Multipath Underwater Acoustic Channel Research Articles

Underwater Acoustic Orthogonal Frequency-Division Multiplexing Communication Using Deep Neural Network-Based Receiver: River Trial Results.

In this article, a deep neural network (DNN)-based underwater acoustic (UA) communication receiver is proposed. Conventional orthogonal frequency-division multiplexing (OFDM) receivers perform channel estimation using linear interpolation. However, due to the significant delay spread in multipath UA channels, the frequency response often exhibits strong non-linearity between pilot subcarriers. Since the channel delay profile is generally unknown, this non-linearity cannot be modeled precisely. A neural network (NN)-based receiver effectively tackles this challenge by learning and compensating for the non-linearity through NN training. The performance of the DNN-based UA communication receiver was tested recently in river trials in Western Australia. The results obtained from the trials prove that the DNN-based receiver performs better than the conventional least-squares (LS) estimator-based receiver. This paper suggests that UA communication using DNN receivers holds great potential for revolutionizing underwater communication systems, enabling higher data rates, improved reliability, and enhanced adaptability to changing underwater conditions.

Cosine function variable step-size transform domain least mean square algorithm based on matrix rotation

A novel cosine function variable step-size transform domain least mean square (LMS) algorithm based on matrix rotation (COS-ROTDCT-LMS-DFE) was put forward. Based on the discrete cosine transform domain LMS (DCT-LMS) algorithm, it was first processed by matrix rotation in an anticlockwise direction to resolve the problem of self-interference between signals, which effectively sped up the convergence of the algorithm. Subsequently, a cosine function variable step-size algorithm was developed considering that its curve was characterized by a smooth top and fast rising and falling speed so as to further improve the convergence speed of the algorithm. Subsequently, the decision feedback equalizer (DFE) was introduced into the algorithm to compensate signal distortion and noise. The convergence performance of the algorithm was simulated in typical multipath underwater acoustic channels. The simulation results showed that the convergence performance of the new algorithm was equivalent to that of recursive least squares (RLS). The convergence speed of COS-ROTDCT-LMS-DFE was even better than that of the recursive least square decision feedback equalizer (RLS-DFE) algorithm. The new algorithm performed well in terms of both convergence speed and steady-state error and could be easily implemented.

Deep Learning-Aided Signal Detection for Two-Stage Index Modulated Universal Filtered Multi-Carrier Systems

The growing interests in Internet of Underwater Things (IoUT) put forward more demands for underwater acoustic (UWA) communication technologies. However, the conventional orthogonal frequency division multiplexing (OFDM) technology underperforms in terms of the resistance to carrier frequency offset (CFO), symbol time offset (STO), and applicability to multiple application scenarios. To remedy the deficiencies, this paper introduces the emerging universal filtered multi-carrier (UFMC) technology into UWA communications and devises a two-stage index modulated UFMC (TSIM-UFMC) system for performance improvement. In addition, a deep learning-aided signal detector termed as TSIMNet is proposed for the TSIM-UFMC system over multipath UWA channels. Specifically, at the transmitter, the TSIM-UFMC system adopts two-stage index modulation to characterize the different position information of data, pilot, and inactive subcarriers in each subblock for ameliorating the bit error rate (BER) performance under channel interferences. At the receiver, the TSIMNet detector exploits configurable deep neural networks to encapsulate the index demodulation, channel estimation, and constellation demodulation for optimizing the system structure. Furthermore, TSIMNet can be deployed to detect the received signal online for the TSIM-UFMC system after trained by offline data. Numerical results reveal that the proposed TSIM-UFMC system exhibits achievable advantages in combating CFO and STO, and the TSIMNet detector actualizes a near-optimal performance on BER with preferable computational complexity.

A Comparative Study of SC and MC Underwater Acoustic Communication Systems

In this study, comparative performance analyzes of single carrier (SC) and multi carrier (MC) underwater acoustic communication (UWAC) schemes are performed in underwater acoustic channel environments. Computer simulation studies are carried out to compare SC and MC UWAC communication systems in multi-path underwater acoustic channel environments based on bit error rate (BER) and mean square error (MSE) accomplishment benchmarks. From the acquired outcomes, it is perceived that the MC-UWAC communication scheme has approximately 3 dB better achievement than the SC-UWAC communication scheme.

