Reinforcement Learning-Based Virtual Time Compressed Mirror for Underwater Acoustical Channel Equalization Based on Main Path to Side Path Ratio Criterion

Owing to the underwater (UW) acoustic channel characteristic (i.e. low bandwidth and the multipath spreading) the real time multimedia (i.e. image and video) transmission over underwater acoustic (UWA) channel is a very tough task. Therefore, in this paper, an acoustic millimeter-wave (mmWave) communication channel is proposed to replace the conventional UWA channel. Where, the high bandwidth of acoustic mmWave is exploited to improve the UW communication throughput (megabit/sec). Moreover, the set partitioning in hierarchical trees (SPIHT) coder is used as an efficient source coder to effectively support the real-time underwater image transmission over the acoustic mmWave channel. However, a real measured UWA channel data are used in this paper to test the performances of the mm Wave underwater communication. The data are collected from the South China Sea to demonstrate the acoustic mmWave underwater communication channel to be used to transmitting a high efficient real-time underwater image. The simulation results indicate the efficiency of multimedia communication over the UW acoustic mmWave channel. However, UW acoustic mmWave communication improves the peak signals-to-noise ratio (PSNR) performance of the UW multimedia transmission.

The fast temporal variations, long multipath delay spreads, and severe frequency-dependent attenuations of underwater acoustic communication channels are extremely complex that impedes underwater acoustic (UWA) data transmission. To alleviate this problem, channel coding is indispensable in UWA communication system to increase the reliability. In this paper, performances of LDPC codes with different parameters over different underwater acoustic communication channels are presented, which is to know how to adjust the encoding and decoding parameters according to different underwater acoustic channels. The results indicate that LDPC codes have a good performance of the estimated BER on the order of 10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-4</sup> -10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-5</sup> either in positive sound velocity gradient (PSVG) underwater channel or negative sound velocity gradient (NSVG) one, even invariable sound velocity gradient (ISVG) one. In addition, whatever the encoding or decoding parameters is adopted, performance of the LDPC codes over the NSVG underwater channel is the best, compared with PSVG one and ISVG one. Furthermore, in the desired performance of BER of 10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-5</sup> , the encoding and decoding parameters according to the three different underwater channels specifications are summarized.

The recent emerging applications of novel underwater systems lead to increasing demand for underwater acoustic (UWA) communication and networking techniques. However, due to the challenging UWA channel characteristics, conventional wireless techniques are rarely applicable to UWA communication and networking. The cognitive and software-defined communication and networking are considered promising architecture of a novel UWA system design. As an essential component of a cognitive communication system, the modeling and prediction of the UWA channel impulse response (CIR) with deep generative models are studied in this work. Firstly, an underwater acoustic communication and networking testbed is developed for conducting various simulations and field experiments. The proposed test-bed also demonstrated the capabilities of developing and testing SDN protocols for a UWA network in both simulation and field experiments. Secondly, due to the lack of appropriate UWA CIR data sets for deep learning, a series of field UWA channel experiments have been conducted across a shallow freshwater river. Abundant UWA CIR data under various weather conditions have been collected and studied. The environmental factors that significantly affect the UWA channel state, including the solar radiation rate, the air temperature, the ice cover, the precipitation rate, etc., are analyzed in the case studies. The obtained UWA CIR data set with significant correlations to weather conditions can benefit future deep-learning research on UWA channels. Thirdly, a Wasserstein conditional generative adversarial network (WCGAN) is proposed to model the observed UWA CIR distribution. A power-weighted Jensen–Shannon divergence (JSD) is proposed to measure the similarity between the generated distribution and the experimental observations. The CIR samples generated by the WCGAN model show a lower power-weighted JSD than conventional estimated stochastic distributions. Finally, a modified conditional generative adversarial network (CGAN) model is proposed for predicting the UWA CIR distribution in the 15-minute range near future. This prediction model takes a sequence of historical and forecast weather information with a recent CIR observation as the conditional input. The generated CIR sample predictions also show a lower power-weighted JSD than conventional estimated stochastic distributions.

