Acoustic Orthogonal Frequency Division Multiplexing System Research Articles

A fast temporal multiple sparse Bayesian learning-based channel estimation method for time-varying underwater acoustic OFDM systems

In this paper, a fast temporal multiple sparse Bayesian learning (FTMSBL)-based channel estimation method for underwater acoustic (UWA) orthogonal frequency division multiplexing (OFDM) systems is proposed, which is optimized using the fast marginalized likelihood maximization method. The algorithm fully uses the consistent sparse structure and time-domain correlation properties of channels to improve the reconstruction performance and computational efficiency, offering better performance and higher computational efficiency than the traditional Bayesian learning algorithms. At the same time, the FTMSBL algorithm does not require computing the inverse of large matrices and consumes very little storage resources in the operation, making it suitable for hardware implementation. Simulation and sea trial results show that the FTMSBL-based underwater channel estimation algorithm achieves higher channel estimation accuracy than the orthogonal matching tracking algorithm, and the system bit error rate (BER) is significantly reduced; specifically, the FTMSBL algorithm can achieve optimal performance in strong time-dependent channels.

Impact of Inter-Channel Interference on Shallow Underwater Acoustic OFDM Systems

This paper investigates the impacts of Inter-Channel Interference (ICI) effects on a shallow underwater acoustic (UWA) orthogonal frequency-division multiplexing (OFDM) communication system. Considering both the turbulence of the water surface and the roughness of the bottom, a stochastic geometry-based channel model utilized for a wide-band transmission scenario has been exploited to derive a simulation model. Since the system bandwidth and the sub-carrier spacing is very limited in the range of a few kHz, the channel capacity of a UWA system is severely suffered by the ICI and Doppler effects. For further investigation, we construct the signal-to-noise-plus-interference ratio (SINR) based on the simulation model, then evaluate the channel capacity. Numerical results show that the various factors of a UWA-OFDM system as subcarriers, bandwidth, and OFDM symbols affects the channel capacity under the different Doppler frequencies. Those observations give hints to select the good parameters for UWA-OFDM systems.

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.

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.

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.

Iterative Sparse Channel Estimation and Spatial Correlation Learning for Multichannel Acoustic OFDM Systems

This article addresses the problem of coherent detection of acoustic orthogonal frequency division multiplexing (OFDM) signals using a sparse channel estimation method based on a physical model of multipath propagation. Unlike the conventional sample-spaced and subsample-spaced methods, such as least squares and orthogonal matching pursuit (OMP), which target the taps of an equivalent discrete-delay channel response, the path identification (PI) method targets the physical propagation paths in a continuous-delay domain, and focuses on explicit estimation of delays and complex amplitudes of the channel paths in an iterative fashion. When multiple receive elements are available, two situations are possible: one in which the array elements see uncorrelated channel responses, and another in which the channel responses are correlated. In the first case, channel estimation must be accomplished element-by-element. This is done simply by applying the PI algorithm to each element individually. In the second case, correlation between the elements can be exploited. In doing so, our goal is to reduce the signal processing complexity without compromising the performance. Toward this goal, an adaptive precombining method is proposed. Without requiring any a priori knowledge about the spatial distribution of received signals, the method exploits spatial coherence between receive channels by linearly combining them into fewer output channels so as to reduce the number of subsequent channel estimators. The algorithm learns the spatial coherence pattern recursively over the carriers, thus effectively achieving broadband beamforming. The reduced-complexity precombining method relies on differential encoding that keeps the receiver complexity at a minimum and requires a very low pilot overhead. Using synthetic data as well as 210 experimental signals transmitted over a 3–7-km shallow-water channel in the 10.5–15.5-kHz acoustic band during a 3.5-h experiment, we study the system performance in terms of data detection mean-squared error (MSE), symbol error rate, and bit error rate (BER), and show that the PI algorithm achieves excellent MSE performance while its complexity is considerably lower than that of the OMP algorithm. We also demonstrate that the receiver equipped with the proposed reduced-complexity precombining scheme requires three times fewer channel estimators while achieving the same MSE and BER performance as the full-complexity receiver.

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.

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.

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.

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.

