Underwater Acoustic Orthogonal Frequency Division Multiplexing Research Articles

Low-Complexity Doppler Compensation Algorithm for Underwater Acoustic OFDM Systems With Nonuniform Doppler Shifts

The Doppler effect severely degrades the orthogonality of orthogonal frequency division multiplexing (OFDM) systems, and is a severe problem in the underwater acoustic (UWA) communications, leading to nonuniform Doppler shifts for all subcarriers. In order to alleviate Doppler effect, resampling technique by oversized fast Fourier transform (FFT) can achieve fast and accurate resampling in frequency domain. Nevertheless, the accuracy of this conventional FFT based approach depends on the FFT size, which in turn increases receiver complexity. In order to overcome this problem, the Doppler compensation model in frequency domain is simplified by Taylor series expansion in this letter. Based on the simplified model, we propose the Doppler compensation algorithm by using FFT and interpolation to achieve higher compensation accuracy. Simulation results demonstrate that the proposed algorithm shows very similar bit error rate (BER) performance with that of Chirp Z-transform (CZT) based method. However, the complexity of our proposed algorithm is about half of CZT based method. Further, our proposed low-complexity Doppler compensation algorithm can also be applied to the sampling frequency offset (SFO) correction in terrestrial OFDM communication systems.

Time-Varying Channel Equalization in Underwater Acoustic OFDM Communication System

In this paper, three time-varying channel equalization schemes are studied in the underwater acoustic (UWA) Orthogonal Frequency Division Multiplexing (OFDM) communication system. The equalization algorithms are the zero-forcing (ZF) equalization algorithm, and the minimum mean square error equalization (MMSE) algorithm and the serial interference cancellation (SIC) equalization algorithm. Among the schemes, there is a problem of needing a large amount of operation when obtaining the inversion of the channel matrix. Then, to reduce the computation complexity of channel matrix inversion, the band approximation of the channel matrix, the serial equalization and the LDLH decomposition are also studied. To evaluate the efficacy of the algorithms studied in this paper, numerical simulation and the field experiment are both conducted. The simulation results proof that each equalization algorithm can work appropriately under different time-varying conditions, and valid the reliability of each simplified algorithm under the same Doppler factor. The results of two sets of field experiment also prove that the simplified algorithm eliminates the influence of the residual narrow band Doppler to a certain extent, and a better effect is obtained while a channel estimation algorithm with higher accuracy is combined.

Compressive sensing compensation algorithm about nonlinear distortion of clipping for underwater acoustic OFDM systems

Orthogonal frequency division multiplexing (OFDM) is one of the most attractive multicarrier modulation schemes over underwater acoustic (UWA) communication due to its robustness against multipath channels. However, the multicarrier modulation technique also leads to a higher peak to average power ratio (PAPR). The nonlinear distortion is produced when the traditional clipping method was used to restrain PAPR. In this paper, we proposed a compensation algorithm based on compressive sensing (CS) about the nonlinear distortion. Combined with orthogonal matching pursuit (OMP) algorithm, pilot and null subcarriers are used to compensate the nonlinear distortion in the receiver. Theoretical analysis and simulation results show that the new algorithm can effectively reduce computational complexity and restrain the nonlinear distortion for UWA communication systems.

New Results on Joint Channel and Impulsive Noise Estimation and Tracking in Underwater Acoustic OFDM Systems

Impulsive noise can greatly affect the performance of underwater acoustic (UA) orthogonal frequency-division multiplexing (OFDM) systems. In this paper, by utilizing the sparsity of the UA channel impulse response and impulsive noise, we first propose a novel sparse Bayesian learning (SBL) based expectation maximization (EM) algorithm for joint channel estimation and impulsive noise mitigation in UA OFDM systems. Secondly, considering that the UA channel and impulsive noise are fast time-varying, we develop a new approach which combines the SBL with the forward-backward Kalman filtering to track the UA channel and impulsive noise. To further improve the system performance, we utilize the information available on data subcarriers for joint time-varying channel estimation and data detection, based on the SBL algorithm and the Kalman filter. The performance of our proposed algorithms is verified through both numerical simulations and by data collected during a UA communication experiment conducted in the estuary of the Swan River, Perth, Australia. The results demonstrate that compared with existing approaches, the proposed algorithms achieve a better system bit-error-rate and frame-error-rate performance.

