Blind Equalization Based on RLS Algorithm Using Adaptive Forgetting Factor for Underwater Acoustic Channel

Blind equalization based on adaptive forgetting factor, recursive least squares （RLS） with constant modulus algorithm （CMA）, is investigated. The cost function of CMA is simplified to meet the second norm form to ensure the stability of RLS-CMA, and thus an improved RLS-CMA （RLS-SCMA） is established. To further improve its performance, a new adaptive forgetting factor RLS-SCMA （ARLS-SCMA） is proposed. In ARLS-SCMA, the forgetting factor varies with the output error of the blind equalizer during the iterative process, which leads to a faster convergence rate and a smaller steady-state error. The simulation results prove the effectiveness under the condition of the underwater acoustic channel.

Self-adjusting decision feedback equalizer for variational underwater acoustic channel environments

Aimed at the abominable influences to blind equaliza-tion algorithms caused by complex time-space variability existing in underwater acoustic channels, a new self-adjusting decision feedback equalization （DFE） algorithm adapting to different under-water acoustic channel environments is proposed by changing its central tap position. Besides, this new algorithm behaves faster convergence speed based on the analysis of equalizers’ working rules, which is more suitable to implement communications in dif-ferent unknown channels. Corresponding results and conclusions are validated by simulations and spot experiments.

Modeling and Simulation of P-Aloha,CSMA /CA and MACAW Protocols for Underwater Acoustic Channel

Medium access control( MAC) protocol of underwater acoustic communication network is a key technology for underwater acoustic networks( UANs). Most of the MAC protocols for wireless terrestrial communication networks have been designed with negligible propagation delay. If it is deployed directly in an underwater environment,the UANs will perform inefficiently. In this paper,the characteristics of underwater acoustic channel are modeled and simulated by using the OPNET simulation tool,which are the speed of sound, propagation loss, and four sources for ambient noise: the turbulence,shipping,wind driven waves and thermal noise. The performance of pure Aloha( P-Aloha),carrier sense multiple access with collision avoidance( CSMA / CA) and multiple access collision avoidance for wireless local area network( MACAW) protocols in underwater acoustic channel environment are evaluated. The different performance of protocols in underwater environment is compared in the simulation.

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.

Blind equalization of underwater acoustic channel using a combined constant modulus algorithm

A kind of Combined Constant Modulus Algorithm (CCMA) is presented to compensate the defects of the Constant Modulus Algorithm (CMA) and the Sign Error CMA (SECMA). And CCMA is applied to the equalization of the underwater acoustic channel (UWAC). Based on the decision of the equalizer’s output, its iteration process switches between

Correlation equalizer and its simulation for underwater acoustic channels

A robust correlation equalizer is presented to resolve the equalization divergence,which is caused by the distribution of channel response function's zero points outside the unit circle. The equalizer is robust except that the channel response function has zero points just on the wht circle. Noncausal two-side prediction is also proposed. Based on the prediction and FFT the transversal form of the correlation equdrier and the fast algorithIn are developed. The simulation results of the correlation equallzer of transversal form are given.

基于注意力机制的LSTM时变水声信道深度学习预测

This paper investigates the channel prediction algorithm of the time-varying channels in underwater acoustic(UWA)communication systems using the long short-term memory(LSTM)model with the attention mechanism.AttLstmPreNet is a deep learning model that combines an attention mechanism with LSTM-type models to capture temporal information with different scales from historical UWA channels.The attention mechanism is used to capture sparsity in the time-delay scales and coherence in the gep-time scale under the LSTM framework.The soft attention mechanism is introduced before the LSTM to support the model to focus on the features of input sequences and help improve the learning capacity of the proposed model.The performance of the proposed model is validated using different simulation time-varying UWA channels.Compared with the adaptive channel predictors and the plain LSTM model,the proposed model is better in terms of channel prediction accuracy.

Signal processing for noncoherent underwater acoustic communication approaching channel capacity

Noncoherent underwater acoustic communication channel in adverse conditions is modeled as a phase-random Rayleigh fading channel,and its capacity curve is derived.To approach the channel capacity curve,the concatenated code of the nonbinary LDPC code and the constant weight code is proposed for noncoherent communication which can late be iteratively decoded in the probability domain.Without information of channel amplitude or phase in the receiver,statistic parameters of the respective signal and noise bins were estimated based on the moment estimation method,the posterior probabilities of the constant weight code words were further calculated,and the nonbinary LDPC code was decoded with the nonbinary factor graph algorithm.It is verified by simulations that by utilizing the proposed concatenated code and its processing algorithm,gap to channel capacity curve is reduced by 3 dB when compared to the existing method.Underwater communication experiments were carried out in both deep ocean（vertical communication,5 km）and shallow lake（horizontal communication,near 3 km,delay spread larger than 50 ms）,in which the signal frequency band was 6 kHz to10 kHz,and the data transmission rate Was 357 bps.The proposed scheme can work properly in both experiments with a signal-to-noise ratio threshold of 2 dB.The performance of the proposed algorithm Was well verified by the experiments.

Underwater acoustic multipath sparse channel estimation via gridless relevance vector machine method

In the scenario of underwater acoustic sparse channel estimation with training sequences,grid points in the measuring matrix are caused by discretizing procedure.Estimated accuracy might not be guaranteed with the state-of-the-art methods when multipath delays don't exactly locate on the grid points.In this paper,we construct a gridless measuring matrix for sparse channel estimation which contains an off-grid adjusting factor.The Relevance Vector Machine(RVM) algorithm is employed to estimate this factor.The numerical experiments for two different underwater channels are performed to testify the newly proposed method.The results demonstrate that this method outperforms conventional ones in terms of estimating error and bit error rate,especially when the grid gets coarser.

Underwater acoustic communication and the general performance evaluation criteria

Driven by the huge demand to explore oceans, underwater wireless communications have been rapidly developed in the past few decades. Due to the complex physical characteristics of water, acoustic wave is the only media available for underwater wireless communication at any distance. As a result, underwater acoustic communication(UAC) is the major research field in underwater wireless communication. In this paper, characteristics of underwater acoustic channels are first introduced and compared with terrestrial communication to demonstrate the difficulties in UAC research. To give a general impression of the UAC, current important research areas are mentioned. Furthermore, different principal modulation-based schemes for short-and medium-range communications with high data rates are investigated and summarized. To evaluate the performance of UAC systems in general,three criteria are presented based on the research publications and our years of experience in high-rate short-to medium-range communications. These three criteria provide useful tools to generally guide the design and evaluate the performance of underwater acoustic communication systems.

An Orthogonal Wavelet Transform Fractionally Spaced Blind Equalization Algorithm Based on the Optimization of Genetic Algorithm

An orthogonal wavelet transform fractionally spaced blind equalization algorithm based on the optimization of genetic algorithm(WTFSE-GA) is proposed in viewof the lowconvergence rate,large steady-state mean square error and local convergence of traditional constant modulus blind equalization algorithm(CMA).The proposed algorithm can reduce the signal autocorrelation through the orthogonal wavelet transform of input signal of fractionally spaced blind equalizer,and decrease the possibility of CMA local convergence by using the global random search characteristics of genetic algorithm to optimize the equalizer weight vector.The proposed algorithm has the faster convergence rate and smaller mean square error compared with FSE and WT-FSE.The efficiency of the proposed algorithm is proved by computer simulation of underwater acoustic channels.