Residual Doppler Effect Analysis of the FBMC/OQAM Communication System in Underwater Acoustic Channel

The filterbank multicarrier (FBMC) waveform has better properties in spectral as compared to the Orthogonal Frequency Division Multiplexing (OFDM) and it exhibits good anti-interference performance. We mainly consider an important variety of the FBMC systems, namely FBMC based on offset orthogonal amplitude modulation (FBMC/OQAM). This letter presents an analysis of the residual Doppler effect in the multipath underwater acoustic (UWA) channel for the FBMC/OQAM system. Assuming the received signal has gone through coarse non-uniform Doppler compensation by resampling, we model the compensated signal with residual Doppler effect and multipath effect. Especially, we derive a simplified closed-form expression for the received FBMC signal after non-uniform Doppler compensation under the signal-to-interference ratio. The theoretical results and the simulations show better compliance in the UWA multipath channel. Furthermore, the results obtained demonstrate that FBMC has better BER performance than the cyclic prefix (CP) based OFDM in the case of residual Doppler effect under the UWA channel.

NOMA Based Cooperative Relaying Strategy for Underwater Acoustic Sensor Networks Under Imperfect SIC and Imperfect CSI: A Comprehensive Analysis

In this paper, we propose non-orthogonal multiple access based cooperative relaying strategy (NOMA-CRS) for underwater acoustic sensor networks (UASNs). We analyse the performance of NOMA-CRS for both shallow and deep water scenarios, under imperfect channel state information (I-CSI) as well as imperfect successive interference cancellation (I-SIC). We derive mathematical expressions for ergodic rate, outage probability as well as the energy efficiency of NOMA-CRS in UASNs by considering the underwater specific characteristics, such as distance-dependent usable bandwidth, acoustic spreading, propagation loss, and fading effects. We compare the performance of NOMA-CRS with the widely used decode-and-forward based CRS in the UASNs. From the results, it is evident that NOMA-CRS can achieve significant improvement in ergodic sum rate and energy efficiency. But the outage performance is slightly degraded for the proposed scheme. Our results show that I-CSI and I-SIC have a significant impact on the performance of the NOMA-CRS. We also investigate the impact of relay position, wind speed as well as shipping activities on the performance of NOMA-CRS under the realistic underwater scenario. Results show that high-speed winds and high shipping activities severely degrade the performance of ergodic sum rate of the NOMA-CRS. Implementation of NOMA-CRS requires CSI at the transmitter. However, acquiring perfect CSI at the transmitter is a challenging task in time-varying multi-path underwater acoustic channels. As a solution, we also propose space-time block coded NOMA-CRS (STBC-NOMA-CRS) for UASNs, which can be implemented without CSI at the transmitter. Extensive simulation studies are conducted to corroborate the analytical findings.

Subcarrier modulation identification of underwater acoustic OFDM based on block expectation maximization and likelihood

The low identification rate of the Orthogonal frequency division multiplexing (OFDM) based subcarrier modulation in underwater acoustic multipath channel is an important issue. Therefore, we proposed a novel Expectation Maximization-Block-Quasi Hybrid Likelihood Ratio Test (EM-Block-QHLRT) method which effectively improved the identification rate while using the blind channel impulse response (CIR) estimation and likelihood. Initially, CIR is obtained by using clustering, and then the CIR is updated iteratively by EM-Block method. Further, the subcarrier modulation is identified using QHLRT. The influence of iteration times, the length of symbol and influence of the number of blocks in EM are analyzed by using extensive simulation. The identification rate of subcarrier modulation of binary phase shift keying (BPSK), QPSK, 8PSK and 16QAM are presented using different signal noise ratio (SNR). In addition, the identification rate of subcarrier modulation based on Average Likelihood Rate Test (ALRT) as well as QHLRT with EM are compared. Simulation results showed that the identification rate of the proposed EM-Block-QHLRT method can reach to more than 90% when SNR is higher than 5 dB. Finally, the performance of the proposed EM-Block-QHLRT method is verified using sea trial data.

Blind Modulation Identification of Underwater Acoustic MPSK Using Sparse Bayesian Learning and Expectation Maximization