Adaptive and efficient nonlinear channel equalization for underwater acoustic communication

Underwater acoustic (UWA) channel is a complex time-space- and frequency-variant channel, which is one of the most difficult wireless communication channels so far. Coherent communication has become a hotspot in high speed underwater acoustic communication. To achieve the low bit error rate and high data transmission rate, the channel equalization technique must be introduced for coherent underwater acoustic communication system, such as QPSK, OFDM and so on. The variable step-size LMS adaptive equalization algorithm reduces the steady-state error while increasing the convergence rate, and is commonly used in the underwater acoustic channel equalization. In this paper, a new variable step-size LMS adaptive equalization algorithm is proposed. The algorithm improves the convergence performance by establishing the nonlinear function model of step-size and error. In this paper, the key parameter selection of the algorithm is analyzed and the reasonable setting is given. The simulation results in Matlab show that the algorithm has a great improvement in the convergence rate, and it is suitable for the fast time — variant underwater acoustic channel.

In this paper, two typical methods of designing underwater acoustic (UWA) channel simulators, the geometry based and the measurement based, are investigated. Then, the performance of each method is analyzed by comparing the statistical properties of the simulated channels with those of the real shallow UWA channel measured in Halong bay, Vietnam, in June 2015. The results show that the measurement-based channel simulator provides the simulated channel which matches well with the real UWA channel, but it requires application of complex optimization computation methods to estimate a larger number of channel parameters. The geometry-based simulator has a lower complexity than the measurement-based simulator. However, the statistical properties obtained by this simulator do not fit with those of the real UWA channel. This is our motivation to propose an effective channel simulator, which is not only simple in computation but also in good agreement with the real UWA channel. The parameters of the proposed UWA channel simulator can be directly exploited from the measurement data without applying any optimization computation method. Moreover, the simulation results show that the channel statistical properties obtained by the proposed method match well with those of the real UWA channel.

Due to the complex ocean propagation environments, the underwater acoustic (UWA) multipath channel often exhibits block sparse time-varying features, and while dynamic compressed sensing (DCS) can mitigate the time-varying effects of the UWA channel, DCS-based algorithms have limited performance for the UWA channel with block sparsity. In this study, by formulating the UWA channel with blocks concatenation, a block sparse-based DCS approach (BS-CS) is proposed to explore the block and time-varying sparsity of UWA channel simultaneously. In detail, we firstly adopt a block sparse recovery algorithm, block orthogonal matching pursuit (BOMP), to compute the temporary estimate. Then, the CS approach is applied to compute the support additions, which are caused by the time-varying components of the UWA channel. Next, we use the selected support to perform the BOMP estimate, and obtain the estimated channel response. Finally, the numerical simulation and the sea experiment were carried out to verify the superior performance of the proposed BS-CS algorithm in the block sparse time-varying UWA channels.

Channel estimation for underwater acoustic (UWA) channels in orthogonal frequency division multiplexing (OFDM) systems is one of the most difficult problems in UWA communications. Because UWA channels are both frequency-selective and time-selective, the total number of channel coefficients to be estimated will significantly increase. Besides, the fast time-varying characteristics and strong Doppler effects will deteriorate the orthogonality between the OFDM subcarriers and cause inter-carrier interference (ICI). To handle these problems, in this paper, we firstly transform the discrete doubly selective UWA channel model into an expansion of complex exponential basis. Based on the basis expansion model (BEM) of UWA channels, we then equivalently transform the channel estimation problem into the recovery of sparse BEM coefficients. Finally, a modified sparse signal recovery scheme based on block sparse Bayesian learning is proposed to estimate the doubly selective UWA channel state information (CSI). Simulation results confirm its performance merits.

Acoustic signals are a first choice in underwater communication since sound waves face very low attenuation in water compared to radio frequency (RF). However, the tendency of receiver to detect multipath signals (due to signals bouncing off surface or the bottom) induces large delay spreads and thus strong channel frequency selectivity. Additionally, rapid spatial and temporal variations in underwater acoustic (UWA) channel makes it hostile for communication systems based on single carrier modulation. Multicarrier modulation techniques, on the other hand, can greatly improve bandwidth utilization and help deal with time dispersal effects. Orthogonal frequency division multiplexing (OFDM) is a proven multicarrier communication system having capabilities to cope with frequency selectivity and delay spreads effectively. OFDM has started to get attention for being a simpler alternative to high complexity and high maintenance single carrier systems in UWA communication systems. This work proposes a Matlab model of an OFDM transceiver along with UWA channel characterization based on Rician shadowed fading model as it perfectly characterizes the way in which a shallow UWA channel behaves. Eventually, the proposed design allows implementation of various OFDM modulation methods and to perform Monte Carlo simulations for bit error rate comparisons together with the ability to tune multiple UWA channel parameters.