Channel Estimation Based on Adaptive Denoising for Underwater Acoustic OFDM Systems

Underwater acoustic (UWA) communications systems suffer from a low signal-to-noise ratio (SNR) and a doubly selective channel, which are caused by many limitations, such as high propagation loss, slow propagation speed, and time-varying environmental factors. To overcome a low SNR, various diversity techniques are often adopted in UWA communications. However, such diversity can only be exploited with knowledge of the channel. Accordingly, channel estimation needs to be performed without obtaining the benefit of diversity. Moreover, accurate side information that can support a channel estimator (CE) is difficult to acquire at a low SNR under doubly selective channel. In this article, a novel CE based on an adaptive denoising is proposed for UWA orthogonal frequency-division multiplexing (OFDM) systems. The proposed method exploits two different types of pilot symbols. Channel impulse response (CIR) is estimated based on primary pilot symbols. By minimizing the squared error of the received secondary pilot symbols, a near-optimal denoising window is adaptively determined based on the channel length for the given CIR estimate. The proposed method does not require a priori information about channel statistics and SNR values. Analysis on the effect of denoising and the performance of the proposed denoising window estimator are also presented. Simulation and at-sea experiments verify that the proposed method has superior performance, compared with conventional CEs over diverse channel conditions. Complexity analysis shows that the proposed method is computationally efficient. Therefore, the proposed method is effective for real-time UWA OFDM systems under a harsh UWA channel with strong noise.

Fine Doppler scale estimations for an underwater acoustic CP-OFDM system

In the challenging underwater acoustic (UWA) communication channels, the performance of orthogonal frequency division multiplexing (OFDM) systems is severely affected by the Doppler effect. Hence, the Doppler scale estimation and compensation are critical for UWA OFDM systems. As a commonly adopted solution, the Doppler scale can be estimated by the maximization of auto-correlation between the received cyclic prefix (CP) and OFDM symbol. However, the accuracy of the auto-correlation based Doppler scale estimation is decided by the sampling rate of the signal. To achieve higher estimation accuracy, higher sampling rate is required and which means more computational complexity. To overcome this problem, we propose several fine Doppler scale estimation methods by interpolating the auto-correlation peak values, based on the derived expression of the expected auto-correlation outputs corresponding to a CP-OFDM signal after the UWA channel. Simulation results demonstrate the effectiveness of the proposed methods, and the decoding of experimental data further verifies the superiority of those methods.

An Underwater Acoustic OFDM System Based on NI CompactDAQ and LabVIEW

Recently the orthogonal frequency division multiplexing (OFDM) technique has attracted increasing interests in underwater acoustic (UA) communications. In this paper, we present an OFDM-based UA communication system, which is designed based on the National Instruments LabVIEW software and the CompactDAQ device. Details on both the transmitter and receiver system design are discussed. The performance of this UA OFDM system is verified through recent UA communication experiments performed in a tank, in the Canning River, and in the estuary of the Swan River, Western Australia. Experimental results show that the system achieves a reliable bit error rate performance even with high-order modulation schemes. Compared with conventional field-programmable gate array and digital signal processor based designs, the proposed implementation simplifies the prototype design process and reduces the software development time. The proposed system provides a flexible and reconfigurable prototype for researchers to test and validate the performance of UA communication algorithms in real UA channels.

Parameter estimation based on factor graph in wide‐band OFDM systems

The channel estimation in a wide-band orthogonal frequency division multiplexing (OFDM) system is different from the narrow-band system, for the estimation parameters should include the Doppler scale factor, which is a particular parameter of the wide-band system. The underwater acoustic OFDM system is a typical wide-band system, and its channel has more than one scale factor usually. For this multi-scale case, the common estimation method is a factor-by-factor process with repeated calculation of the reproduced waveform. This article proposes a factor-graph-based estimation method, which fully uses the restriction relationship among the parameters, and estimates the parameters simultaneously. To reduce the computation load, the modified Bayesian propagation (BP) algorithm is proposed. Comparing to the common BP algorithm, the modified BP algorithm simplifies the calculation of the condition probability in the summation. The simulation results of the mean squared error show that the proposed method is an effective estimation method for the multi-scale wide-band system. The bit error rate performance of the proposed method is very close to the result of the known channel-state-information, and outperforms the fractional Fourier transform (FrFT) and the modified particle swarm optimisation (MPSO) methods for well channel condition.