This paper presents a likelihood-based algorithm for identifying different phase shift keying (PSK) modulations, i.e., BPSK, QPSK, and 8PSK. This algorithm selects the modulation type that maximizes a loglikelihood function that is based on the known original constellation associated with the constellation of the received signals for the candidate modulation types. However, there are two problems in non-cooperative underwater acoustic Multiple Phase Shift Keying (MPSK) modulation identification based on the likelihood method. One is the original constellation, which as prior information is unknown. The other is the underwater acoustic multipath channel makes the constellation distort seriously. In this paper, we solved these problems by combining sparse bayesian learning (SBL) with expectation maximization (EM). The specific steps are as follows. Firstly, blind channel equalization can be achieved by channel impulse response (CIR), which is estimated by sparse bayesian learning in single input multi output (SIMO) underwater acoustic channel. Subsequently, we used expectation maximization to compensate amplitude attenuation and phase offset, as the original constellation of MPSK is unknown. Finally, modulation can be successfully identified by the Quasi Hybrid Likelihood Ratio Test (QHLRT). The simulation results show that the channel estimation method based on SBL can eliminate the influence of channel effectively, and the EM algorithm can make the received constellation converge to the preset constellation in the case of unknown original transmit constellation, which effectively solves these two problems. We use the proposed SBL-EM-QHLRT method to achieve an identification rate of more than 95% in underwater acoustic multipath channels with Signal to Noise Ratio (SNR) higher than 15 dB, which provides a new idea for modulation identification of non-cooperative underwater acoustic MPSK.

Positioning of leakages in underwater natural gas pipelines for time-varying multipath environment

Underwater natural gas pipelines (UNGPs) used to typically transport natural gas, which is a very important energy resource, can be punctured due to various reasons such as corrosion and shipping/fishing activities. Therefore, the detection and positioning of leakages has an important role in ensuring energy reliability and preventing environmental pollution. In this study, kth nearest neighbor (KNN) algorithm based fingerprint method is proposed to locate leakages in the UNGPs. The success of this method is analyzed using a realistic time-varying multipath underwater acoustic channel and the parameters of a real life UNGP. Numerical results show that for this channel, leakages can be positioned with a margin of low errors from kilometers away depending on the ambient noise, number of receivers, and sea wave height.

Iterative matching-based parameter estimation for time-scale underwater acoustic multipath echo

In this paper, a wideband underwater acoustic multipath channel is investigated with a sonar-target relative movement. The underwater environment causes time delay, amplitude and Doppler factor changes on the transmitted signals, as a result, the signal components from the respective paths may be differentiated from these parameters. The Doppler factor of a specific path is analyzed in a moving condition, and the impulse responses of the propagation paths are illustrated by the wideband ambiguity function. Since different Doppler factors should be taken into consideration, an effective iterative method is proposed for parameter estimation of multipath echo. The proposed method retrieves a signal component by searching for the optimal scale factor from the resampling matching outputs, and eliminates the matching output of the estimated signal to analyze the next component. The effectiveness of the method is confirmed by some simulation results. It is also effective for various wideband signals with a broad range of frequencies, because the method prevents the time-domain subtractions of the received signals for providing a higher robustness. Therefore, it can be applied in many fields including active target detection and underwater communication.

Parameter Estimation of Delay-Doppler Underwater Acoustic Multi-Path Channel Based on Iterative Fractional Fourier Transform

The characterization of wideband underwater acoustic (UWA) multi-path signals is investigated in this paper. The UWA multi-path channel can be considered as a sparse model and it causes changes of the transmitted signal on Doppler factor, time delay, and amplitude, thus the signal component from each path can be differentiated from the set of parameters. This paper proposes an FrFT-based method to estimate the channel parameters, which can decompose and retrieve the multi-path signals from the UWA channels. The proposed algorithm proceeds in an iterative manner and returns a set of estimated parameters at each turn. The estimated time delay is obtained directly without any extra correlation computation. Then, the estimated component is extracted by eliminating its FrFT result from the fractional domain. Compared to the existing methods, the most improvement is that the method can be applied to the wideband LFM signals with a wider frequency range in low signal-to-noise environment. Because the indirect subtractions avoid the bad chain effect caused by the low resolution or estimation error. The effectiveness of the method is confirmed by several simulations with low and high frequency. The performance is compared with a matching pursuit-based algorithm and an FrFT-based algorithm. It is shown that the proposed method outperforms the existing algorithms in low-frequency multi-component separation as well as estimation accuracy.

