Soft Direct-Adaptation Based Bidirectional Turbo Equalization for MIMO Underwater Acoustic Communications

This paper proposes a soft direct-adaptation based bidirectional turbo equalizer for multiple-input multiple-output underwater acoustic communication systems. Soft, rather than hard, direct-adaptation based equalizer combined with the fast self-optimized least mean square algorithm is employed to achieve a faster convergence rate, and the second-order phase-locked loop is embedded into the equalizer to track the time-varying channel. Meanwhile, by utilizing a weighted linear combining scheme, the conventional soft direct-adaptation based equalizer is combined with the time-reversed soft direct-adaptation based equalizer to exploit bidirectional diversity and mitigate error propagation. Both the simulation and experimental results demonstrate that the soft direct-adaptation based bidirectional turbo equalizer outperforms the single-direction soft direct-adaptation based turbo equalizer, and achieves a faster convergence rate than the hard direct-adaptation based bidirectional turbo equalizer.

Modeling and Channel Estimation for Piezo-Acoustic Backscatter Assisted Underwater Acoustic Communications

Relying on direct and converse piezoelectric effects,piezo-acoustic backscatter(PAB)technology reflects ambient acoustic signals to enable underwater backscatter communications at near-zero power,which was first realized through a prototype.In this paper,we propose a mathematical model of the PAB assisted underwater acoustic(UWA)communication,and address the sparse channel estimation problem.First,we present a five-stage backscatter process to derive the backscatter coefficient,and propose the channel model for the shallow-water communications.Then,we formulate the shallow-water acoustic channel estimation problem as a sparse vector recovery one according to the compressed sensing theory,and leverage the orthogonal matching pursuit(OMP)algorithm to obtain the channel estimator.Finally,simulation results are provided to corroborate our proposed studies.

An improved least mean square/fourth direct adaptive equalizer for under-water acoustic communications in the Arctic

An improved least mean square/fourth direct adaptive equalizer(LMS/F-DAE)is proposed in this paper for underwater acoustic communication in the Arctic.It is able to process complex-valued baseband signals and has better equalization performance than LMS.Considering the sparsity feature of equalizer tap coefficients,an adaptive norm(AN)is incorporated into the cost function which is utilized as a sparse regularization.The norm constraint changes adaptively according to the amplitude of each coefficient.For small-scale coefficients,the sparse constraint exists to accelerate the convergence speed.For large-scale coefficients,it disappears to ensure smaller equalization error.The performance of the proposed AN-LMS/F-DAE is verified by the experimental data from the 9th Chinese National Arctic Research Expedition.The results show that compared with the standard LMS/F-DAE,AN-LMS/F-DAE can promote the sparse level of the equalizer and achieve better performance.

Low Complexity Adaptive Equalizers for Underwater Acoustic Communications

Interference signals due to scattering from surface and reflecting from bottom is one of the most important problems of reliable communications in shallow water channels. To solve this problem, one of the best suggested ways is to use adaptive equalizers. Convergence rate and misadjustment error in adaptive algorithms play important roles in adaptive equalizer performance. In this paper, affine projection algorithm （APA）, selective regressor APA（SR-APA）, family of selective partial update （SPU） algorithms, family of set-membership （SM） algorithms and selective partial update selective regressor APA （SPU-SR-APA） are compared with conventional algorithms such as the least mean square （LMS） in underwater acoustic communications. We apply experimental data from the Strait of Hormuz for demonstrating the efficiency of the proposed methods over shallow water channel. We observe that the values of the steady-state mean square error （MSE） of SR-APA, SPU-APA0 SPU-normalized least mean square （SPU-NLMS）, SPU-SR-APA0 SM-APA and SM-NLMS algorithms decrease in comparison with the LMS algorithm. Also these algorithms have better convergence rates than LMS type algorithm.

Space-division multiple access for CDMA multiuser underwater acoustic communications

Time reversal mirror （TRM） can use the physical characteristics of the underwater acoustic （UWA） channel to focus on the desired user in multi-user UWA communication. The active average sound intensity （AASI） detector can estimate all azimuths of users with the same frequency band at the same time in order to achieve directional communication by vector combination. Space-division multiple access （SDMA） based on TRM combined with the AASI detector is proposed in this paper, which can make the capacity of the code division multiple access （CDMA） UWA system significantly increase. The simulation and lake test results show that the 7-user UWA multi-user system can achieve low bit error communication.

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.

