Multiple-input Multiple-output Underwater Acoustic Communications Research Articles

Time domain turbo equalization based on vector approximate message passing for multiple-input multiple-output underwater acoustic communications.

This paper proposes a high-performance receiver for underwater acoustic communications based on time reversal processing for multiple-input multiple-output (MIMO) systems. The receiver employs the vector approximate message passing (VAMP) algorithm as a soft equalizer in turbo equalization. By performing self-iteration between the inner soft slicer and the inner soft equalizer, the VAMP algorithm achieves near-optimal performance. Furthermore, an iterative channel-estimation-based soft successive interference cancellation method is incorporated to suppress co-channel interference in the MIMO system. Additionally, the introduction of passive time reversal technology can combine multiple channels into a single channel, which greatly reduces the computational complexity of the MIMO system, especially for large MIMO systems. The effectiveness of the proposed receiver is verified using experimental data collected in Songhua Lake, China in 2019. The results demonstrate that the proposed receiver significantly reduces the complexity of the traditional parallel-VAMP receiver without sacrificing performance and outperforms other receivers of the same type. Moreover, our experimental results also verify that the VAMP-turbo outperforms the generalized approximate message passing (GAMP)-turbo in terms of bit error rate and convergence performance.

Adaptive equalization based on dynamic compressive sensing for single-carrier multiple-input multiple-output underwater acoustic communications.

The sparse property of a direct adaptive equalizer (DAE) for single-carrier underwater acoustic communications is well recognized. It has been used to improve the performance and/or reduce the complexity of a DAE. Extensive investigations have been performed in terms of performance improvement. On the contrary, research on complexity reduction remains preliminary. A fundamental way for reducing the complexity of a DAE is to keep only significant taps while discarding trivial taps, that is, to run a partial-tap DAE. Existing partial-tap DAE designs assume a slowly varying sparse structure and may suffer performance degradation under a severe underwater environment. Motivated by this fact, the dynamic compressed sensing (DCS) technique is resorted to and a partial-tap DAE based on the sparse adaptive orthogonal matching pursuit-affine projection algorithm is proposed. The sparse adaptive orthogonal matching pursuit-affine projection algorithm-direct adaptive equalizer (SpAdOMP-APA-DAE) achieves symbol-wise updating of both positions and values of the significant coefficients. In this paper, a more extensive study on DCS-based DAEs is performed, and an enhanced dynamic compressed sensing-direct adaptive equalizer design enabled by the sparse adaptive subspace pursuit-improved proportionate affine projection algorithm (SpAdOMP-IPAPA) is proposed. The sparse adaptive subspace pursuit-improved proportionate affine projection algorithm-direct adaptive equalizer enjoys lower complexity while better performance than the previous SpAdOMP-APA-DAE. Experimental results corroborated the superiority of the SpAdOMP-IPAPA-DAE.

Bayesian Iterative Channel Estimation and Turbo Equalization for Multiple-Input–Multiple-Output Underwater Acoustic Communications

This article investigates a robust receiver scheme for a single carrier, multiple-input-multiple-output (MIMO) underwater acoustic (UWA) communications, which uses the sparse Bayesian learning algorithm for iterative channel estimation embedded in Turbo equalization (TEQ). We derive a block-wise sparse Bayesian learning framework modeling the spatial correlation of the MIMO UWA channels, where a more robust expectation-maximization algorithm is proposed for updating the joint estimates of channel impulse response, residual noise, and channel covariance matrix. By exploiting the spatially correlated sparsity of MIMO UWA channels and the second-order a priori channel statistics from the training sequence, the proposed Bayesian channel estimator enjoys not only relatively low complexity but also more stable control of the hyperparameters that determine the channel sparsity and recovery accuracy. Moreover, this article proposes a low complexity space-time soft decision feedback equalizer (ST-SDFE) with successive soft interference cancellation. Evaluated by the undersea 2008 Surface Processes and Acoustic Communications Experiment, the improved sparse Bayesian learning channel estimation algorithm outperforms the conventional Bayesian algorithms in terms of the robustness and complexity, while enjoying better estimation accuracy than the orthogonal matching pursuit and the improved proportionate normalized least mean squares algorithms. We have also verified that the proposed ST-SDFE TEQ significantly outperforms the low-complexity minimum mean square error TEQ in terms of the bit error rate and error propagation.