Deep learning based underwater acoustic OFDM communications

In this paper, we present a deep learning based underwater acoustic (UWA) orthogonal frequency-division multiplexing (OFDM) communication system. Unlike the traditional receiver for UWA OFDM communication system that performs explicitly channel estimation and equalization for the detection of transmitted symbols, the deep learning based UWA OFDM communication receiver interpreted as a deep neural network (DNN) can recover the transmitted symbols directly after sufficient training. The estimation of transmitted symbols in the DNN based receiver is achieved in two stages: (1) training stage, when labeled data such as known transmitted data and signal received in the unknown channel are used to train the DNN, and (2) test stage, where the DNN receiver recovers transmitted symbols given the received signal. To demonstrate the performance of the deep learning based UWA OFDM communications, we generate a large number of labeled and unlabeled data by using an acoustic propagation model with a measured sound speed profile to train and test the DNN receiver. The performance of the deep learning based UWA OFDM communications is evaluated under various system parameters, such as the cyclic prefix length, number of pilot symbols, and others. Simulation results demonstrate that the deep leaning based receiver offers consistent improvement in performance compared to the traditional UWA OFDM receiver.

Underwater Acoustic OFDM Channel Estimation with Unknown Sparsity

Underwater acoustic channels estimation accuracy seriously affects the demodulation performance of the receiver in underwater acoustic (UWA) orthogonal frequency division multiplexing (OFDM) communications. Many channel estimation algorithms based on compressed sensing (CS) have been proposed. However, these algorithms usually needs the information of sparsity, while the information of sparsity is unavailable in many UWA OFDM communications. In this paper, a novel channel estimation algorithm based on fractional Fourier transform (FRFT) and orthogonal matching pursuit (OMP) is proposed, FRFT is introduced to process the synchronization signal, so sparsity is estimated. OMP is adopted to reconstruct channel impulse response (CIR). The most innovative feature of the proposed algorithm is the estimation of sparsity, which makes OMP algorithm more practical. Simulation results show that the proposed algorithm outperforms the least square (LS) and in UWA OFDM communication.

Channel Modelling and Estimation for Shallow Underwater Acoustic OFDM Communication via Simulation Platform

The performance of underwater acoustic (UWA) communication is heavily dependent on channel estimation, which is predominantly researched by simulating UWA channels modelled in complex and dynamic underwater environments. In UWA channels modelling, the measurement-based approach provides an accurate method. However, acquirement of environment data and simulation processes are scenario-specific and thus not cost-effective. To overcome such restraints, this article proposes a comprehensive simulation platform that combines UWA channel modelling with orthogonal frequency division multiplexing (OFDM) channel estimation, allowing users to model UWA channels for different ocean environments and simulate channel estimation with configurable input parameters. Based on the simulation platform, three independent simulations are conducted to determine the impacts of receiving depth, sea bottom boundary, and sea surface boundary on channel estimation. The simulations show that UWA channel estimation is greatly affected by underwater environments. The effect can be mainly attributed to changing acoustic rays tracing which result in fluctuating time delay and amplitude. With 10 m receiving depth and flat sea bottom, the channel estimation achieves optimal performance. Further study indicates that the sea surface has stochastic effects on channel estimation. As the significant wave height (SWH) increases, the average performance of channel estimation shows improvements.

A low-complexity orthogonal matching pursuit based channel estimation method for time-varying underwater acoustic OFDM systems

In this paper, we propose a low-complexity Orthogonal Matching Pursuit (OMP) based channel estimation method in underwater acoustic (UWA) orthogonal frequency division multiplexing (OFDM) system, where the channel is time-varying and described by a limited number of paths, each characterized by path delay, path gain and path Doppler scale. In the proposed method, we calculate the candidate path signature Hermitian inner product matrix in advance, avoiding the repeated calculations at each iteration in conventional OMP method. To further reduce the complexity, we estimate the path gains by solving a least-squares (LS) problem after the whole iteration procedure instead of doing this at each iteration step in the conventional OMP method. Results of numerical simulation and sea trial demonstrate the effectiveness of the proposed method in time-varying UWA channels, which can achieve the comparable performance with much lower computational complexity compared with the conventional OMP method.

Joint Compressed Sensing and Enhanced Whale Optimization Algorithm for Pilot Allocation in Underwater Acoustic OFDM Systems

