symbolic form that is used to mathematically model the DPD. We consider case studies for PA and show that the analytical DPD solution matches the Monte Carlo simulations. Moreover, we also provide a closed-form solution for the iterative adaptive ILA-DPD. Our analysis shows that in the case of a large training block length the non-iterative DPD achieves approximately the same performance as an iterative DPD with a shorter training block length. System impairments are also considered, e.g. the thermal noise and the quantization noise in analog–digital conversion (ADC). We derive the normalized mean square error (NMSE) for the transmit chain in the presence of these impairments. The NMSE expression is verified through numerical simulations.     

水声通信系统中双向turbo均衡算法

提出了一种水声通信系统中直接自适应双向turbo均衡算法。摒弃了信道估计步骤,采用基于直接自适应的turbo均衡器,并利用内嵌数字锁相环的判决反馈均衡器结构跟踪时变信道,采用最速优化算法自适应调整迭代步长,使得收敛速度和算法性能得到很好折中。此外,利用最小均方误差准则,得到最优权重因子,对正向与反向turbo均衡结果加权求和,消除误差传播效应。仿真和湖上实验验证了方法的正确性,双向均衡的性能优于单向均衡。湖上实验结果表明,基于直接自适应算法相比于基于信道估计的算法,对时变信道不敏感,能获得更低的误比特率。      

水声通信系统中双向turbo均衡算法研究（英文）

A direct-adaptation based bidirectional turbo equalizer for underwater acoustic communications is proposed.Abandoning the channel estimation process,the direct-adaptation based turbo equalizer embedded with digital phase-locked loop is adopted to track time-varying channel.The fast self-optimized algorithm is used to adjust the step size,thus a good tradeoff between the convergence speed and performance has been made.Furthermore,by minimizing the mean squared error,an optimal weighting factor is derived to exploit bidirectional diversity gain.The forward turbo equalizer is combined with the backward turbo equalizer to eliminate error propagation effect.Simulated and experimental results demonstrate that the bidirectional turbo equalizer outperforms the single directional one.It can be seen from the experimental results that,compared with the channel estimation based algorithm,the direct-adaptation based algorithm is less sensitive to the time-varying channel and has a lower bit error rate.     

ECM and SAGE based joint estimation of timing and frequency offset for DMIMO–OFDM system

Distributed multiple-input multiple-output (DMIMO) technology is a key enabler of coverage extension and enhancement of link reliability in wireless networks through distributed spatial diversity. DMIMO employs classic relay channels in between the source and the destination to opportunistically form a virtual antenna array (VAA) for emulating cooperative diversity. Use of multiple antennas at the relays further increases capacity and reliability of the relay–destination channel through multiplexing and diversity of MIMO antennas respectively. In such network, the signal received at the destination is characterized by multiple timing offsets (MTO) due to different propagation delay and multiple carrier frequency offsets (MCFO) due to independent oscillators of the relays. Hence, synchronization becomes a crucial issue in DMIMO in order to realize the distributed coherence. In this paper, we address joint estimation of MCFO and MTO in DMIMO orthogonal frequency division multiplexing (OFDM) with MIMO configuration at the relays for estimate-and-forward (EF) relaying protocol. Two iterative algorithms, based on expectation conditional maximization (ECM) and space alternating generalized expectation–maximization (SAGE) are proposed for joint estimation in presence of inter carrier interference (ICI). The robustness of both the estimators to ICI is evaluated by mathematical analysis and supported by extensive simulations. The performance of the proposed estimators is assessed in terms of mean square error (MSE) and bit error rate (BER). The theoretical Cramer–Rao lower bound (CRLB) of estimator error variance is also derived.     