MIMO GS OVSF/OFDM Based Underwater Acoustic Multimedia Communication Scheme

An underwater acoustic multimedia communication (UWAMC) system is proposed with 2400 transmission modes according to time-varying multipath underwater acoustic (UWA) channel conditions. The orthogonal variable spreading factor (OVSF) scheme and Gold sequence (GS) scramble code are integrated into multi-input multi-output UWAMC system based on orthogonal frequency-division multiplexing to achieve the quality of service of multimedia transmission in the UWA channel. Binary phase shift keying (BPSK) and quadrature phase shift keying (QPSK) adaptive modulation, direct mapping (DM) or space–time block code (STBC) transmission strategies, convolution channel code with rate 1/2 and 1/3, and a power assignment mechanism were adopted in the proposed system. Simulation results show that the bit error rate (BER) and power saving ratio (PSR) performance of the STBC strategy with transmission diversity is superior to that of the DM strategy without transmission diversity, and the performance of the BERs and PSRs of the transmission scheme with the GS scramble code surpasses that of the scheme without the code. The performance of the BERs and PSRs of BPSK modulation with a channel code rate of 1/3 is better than that of BPSK modulation with a channel code rate of 1/2, and the performances of BERs and PSRs of BPSK modulation with a channel code rate of 1/3 are better than that of QPSK modulation with a channel code rate of 1/3. As the length of the OVSF codes increases, the UWAMC system’s BERs decrease, and its PSRs increase. The UWAMC system can achieve either maximum transmission speed or maximum transmission power efficiency.

Experimental Estimation of the Constant Envelope FM-OFDM Method Usage in Underwater Acoustic Communication Systems

Nowadays, more and more complex methods of signal modulating and processing are actively used for organizing underwater acoustic communication with and between submerged mobile vehicles due to harsh underwater conditions. In this research, the method that is based on multi-frequency signals forming (OFDM) with the constant envelope is applied to the problem. It is based on multi-frequency FM-OFDM signals forming with Quadrature Phase Shift Keying (QPSK) modulated subcarriers and FM spectrum spreading coefficients of 1, 2, 4, and 10. The proposed solution was modeled in a software simulator, which implements a noisy underwater acoustic multipath channel, changing the bit error rate (BER) from 0.15 to 10−3. In addition, it was tested during the full-scale data transmission experiments at 25 km distance using a low frequency (400 Hz) underwater acoustic apparatus under conditions of strong impulse noises and quasi-non-stationary channel. The results of in-situ experiments were similar to the ones that were obtained during the simulation.

Parameter Estimation of Chirp for Underwater Acoustic Channel

To overcome the performance degradation of conventional Chirp parameters estimation methods in underwater acoustic multipath channels, a novel parameters estimation method based on Fractional Fourier transform (FRFT) and Fourier transform (FFT) was proposed. Firstly, the Chirp rate was estimated by searching for the best degree of Chirp after Fractional Fourier transform. Secondly, the Chirp signal turned into a single-frequency signal by means of Chirp rate equalization. Finally, FFT was applied to estimate the initial frequency. The simulation experiment show that the proposed algorithm enhanced about 1dB RMSE performance on Chirp initial frequency compared with FRFT while the computational complexity is similar to FRFT.

Receiver design for spread-spectrum communications with a small spread in underwater clustered multipath channels.

This paper studies a direct-sequence spread-spectrum communication system with a small spreading factor (e.g., a single digit) in underwater acoustic multipath channels. Exploiting the channel characteristics that the propagation paths can be grouped into distinct clusters, a receiver with a set of parallel branches is proposed, where per-survivor processing (PSP) is applied on each branch to deal with the signal from one cluster while explicitly treating the signals from other clusters as structured interference. As such, it overcomes a major limitation of an existing PSP based receiver [Zhou, Morozov, and Preisig, J. Acoust. Soc. Am. 133, 2746-2754 (2013)], avoiding exponential complexity increase when the spreading factor decreases. On the first branch, joint channel estimation and interference cancellation are performed based solely on the survivor paths. On the other branches, joint channel estimation and interference cancellation are carried out based on the survivor paths and the tentatively decoded data. The bit log-likelihood ratios from different branches are combined for channel decoding. Performance results based on simulations and collected data sets validate the superior performance of the proposed receiver over the conventional RAKE receiver, which is effective only when the spreading factor is large.

Parameter Estimation for Multi-Scale Multi-Lag Underwater Acoustic Channels Based on Modified Particle Swarm Optimization Algorithm

The wideband underwater acoustic multipath channel can be modeled as a multi-scale multi-lag (MSML) channel because signals from different paths might experience different Doppler scales. This brings great challenge to channel parameter estimation. In this paper, we propose a novel algorithm for parameter estimation of MSML channels. This new algorithm is a modified particle swarm optimization (MPSO) algorithm, which can estimate the parameters of the Doppler scale, the time delay, and the amplitude simultaneously for each individual path. Comparing to PSO algorithm, MPSO algorithm uses a multipath list to record positions and fitness values of particles whose fitness values are selected as lbest s, and uses these lbest s to update particles’ velocities at each iteration. As for training sequence, we employ the zero correlation zone sequence which has excellent correlation properties. Computer simulation is used to evaluate the proposed algorithm in comparison with the matching pursuit (MP)-based method and the fractional Fourier transform (FrFT)-based method. Simulation results confirm that the proposed MPSO algorithm outperforms both MP-based method and FrFT-based method in estimation accuracy as well as computation complexity.