Multicarrier acoustic communication has enabled wireless underwater transmission at higher data rates. Several multicarrier modulation systems have been explored in the past for data transmission. Orthogonal frequency division multiplexing (OFDM) fights-off inter-symbol-interference due to orthogonality of the carriers. However, it is susceptible to time variations which introduces inter-carrier-interference. Being double selective, the underwater acoustic (UWA) channel is both time and frequency variant. Time variations and multipath fading makes it a complex channel to estimate. In this paper, we explore linear frequency domain equalization techniques available for radio OFDM systems and compare their performance for a shallow underwater acoustic channel. The underwater channel model used is based on Rician shadowed distribution with Doppler shifts. We compare the performance of a linear equalizer with pilot estimated channel against a zero-forcing equalizer where the channel is assumed to be known. Results collected through Monte Carlo simulations show that for a 128-subcarrier OFDM system and a transmitter-receiver separation of 800 m, a gain of almost 7dB is obtained at a BER of 10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-3</sup> when a zero-forcing equalizer is used. Moreover, when the subcarriers are increased to 256, this gain almost doubles. In conclusion, the zero-forcing equalizer outperforms the LS equalizer for an underwater acoustic channel.

The achievement of efficient data transmissions via underwater acoustic channels, while dealing with large data packets and real-time data fed by underwater sensors, requires a~high data rate. However, diffraction, refraction, and reflection phenomena, as well as phase and amplitude variations, are common problems experienced in underwater acoustic (UWA) channels. These factors make it difficult to achieve high-speed and long-range underwater acoustic communications. Due to multipath interference caused by surface and ocean floor reflections, the process of modeling acoustic channels under the water's surface is of key importance. This work proposes a~simple geometry-based channel model for underwater communication. The impact that varying numbers of reflections, low water depth values, and distances between the transmitter and the receiver exert on channel impulse response and transmission loss is examined. The high degree of similarity between numerical simulations and actual results demonstrates that the proposed model is suitable for describing shallow underwater acoustic communication environments.

In this paper, the estimation of doubly spread underwater acoustic (UWA) channels is investigated. The UWA channels are characterized by severe delay spread and significant Doppler effects, and can be well modeled as a multi-scale multi-lag (MSML) channel. Furthermore, exploiting the sparsity of UWA channels, MSML channel estimation can be transformed into the estimation of parameter sets (amplitude, Doppler scale factor, time delay). Based on this, the orthogonal matching pursuit (OMP) algorithm has been widely used. However, the estimation accuracy of OMP depends on the size of the dictionary, which is related with both delay spread and Doppler spread. Thus it requires high computational complexity. This paper proposes a new method, called wavelet transform (WT) based algorithm, for the UWA channel estimation. Different from OMP algorithm which needs to search in both time domain and Doppler domain, WT-based algorithm only needs to search in time domain by using the Doppler invariant characteristic of hyperbolic frequency modulation (HFM) signal. The performance of the proposed algorithm is evaluated by computer simulations based on BELLHOP. The simulation results show that WT-based algorithm performs slightly better than OMP algorithm in low signal to noise ratio (SNR) while can greatly reduce computational complexity.

Underwater acoustic (UWA) channel is typically sparse. In this paper, a complex Homotopy algorithm is presented and then applied for UWA OFDM channel estimation. Two enhancements that exploit UWA channel temporal correlation for the compressed-sensing(CS)-based channel estimators are proposed. The first one is based on a first-order Gauss-Markov (GM) model which uses the previous channel estimate to assist current one. The other is to use the recursive least-squares (RLS) algorithm together with the CS algorithms to track the time-varying UWA channel. Simulation results show that the Homotopy algorithm offers faster and more accurate UWA channel estimation performance than other sparse recovery methods, and the proposed enhancements offer further performance improvement.

Underwater acoustic (UWA) channel is a time-space-frequency varying channel. Coherent detection requires channel estimation in Orthogonal Frequency Division Multiplexing (OFDM) system. In this paper, the channel estimation methods based on pilot for OFDM UWA system are investigated. Through analysis and testing about two channel estimation performance, the adaptability based on Pilot Symbol Assisted Modulation (PSAM) channel estimation methods under UWA channel is given.

Experimental evaluation of norm constraint sparsity exploitation for shallow water acoustic communication