Experimental assessment of a multicarrier underwater acoustic communication system

This paper presents a multicarrier communication system which transmits information on independent subcarriers to achieve an increased data rate. For this system, a passive-phase conjugation (PPC) based receiver structure is assessed by processing data collected in sea trials. Based on temporal diversity (pulse compression) exploited by PPC processing, an adaptive multichannel decision feedback equalizer is used to remove intersymbol interference, where spatial diversity is exploited by adaptive multichannel combination. The digital phase-locked loop (DPLL) technique is implemented for carrier-phase tracking. In the scenario of low input signal-to-noise ratios (SNRs), the receiver structure achieved superior performance using a common DPLL. In a depth-fluctuated environment, two sea experiments were conducted over ranges of 2 km and 4 km, respectively, and this communication system was assessed with a data rate of 4 kbps. In terms of mean square error, output SNR and bit error rate, this receiver structure has demonstrated its performance for the multicarrier communication system.     

Deep-BiGRU based channel estimation scheme for MIMO–FBMC systems

Deep Learning (DL)–based wireless communication systems have the potential to improve the conventional functions and current architecture of communication systems. In this paper, we propose a novel DL-based channel estimation scheme for multiple-input multiple-output filter bank multicarrier with offset quadrature amplitude modulation (MIMO-FBMC/OQAM) systems called deep bidirectional gated-recurrent unit (BiGRU) scheme. This scheme can easily be applied to a single-input single-output (SISO) system. The proposed scheme is divided into two stages: offline and online. The network is first trained in the offline stage. The prediction of channel information and estimation of the channel matrix using the trained network is then performed in the online stage. The simulation results in terms of the normalized mean square error (NMSE) and bit error rate (BER) demonstrate that, under different time-varying channel models, the proposed DL scheme significantly improves the channel estimation performance of FBMC for single and multiple antennas compared to conventional interference approximation method (IAM) channel estimation methods.     

偏振复用光纤通信系统色散均衡器及算法的研究

设计了一种适用于偏振复用相干解调光纤通信系统的色散均衡器,用于补偿信道传输的色散损伤。该均衡器采用半码元间隔的蝶形有限脉冲响应滤波器结构,与此结构配合的自适应算法分别采用最小均方算法和递归最小二乘算法。通过仿真实验,分析了两种算法对残留色度色散和偏振模色散的补偿容限。仿真结果表明,递归最小二乘算法的补偿效果优于最小均方算法,它可以同时补偿1760ps/nm的残留色度色散和104.9ps偏振模色散引起的差分群时延,比同等条件的最小均方算法提升性能2.23dB。     

Least mean square error difference minimum criterion for adaptive chaotic noise canceller

The least mean square error difference (LMS-ED) minimum criterion for an adaptive chaotic noise canceller is proposed in this paper. Different from traditional least mean square error minimum criterion in which the error is uncorrelated with the input vector, the proposed LMS-ED minimum criterion tries to minimize the correlation between the error difference and input vector difference. The novel adaptive LMS-ED algorithm is then derived to update the weights of adaptive noise canceller. A comparison between cancelling performances of adaptive least mean square (LMS), normalized LMS (NLMS) and proposed LMS-ED algorithms is simulated by using three kinds of chaotic noises. The simulation results clearly show that the proposed algorithm outperforms the LMS and NLMS algorithms in achieving small values of steady-state excess mean square error. Moreover, the computational complexity of the proposed LMS-ED algorithm is the same as that of the standard LMS algorithms.     

Improved partial response maximum likelihood method combining modulation code for signal waveform modulation multi-level disc

In this paper, we describe an improved adaptive partial response maximum likelihood （PRML） method combining modulation code tbr signal waveform modulation multi-level disc. This improved adaptive PRML method employs partial response equalizer and adaptive viterbi detector combining modulation code. Compared with the traditional adaptive PRML detector, the improved PRML detector additionally employs illogical sequence detector and corrector. Illogical sequence detector and corrector can aw）id the appearance of illogical sequences effectively, which do not follow the law of modulation code for signal waveform modulation multi-level disc, and obtain the correct sequences. We implement the improved PRML detector using a DSP and an FPGA chip. The experimental results show good performance. The higher efficient and lower complexity can be obtained by using the improved PRML method than by using the previous PRML method. Meanwhile, resource utilization of the improved PRML detector is not changed, but the bit error rate （BER） is reduced by more than 20%.