Equalization and Carrier Frequency Offset Compensation for Underwater Acoustic OFDM Systems

Due to noise enhancement, conventional Zero Forcing (ZF) equalizers are not suitable for wireless Underwater Acoustic (UWA) Orthogonal Frequency Division Multiplexing (OFDM) communication systems. Furthermore, these systems suffer from increasing complexity due to the large number of subcarriers, especially in Multiple-Input Multiple-Output (MIMO) systems. On the other hand, the Minimum Mean Square Error equalizer suffers from high complexity. This type of equalizers needs an estimation of the operating Signal-to-Noise Ratio to work properly. In this paper, we propose a Joint Low-Complexity Regularized ZF equalizer for MIMO UWA-OFDM systems to cope with these problems. The main objective of the proposed equalizer is to enhance the system performance with a lower complexity by performing equalization in two steps. The co-channel interference can be mitigated in the first step. A regularization term is added in the second step to avoid the noise enhancement. Simulation results show that the proposed equalization scheme has the ability to enhance the UWA system performance with low complexity.

Impulsive Noise Mitigation in Underwater Acoustic OFDM Systems

Mitigation of impulsive noise has been extensively studied in wireline, wireless radio, and powerline communication systems. However, its study in underwater acoustic (UWA) systems is quite limited. This paper considers impulsive noise mitigation for underwater orthogonal frequency-division multiplexing (OFDM) systems, where the system performance is severely impacted by the channel Doppler effect. We propose a practical approach based on a least squares formulation: First, the positions of impulsive noise are determined in the time domain based on the signal amplitude, and second, impulsive noise samples are jointly estimated with the Doppler shift based on the measurements of the OFDM null subcarriers. Based on the available channel estimate and tentative data symbol decisions, an iterative receiver is further developed. Data sets have been acquired in a recent sea experiment near Kaohsiung city, Taiwan, in May 2013. Performance results based on extensive simulations and collected data sets demonstrate that the proposed receivers effectively mitigate impulsive noise for UWA OFDM systems.

CSI feedback-based CS for underwater acoustic adaptive modulation OFDM system with channel prediction

In this paper, we investigate the performance of adaptive modulation (AM) orthogonal frequency division multiplexing (OFDM) system in underwater acoustic (UWA) communications. The aim is to solve the problem of large feedback overhead for channel state information (CSI) in every subcarrier. A novel CSI feedback scheme is proposed based on the theory of compressed sensing (CS). We propose a feedback from the receiver that only feedback the sparse channel parameters. Additionally, prediction of the channel state is proposed every several symbols to realize the AM in practice. We describe a linear channel prediction algorithm which is used in adaptive transmission. This system has been tested in the real underwater acoustic channel. The linear channel prediction makes the AM transmission techniques more feasible for acoustic channel communications. The simulation and experiment show that significant improvements can be obtained both in bit error rate (BER) and throughput in the AM scheme compared with the fixed Quadrature Phase Shift Keying (QPSK) modulation scheme. Moreover, the performance with standard CS outperforms the Discrete Cosine Transform (DCT) method.

Joint Interference mitigation with channel estimated in Underwater Acoustic OFDM system

Multicarrier modulation in the form of orthogonal frequency-division-multiplexing (OFDM) has been actively pursued in underwater acoustic communications. However, carrier frequency offset (CFO) can cause significant performance degradation in OFDM systems. Although underwater acoustic communication was recently the focus of research, literatures about joint interference mitigation with channel estimation using compressed sensing (CS) has been very limited in underwater acoustic OFDM. In the Cyclic prefix orthogonal frequency division multiplexing (CP-OFDM) system, a novel method was proposed which combined interference mitigation with channel estimation based on compressed sensing (CS).The novel joint optimization model combined CFO estimation with CS-based channel estimation based on the sparse in the delay-Doppler domain by using the null sub-carriers. Simulations and tank experiments have verified the performance of the receiver based on the joint interference mitigation and CS channel estimation. This method enables the OFDM system is effective against the CFO, and has better robustness.

Implementation of an Impulse Noise Suppression Method in OFDM Underwater Acoustic Communication System

This paper describes the characteristics of the impulse noise in the shallow water acoustic channel, and its influence on the bit error rate (BER) performance of the Orthogonal Frequency Division Multiplexing (OFDM) system. The simulation has been carried out to analyze the performance of the joint suppression of impulse noise in time and frequency domain in OFDM underwater acoustic communication system. Data processing of the actual sea trial in Xiamen Harbor shows that the method has some impressive effect on impulse noise in shallow water acoustic OFDM system, and improves the BER performance on different levels.

Acoustic OFDM system and its extension

This paper presents a method of aerial acoustic communication in which data is modulated using OFDM (Orthogonal Frequency Division Multiplexing) and embedded in regular audio material without significantly degrading the quality of the original sound. It replaces the high frequency band of the audio signal with OFDM carriers, each of which is power-controlled according to the spectrum envelope of the original audio signal. The implemented system enables the transmission of short text messages from loudspeakers to mobile handheld devices at a distance of around 3 m. This paper also provides the subjective assessment results and the transmission performances.