Sparse direct adaptive equalization based on proportionate recursive least squares algorithm for multiple-input multiple-output underwater acoustic communications.

In this paper, the sparse direct adaptive equalization based on the recently developed proportionate recursive least squares (PRLS) adaptive filtering algorithm is investigated for multiple-input multiple-output (MIMO) underwater acoustic (UWA) communications. First, performance analysis is made for the PRLS, and simulation results show its gain over a standard recursive least squares algorithm under sparse systems. The fast implementation of the PRLS, named the proportionate stable fast transversal filters (PSFTF), is revisited to implement a direct adaptive decision-feedback equalizer which outperforms the existing PSFTF direct adaptive linear equalizer. The PSFTF direct adaptive equalizers (DAEs) are then compared with the selective zero-attracting stable fast transversal filter DAEs (SZA-SFTF-DAEs) enabled by the SZA-SFTF adaptive filtering algorithm. The SZA-SFTF algorithm is designed with the zero-attracting sparsity-promoting principle, which is in parallel to the proportionate updating principle used to design the PSFTF algorithm. Experimental results of an at-sea MIMO UWA communication trial show that PSFTF-DAEs outperform the SZA-SFTF-DAEs.

On the Achievable Rate of Multiple-Input–Multiple-Output Underwater Acoustic Communications

This paper investigates the data gain brought by the multiple-input-multiple-output (MIMO) principle for underwater acoustic (UWA) communication. By considering a class of acoustic MIMO channels where each fading coefficient is modeled by a Rice distribution law with correlation factor depending on channel Doppler spread, we derive the achievable rate of such system that takes into account both channel estimation error and training sequence overhead. Model parameters are then estimated from an experiment campaign in a MIMO shallow water channel conducted in the roadstead of Brest, France. The system achievable rate is evaluated for several MIMO architectures and channel configurations and then compared against the conventional single-input-multiple-output transmission. The achievable rate gain is finally put in perspective with end-to-end data rate performance of a single-carrier MIMO transmission system experimented at sea.

Frequency-domain equalization with interference rejection combining for single carrier multiple-input multiple-output underwater acoustic communications.

This paper describes a three-step frequency-domain equalization scheme for multiple-input multiple-output (MIMO) underwater acoustic communication. First, an iterative least-squares channel estimation method is developed to enhance the accuracy of channel estimation in MIMO communication. The interference rejection combining method is then adopted to suppress co-channel interference based on the estimated MIMO channels. This technique exploits the correlation between the interference received through different channels. Finally, a decision feedback equalizer embedded with a digital phase-lock loop is cascaded before the final determination of equalized symbols to compensate the phase rotation. Experimental results show that the bit error rates of the proposed scheme can be several orders of magnitude lower than those of conventional frequency-domain equalization schemes.

MIMO Underwater Acoustic Communication in Shallow Water with Ice Cover

Although multiple-input multiple-output (MIMO) underwater acoustic (UWA) communication has been intensively investigated in the past years, existing works mainly focus on open-water environment. There is no work reporting MIMO acoustic communication in under-ice environment. This paper presents results from a recent MIMO acoustic communication experiment which was conducted in Bohai Gulf during winter. In this experiment, high frequency MIMO signals centered at 10 kHz were transmitted from a two-element source array to a four-element vertical receiving array at 1 km range. According to the received signal of different array elements, MIMO acoustic communication in under-ice environment suffers less effect from co-channel interference compared with that in open-water environment. In this paper, time reversal followed by a single channel decision feedback equalizer is used to process the experimental data. It is demonstrated that this simple receiver is capable of realizing robust performance using fewer hydrophones (i.e. 2) without the explicit use of complex co-channel interference cancelation algorithms, such as parallel interference cancelation or serial interference cancelation.

Direct adaptive equalization based on fast sparse recursive least squares algorithms for multiple-input multiple-output underwater acoustic communications.