Bidirectional turbo equalization for underwater acoustic communications

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.

Spatial diversity and combination technology using amplitude and phase weighting method for phase-coherent underwater acoustic communications

The UWA channel is characterized as a time-dispersive rapidly fading channel, which in addition exhibits Doppler instabilities and limited bandwidth. To eliminate inter- symbol interference caused by multipath propagation, spatial diversity equalization is the main technical means. The paper combines the passive phase conjugation and spatial processing to maximize the output array gain. It uses signal-to-noise-plus-interference to evaluate the quality of signals received at different channels. The amplitude of signal is weighted using Sigmoid function. Second order PLL can trace the phase variation caused by channel, so the signal can be accumulated in the same phase. The signals received at different channels need to be normal- ized. It adopts fractional-decision feedback diversity equalizer （FDFDE） and achieves diversity equalization by using different channel weighted coefficients. The simulation and lake trial data processing results show that, the optimized diversity receiving equalization algorithm can im- prove communication system＇s ability in tracking the change of underwater acoustic channel, offset the impact of multipath and noise and improve the performance of communication system. The performance of the communication receiving system is better than that of the equal gain combination. At the same time, the bit error rate （BER） reduces 1.8%.

Acoustic MIMO Communications in a Very Shallow Water Channel

Underwater acoustic channels pose a great difficulty for the development of high speed communication due to highly limited band-width as well as hostile multipath interference. Enlightened by rapid progress of multiple-input multiple-output （MIMO） technologies in wireless communication scenarios, MIMO systems offer a potential solution by enabling multiple spatially parallel communication channels to improve communication performance as well as capacity. For MIMO acoustic communications, deep sea channels offer substantial spatial diversity among multiple channels that can be exploited to address simultaneous multipath and co-channel interference. At the same time, there are increasing requirements for high speed underwater communication in very shallow water area （for example, a depth less than 10 m）. In this paper, a space-time multichannel adaptive receiver consisting of multiple decision feedback equalizers （DFE） is adopted as the receiver for a very shallow water MIMO acoustic communication system. The performance of multichannel DFE receivers with relatively small number of receiving elements are analyzed and compared with that of the multichannel time reversal receiver to evaluate the impact of limited spatial diversity on multi-channel equalization and time reversal processing. The results of sea trials in a very shallow water channel are presented to demonstrate the feasibility of very shallow water MIMO acoustic communication.

Beam alignments based on the spectrum decomposition of orbital angular momentums for acoustic-vortex communications

Given the enhanced channel capacity of wave chirality,acoustic communications based on the orbital angular momentum(OAM)of acoustic-vortex(AV)beams are of significant interest for underwater data transmissions.However,the stringent beam alignment is required for the coaxial arrangement of transceiver arrays to ensure the accuracy and reliability of OAM decoding.To avoid the required multiple measurements of the traditional orthogonality based algorithm,the beam alignment algorithm based on the OAM spectrum decomposition is proposed for AV communications by using simplified ring-arrays.Numerical studies of the single-OAM and OAM-multiplexed AV beams show that the error of the OAM spectrum increases with the translation distance and the deflection angle of the transceiver arrays.To achieve an ideal arrangement,two methods of the single-array translation alignment and the dual-array deflection alignment are developed based on the least standard deviation of the OAM spectrum(SD-OAM).By decreasing the SD-OAM towards zero using transceiver arrays of 16 transmitters and 16 receivers,accurate beam alignments are accomplished by multiple adjustments in three dimensions.The proposed method is also demonstrated by experimental measurements of the OAM dispersion and the SD-OAM for misaligned beams.The results demonstrate the feasibility of the rapid beam alignment based on the OAM spectrum decomposition by using simplified transceiver ring-arrays,and suggest more application potentials for acoustic communications.