Parameter Estimation of Wideband Underwater Acoustic Multipath Channels based on Fractional Fourier Transform

Because of relative motion between transmitter and receiver, the wideband underwater acoustic multipath channel can be more accurately described by a multi-scale multi-lag (MSML) model. The signal components received from different paths can be differentiated in terms of Doppler scales, time delays, and amplitudes. Estimation of these parameters is essential for many underwater applications. In this paper, by virtue of the fractional Fourier transform (FrFT), an accurate and efficient method for parameter estimation is proposed. The algorithm proceeds in an iterative manner, returning parameter estimates of the most dominant signal component successively. With the linear frequency modulation signal employed as the probe signal, the estimation of the Doppler scale factor of each dominant component can be converted into a process of searching for the optimal fractional angle/order of the received signal's FrFT. At each iteration, a sub-iteration is contained to adjust the optimal fractional order. The pulse compression techniques for LFM signal, in both time domain and FrFT domain, are utilized to obtain precise parameter estimates. Once the parameters of a multipath are estimated, the corresponding component will be separated from the received signal—through eliminating the resampled, delayed and attenuated version of the original probe signal. The sparsity of the underwater acoustic channel is considered to reduce the amount of calculation. Simulation results confrm that the proposed algorithm outperforms the existing FrFT domain filter and short-time FrFT domain filter in multicomponent separation, and that the proposed parameter estimation scheme surpasses the matching pursuit based method in accuracy.

Performance Evaluation of $$\pi /4$$ π / 4 -DQPSK OFDM over Underwater Acoustic Channels

This paper investigates the performance of orthogonal frequency division multiplexing (OFDM) with $$\pi /4$$ź/4-differential quadrature phase shift keying ($$\pi /4$$ź/4-DQPSK) modulation, over underwater acoustic (UWA) channels. The orthogonal multicarrier scheme with non-coherent detection technique results in spectrally efficient, reliable and simple receiver design. $$\pi /4$$ź/4-QPSK has less envelop fluctuation and performs better in multipath UWA channels. It is shown that with a pair of hydrophones for reception and maximum-ratio combining (MRC) technique, one can achieve considerably low bit-error-rate (BER) at practical signal-to-noise ratio (SNR) value. Further, the BER expression for such a scheme is obtained by using the probability density function and is shown to consist of a series with fast converge rate. The series solution approximation provides a reasonable match between the simulation and the analytical results with and without the MRC diversity technique.

Design optimization of low density parity check codes in multipath underwater acoustic channels

We propose an iterative decoding and equalizing scheme using low density parity check codes and decision feedback equalizer for underwater acoustic communication system. The scheme decodes and equalizes iteratively by linking a LDPC decoder with an adaptive DFE and feeding output soft information of the LDPC decoder to the DFE as priori information. We extend extrinsic information transfer (EXIT) charts to analyze the performance of LDPC codes in multipath underwater acoustic channels. Furthermore, we introduce an EXIT aided method of optimally designing the parameters of LDPC codes using modified differential evolution algorithm in multipath underwater acoustic channel. Design example and simulation are presented in two different underwater acoustic channels which are generated by BELLOP ray tracing model. Bit error rate of the proposed scheme is less than 10-5 as signal to noise rate (SNR) is greater than 8.5 dB in the channels. Compared the regular LDPC code with degree 3 and the Turbo code with feedback and feedforward generator polynomials 1+D+D 2+D 3 and 1+D 2+D 3, the optimized LDPC codes achieve gains of about 0.5 dB and 0.8 dB, respectively, at BER= 10-4 under the same code rate and block length.

Effectiveness of Convolutional Code in Multipath Underwater Acoustic Channel

The forward error correction (FEC) is achieved by increasing redundancy of information. Convolutional coding with Viterbi decoding is a typical FEC technique in channel corrupted by additive white gaussian noise. But the FEC effectiveness of convolutional code is questioned in multipath frequency selective fading channel. In this paper, how convolutional code works in multipath channel in underwater, is examined. Bit error rates (BER) with and without 1/2 convolutional code are analyzed based on channel bandwidth which is frequency selectivity parameter. It is found that convolution code performance is well matched in non selective channel and also effective in selective channel.