In underwater acoustic-orthogonal frequency division multiplexing (UWA-OFDM) systems, the performance of channel estimation is significantly affected by pilot allocation in the framework of compressed sensing (CS). However, for optimizing the pilot allocation, an exhaustive search method over all possible allocations is computationally prohibitive and random search method may not ensure convergence accuracy. In this paper, the meta-heuristic algorithm of the whale optimization algorithm (WOA) is employed to address this issue. For reinforcing the capability of balancing exploration and exploitation, an enhanced variant of WOA termed EWOA is presented with four optimization strategies. After that, a joint algorithm combining CS with EWOA (CS-EWOA) is proposed for pilot allocation in UWA-OFDM systems. Through extensive simulations, the improvement of EWOA is demonstrated on the majority of benchmark functions over other well-known meta-heuristic algorithms. With regard to bit error rate (BER) and mean square error (MSE) for channel estimation, the proposed CS-EWOA algorithm outperforms the equispaced, random, genetic algorithm (GA), particle swarm optimization (PSO), and WOA-based pilot allocation methods. Moreover, it is robust with varying system subcarriers and channel models. Furthermore, the CS-EWOA exhibits superior convergence performance without increasing the computational complexity compared with the GA-, PSO-, and WOA-based methods in the iteration process of pilot allocation optimization. It can be concluded from the simulation results that the proposed CS-EWOA algorithm is competitive to optimize pilot allocation for channel estimation in UWA-OFDM systems.

Research and Development of a Highly Reconfigurable OFDM MODEM for Shallow Water Acoustic Communication

Orthogonal frequency division multiplexing (OFDM) provides an effective approach to combat multipath with high bandwidth efficiency for underwater acoustic communication, thus design and implementation of acoustic OFDM MODEMs draw more and more attention. Extensive work has been performed to mitigate multipath, Doppler shift, and peak average power ratio from the viewpoint of theoretical analysis. Meanwhile, design and implementation of a parameter-configurable OFDM to adapt to highly diverse underwater channels and various missions become more and more important. Traditional MODEM with fixed parameters cannot achieve the best tradeoff between data rate and bit error rate. In order to obtain the best communication performance under long time delay channels, Doppler channels, and frequency-selective channels, in this paper, we provide the design and implementation of a parameter-configurable underwater acoustic OFDM MODEM with the purpose to achieve flexibility. Specifically, the reconfigurable parameters of the OFDM MODEM include the number of receivers, the number of null subcarriers, the number of pilot subcarriers, as well as the type of channel estimation algorithms. The number of pilot subcarriers and type of channel estimation methods are determined based on channel characteristics, the number of null subcarriers is determined based on the Doppler shift, and the number of the received channels is based on fading channel. Moreover, in this paper, the Doppler estimation performance under different number of null subcarriers, and the channel estimation performance under different number of pilot subcarriers and under different channel estimation algorithms, are analyzed in terms of bit error rate. Finally, the effectiveness of the proposed highly configurable OFDM MODEM is demonstrated by two sea trials corresponding to different communication scenarios.

Analysis of SNR Metrics for a Typical Underwater Acoustic OFDM System

Signal to noise ratios (SNRs) are universal metrics for the performance analysis of communication systems. In underwater acoustic orthogonal frequency division multiplexing (OFDM) systems, compared with the time domain input SNR (ISNR), the pilot SNR (PSNR) and effective SNR (ESNR) are demonstrated to be more effective in system performance indication, especially the ESNR. In this paper, for a typical underwater acoustic OFDM system with orthogonal matching pursuit (OMP) based sparse channel estimation, we derive formulas with a closed form for evaluating the ESNR, which avoids the requirement of successful data decoding in conventional ESNR calculation. The derivation is also extended to PSNR easily. We find out that the ESNR is mainly determined by five parameters: the number of deterministic pilots, the number of dominant paths, the inter-carrier interference (ICI), the total channel power and the ISNR; while the PSNR is only determined by the ICI, the total channel power and the ISNR. Simulations and experimental data decoding are carried out to validate the correctness of the theoretical analysis in this paper.

A Multi-User Detection Scheme Based on Polar Code Construction in Downlink Underwater Acoustic OFDM Communication System

In this paper, we propose a novel polar code construction scheme, suitable for the underwater acoustic (UWA) multi-user communication system using orthogonal frequency division multiplexing (OFDM). We use the polar codes because the code rate of a polar code can be arbitrarily designed. Moreover, the polar codes can also be used to create a nested code structure, divided into several subsets (codebook). We exploit this feature of the polar codes and place the information bits in the codebook to avoid superimposition of all the users. This helps to eliminate the influence of the power allocation coefficient and make full use of the power of the transducer at the transmitted node. Furthermore, the proposed scheme maximizes the utilization efficiency of the OFDM subcarrier resource for each user by avoiding null pilot tones that are usually required for channel equalization in the traditional schemes. The proposed scheme also does not depend on the channel state information (CSI) as prior information as each user can decode their own data independently by using their own codebook without successive interference cancellation (SIC). The simulation and tank experiment results demonstrate that the proposed scheme can significantly guarantee the reliability of all the users, and reduces the complexity of the receiver, thus making it most suitable for the downlink UWA multi-user communication systems.