基于信道短化和圆球译码的水声通信迭代序列检测

The demand for high-data-rate underwater acoustic communications(UACs)in marine development is increasing;however,severe multipaths make demodulation a challenge.The decision feedback equalizer(DFE)is one of the most popular equalizers in UAC;however,it is not the optimal algorithm.Although maximum likelihood sequence estimation(MLSE)is the optimal algorithm,its complexity increases exponentially with the number of channel taps,making it challenging to apply to UAC.Therefore,this paper proposes a complexity-reduced MLSE to improve the bit error rate(BER)performance in multipath channels.In the proposed algorithm,the original channel is first shortened using a channel-shortening method,and several dominant channel taps are selected for MLSE.Subsequently,sphere decoding(SD)is performed in the following MLSE.Iterations are applied to eliminate inter-symbol interference caused by weak channel taps.The simulation and sea experiment demonstrate the superiority of the proposed algorithm.The simulation results show that channel shortening combined with SD can drastically reduce computational complexity,and iterative SD performs better than DFE based on recursive least squares(RLS-DFE),DFE based on improved proportionate normalized least mean squares(IPNLMS-DFE),and channel estimation-based DFE(CE-DFE).Moreover,the sea experimental results at Zhairuoshan Island in Zhoushan show that the proposed receiver scheme has improved BER performance over RLSDFE,IPNLMS-DFE,and CE-DFE.Compared with the RLS-DFE,the BER,after five iterations,is reduced from 0.0076 to 0.0037 in the 8–12 k Hz band and from 0.1516 to 0.1145 in the 13–17 k Hz band at a distance of 2000 m.Thus,the proposed algorithm makes it possible to apply MLSE in UAC in practical scenarios.

Controlling acoustic orbital angular momentum with artificial structures:From physics to application

Acoustic orbital angular momentum(OAM)associated with helicoidal wavefront recently attracts rapidly-growing attentions,offering a new degree of freedom for acoustic manipulation.Due to the unique dynamical behavior and inherent mode orthogonality of acoustic OAM,its harnessing is of fundamental interests for wave physics,with great potential in a plethora of applications.The recent advance in materials physics further boosts efforts into controlling OAM-carrying acoustic vortices,especially acoustic metasurfaces with planar profile and subwavelength thickness.Thanks to their un-conventional acoustic properties beyond attainable in the nature,acoustic artificial structures provide a powerful platform for new research paradigm for efficient generation and diverse manipulation of OAM in ways not possible before,enabling novel applications in diverse scenarios ranging from underwater communication to object manipulation.In this article,we present a comprehensive view of this emerging field by delineating the fundamental physics of OAM-metasurface interac-tion and recent advances in the generation,manipulation,and application of acoustic OAM based on artificial structures,followed by an outlook for promising future directions and potential practical applications.

Fractional Fourier domain hopped communication method based on chirp modulation for underwater acoustic channels

To improve the data rate of underwater acoustic frequency-hopped communications, frequency hopping is applied to different orders of fractional Fourier domain (FrFD), to enable non-intrusive, bandwidth-limited acoustic communications. An FrFD frequency-hopped communication method based on chirp modulation, namely multiple chirp shift keying-FrFD hopping (MCSK-FrFDH), is proposed for underwater acoustic channels. Validated by both simulations and experimental results, this method can reach a bandwidth efficiency twice more than conventional frequency-hopped methods with the same data rate and anti-multipath capability, suggesting that the proposed method achieves a better performance than the traditional frequency hopped communication in underwater acoustic communication channels. Results also show that in practical scenarios, the MCSK-FrFDH system with longer symbol length performs better at the low signal-to-noise ratio (SNR), while the system with larger frequency sweeping range performs better at a high SNR.

Shipborne Underwater Acoustic Communication System and Sea Trials with Submersible Shenhai Yongshi

The Shipborne acoustic communication system of the submersible Shenhai Yongshi works in vertical, horizontal and slant channels according to the relative positions. For ease of use, an array combined by a vertical-cone directional transducer and a horizontal-toroid one is installed on the mothership. Improved techniques are proposed to combat adverse channel conditions, such as frequency selectivity, non-stationary ship noise, and Doppler effects of the platform’s nonlinear movement. For coherent modulation, a turbo-coded single-carrier scheme is used. In the receiver, the sparse decision-directed Normalized Least-Mean-Square soft equalizer automatically adjusts the tap pattern and weights according to the multipath structure, the two receivers’ asymmetry, the signal’s frequency selectivity and the noise’s spectrum fluctuation. The use of turbo code in turbo equalization significantly suppresses the error floor and decreases the equalizer’s iteration times, which is verified by both the extrinsic information transfer charts and bit-error-rate performance. For noncoherent modulation, a concatenated error correction scheme of nonbinary convolutional code and Hadamard code is adopted to utilize full frequency diversity. Robust and lowcomplexity synchronization techniques in the time and Doppler domains are proposed. Sea trials with the submersible to a maximum depth of over 4500 m show that the shipborne communication system performs robustly during the adverse conditions. From the ten-thousand communication records in the 28 dives in 2017, the failure rate of the coherent frames and that of the noncoherent packets are both below 10%, where both synchronization errors and decoding errors are taken into account.

Radio-Acoustic Integrated Network for Ocean Information Transmission:Framework and Enabling Technologies

An important vision of next generation mobile system is to provide global internet access.The Space-Terrestrial Integrated Network(STIN)has been proposed and intensively studied to tackle this challenge.Due to the severe attenuation of radio signals in water,the STIN cannot be directly applied in underwater scenarios.In this paper we envision a framework of integrated radio-acoustic network arming at high-efficient data transmission in underwater scenarios,where acoustic signal is for underwater communication and radio signal is for surface and air communications.Since radio links have much higher data transmission rate and lower delay,in the integrated radio-acoustic network,the acoustic links easily become congested,at the same time the radio links are not fully utilized.We therefore propose that the integrated radio-acoustic network should be properly designed to minimize the hop count of acoustic links,as well as the signaling overhead in the acoustic subnetwork.We then present a novel network framework and the relative technologies to help moving the signaling overhead to the radio subnetwork.

Immune particle swarm optimization of linear frequency modulation in acoustic communication

With the exploration of the ocean, underwater acoustic communication has attracted more and more attention in recent years. The underwater acoustic channel is considered to be one of the most complicated channels because it suffers from more serious multipath effect, fewer available bandwidths and quite complex noise. Since the signals experience a serious distortion after being transmitted through the underwater acoustic channel, the underwater acoustic communication experiences a high bit error rate （BER）. To solve this problem, carrier waveform inter- displacement （CWlD） modulation is proposed. It has been proved that CWlD modulation is an effective method to decrease BER. The linear frequency modulation （LFM） carrier-waves are used in CWlD modulation. The performance of the communication using CWID modulation is sensitive to the change of the frequency band of LFM carrier-waves. The immune particle swarm optimization （IPSO） is introduced to search for the optimal frequency band of the LFM carrier-waves, due to its excellent performance in solving complicated optimization problems. The multi-objective and multi- peak optimization nature of the IPSO gives a suitable description of the relationship between the upper band and the lower band of the LFM carrier-waves. Simulations verify the improved perfor- mance and effectiveness of the optimization method.

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.

QMCR:A Q-Learning-Based Multi-Hop Cooperative Routing Protocol for Underwater Acoustic Sensor Networks

Routing plays a critical role in data transmission for underwater acoustic sensor networks(UWSNs)in the internet of underwater things(IoUT).Traditional routing methods suffer from high end-toend delay,limited bandwidth,and high energy consumption.With the development of artificial intelligence and machine learning algorithms,many researchers apply these new methods to improve the quality of routing.In this paper,we propose a Qlearning-based multi-hop cooperative routing protocol(QMCR)for UWSNs.Our protocol can automatically choose nodes with the maximum Q-value as forwarders based on distance information.Moreover,we combine cooperative communications with Q-learning algorithm to reduce network energy consumption and improve communication efficiency.Experimental results show that the running time of the QMCR is less than one-tenth of that of the artificial fish-swarm algorithm(AFSA),while the routing energy consumption is kept at the same level.Due to the extremely fast speed of the algorithm,the QMCR is a promising method of routing design for UWSNs,especially for the case that it suffers from the extreme dynamic underwater acoustic channels in the real ocean environment.

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.

Cross-Ice Acoustic Communication:Cascade Acoustic Channel Model and Experimental Results

Cross-ice acoustic information transmission is an effective means of communication in polar sea areas covered by ice.However,the channel is extremely complicated because of the combined influence of water,ice,and air.Based on the normalmode theory,this paper establishes a cascade acoustic channel(CAC)model for the transmission of underwater acoustic waves across ice layer.The model can calculate the displacement response of the ice layer’s upper surface by separating the upward waves from normal modes in the water and multiplying it by a transmission coefficient matrix.The relationship between the displacement response of the upper surface of ice layer and the acoustic frequency is calculated by the finite-element method,and the calculation result was consistent with that of the CAC model.To verify the applicability of the model,a cross-ice acoustic communication experiment was conducted in Songhua River in January 2019.Experimental results show the energy of the acoustic signals received by geophones is closely related to sound frequency and crossice acoustic communication is feasible.The result of present research is important for understanding crossice acoustic channel characteristics and developing future cross-ice acoustic communication in polar sea areas.