Cost Function based Soft Feedback Iterative Channel Estimation in OFDM Underwater Acoustic Communication

Underwater Acoustic (UWA) communication is mainly characterized by bandwidth limited complex UWA channels. Orthogonal Frequency Division Multiplexing (OFDM) solves the bandwidth problem and an efficient channel estimation scheme estimates the channel parameters. Iterative channel estimation refines the channel estimation by reducing the number of pilots and coupling the channel estimator with channel decoder. This paper proposes an iterative receiver for OFDM UWA communication, based on a novel cost function threshold driven soft decision feedback iterative channel technique. The receiver exploits orthogonal matching pursuit (OMP) channel estimation and low density parity check (LDPC) coding techniques after comparing different channel estimation and coding schemes. The performance of the proposed receiver is verified by simulations as well as sea experiments. Furthermore, the proposed iterative receiver is compared with other non-iterative and soft decision feedback iterative receivers.

A Time-Varying Filter for Doppler Compensation Applied to Underwater Acoustic OFDM.

This paper describes a Doppler compensation algorithm to improve the reliability of orthogonal frequency division multiplexing (OFDM). To compensate for the time-varying Doppler effect in a mobile deployment scenario, first the time-scaling factor over a wideband channel is estimated using pilot tones inserted in each OFDM symbol. Then, using a time-varying resampling technique, the Doppler effect is compensated during the reception of each OFDM symbol in the frame. To predict the performance of the system in relatively shallow waters, a software channel model is developed that is able to simulate a wide variety of dynamic shallow water deployment scenario. The performance of the algorithm was tested for two extreme frequency ranges during sea trials, the first at 2 kHz for a long-range application, and the second at 125 kHz for a short range telemetry link. For the 2-kHz system, a 16-bps mobile link in which the platform was moving at 1 m/s was demonstrated to have a bit error rate on the order of , while, for the 125-kHz telemetry application, a 2000-bps link was enabled with a bit error rate of 0.03 at a low SNR equal to 5.5 dB.

DFT-Precoded MIMO OFDM Underwater Acoustic Communications

The discrete Fourier transform (DFT) precoded orthogonal frequency-division multiplexing (OFDM) has been adopted as the uplink transmission technique in the long-term evolution terrestrial communication standard, for its lower peak-to-average power ratio (PAPR) and similar receiver complexity, compared with the standard OFDM. However, its application in the underwater acoustic (UWA) communications remains doubtful, mainly for the lack of systematic studies as well as sufficient experimental verifications. This paper provides a comprehensive investigation on the DFT-precoded OFDM UWA communication with a multiple-input–multiple-output (MIMO) configuration, and corroborates its superiority for implementing a practical UWA communication modem. The DFT precoding is applied on the data symbols to achieve a lower PAPR than that of the standard OFDM, and it is optional for the pilot symbols. The frequency-domain turbo equalization (FDTE) technique, especially suitable for interference-intensive scenarios, is employed on the receiver side to combat the intersymbol interference (ISI) and the multiplexing interference. Experimental results are provided to demonstrate the performance of the proposed transceiver scheme. It is shown reliable communication is achieved for the two-transducer transmission with a QPSK modulation and the one-transducer transmission with a 16QAM modulation, even without running any iteration for the FDTE. With the help of turbo iterations, a two-transducer transmission with a 16QAM modulation also achieves a satisfactory performance.

Iterative Compressive Sensing for the Cancellation of Clipping Noise in Underwater Acoustic OFDM System

Due to the characteristics of the underwater acoustic channel especially the limited bandwidth, orthogonal frequency division multiplexing (OFDM) is widely used because of its high spectrum efficiency and ability in anti-multipath fading. However OFDM also has its drawbacks, one of which is the relatively high peak-to-average ratio (PAPR). The problem leads to saturation in the power amplifier and consequently distorts the signal which is not allowed in the underwater acoustic communication. Clipping as the most classic and convenience way is widely applied to address the high PAPR. However, it introduces additional noise that degrades the system performance. In this paper compressed sensing (CS) technique is proposed to mitigate the clipping noise. The scheme exploited pilot tones and data tones instead of reserved tones, which is different from the previous works and causes less loss of data rate. Also, in contrast with previous works, to minimizing the influence of underwater acoustic channel, compressed sensing in channel estimating is also adopted during mitigating the clipping noise, which can provide more accurate channel characteristics for estimating the clipping noise than traditional method such as LS or MMSE. The iterative CS technology proposed in this article can significantly improve the communication quality even in low SNR.