The sparse direct adaptive equalizer (DAE) has recently attracted much attention in underwater acoustic (UWA) communications for its improved performance compared with conventional non-sparse DAEs. The recursive least squares (RLS) type sparse DAEs were barely studied, mainly due to their high complexity despite fast convergence. This letter presents several low-complexity sparse RLS algorithms for multiple-input multiple-output UWA channel equalization. The resulting fast sparse RLS DAEs are tested to be effective and outperform their non-sparse counterpart by experimental results.

Improved proportionate FONLMS algorithm based direct adaptive Turbo equalization for MIMO underwater acoustic communications

In this paper, a novel normalized least mean squares (NLMS) algorithm that jointly updates the efficient of the linear equalizer and soft interference canceller (SIC) in an adaptive turbo equalizer for multiple-input multiple-output (MIMO) underwater acoustic (UWA) communications. To exploit the sparsity of MIMO UWA channels and enhance the convergence speed of adaptive equalization, improved proportionate fast self-optimized NLMS algorithm (IPFONLMS), is proposed to well adapt to sparse channel with the similar complexity as improve proportionate NLMS (IPNLMS) algorithm. Then we extend the proposed algorithm to the adaptive turbo equalization for MIMO UWA communications. The performance of the proposed adaptive algorithm is evaluated by numerical results. Simulation results show that the improved data efficiency and bit error ratio (BER) performance of the proposed receiver is achieved over adaptive turbo equalizer based on the IPNLMS algorithm.

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.

Corrections to "Efficient Adaptive Turbo Equalization for Multiple-Input–Multiple-Output Underwater Acoustic Communications" [W. Duan, J. Tao, and Y. Rosa Zheng, IEEE J. Ocean. Eng ., 2017, DOI: 10.1109/JOE.2017.2707285

Corrections to "Efficient Adaptive Turbo Equalization for Multiple-Input–Multiple-Output Underwater Acoustic Communications" [W. Duan, J. Tao, and Y. Rosa Zheng, IEEE J. Ocean. Eng ., 2017, DOI: 10.1109/JOE.2017.2707285

Multiple-input multiple-output underwater acoustic communications by using a quasi-orthogonal group space-time architecture

A Quasi-orthogonal Group Space-Time (QoGST) architecture is presented in this paper for better diversity and multiplexing tradeoff gains in Multiple-Input Multiple-Output (MIMO) underwater acoustic (UWA) communications. Both QoGST and Group Layered Space-Time (GLST) are the combination of space-time block coding (STBC) and layered space-time coding. For GLST, the STBC is taken just in each group. For QoGST, however, all groups are encoded together via inter-group STBC, which can effectively suppress the interference between groups with the orthogonal STBC. At the receivers, the STBC decoding is performed and thus we have the higher diversity gains for the group detection. A statistical model of UWA channel which is presented by Milica Stojanovic and contains variations caused by small- and large-scale effects is considered. Simulation results show that the frame error rate (FER) of QoGST is much lower than that of GLST, which means the QoGST has the higher diversity gains. Furthermore, the lower bound diversity and multiplexing tradeoff of QoGST is coincides with that of GLST and the upper bound diversity and multiplexing tradeoff of QoGST is closer to the optimal values.

Iterative Channel Estimation and Turbo Equalization for Multiple-Input Multiple-Output Underwater Acoustic Communications

This article investigates a robust receiver scheme for a single carrier, multiple-input–multiple-output (MIMO) underwater acoustic (UWA) communications, which uses the sparse Bayesian learning algorithm for iterative channel estimation embedded in Turbo equalization (TEQ). We derive a block-wise sparse Bayesian learning framework modeling the spatial correlation of the MIMO UWA channels, where a more robust expectation–maximization algorithm is proposed for updating the joint estimates of channel impulse response, residual noise, and channel covariance matrix. By exploiting the spatially correlated sparsity of MIMO UWA channels and the second-order a priori channel statistics from the training sequence, the proposed Bayesian channel estimator enjoys not only relatively low complexity but also more stable control of the hyperparameters that determine the channel sparsity and recovery accuracy. Moreover, this article proposes a low complexity space-time soft decision feedback equalizer (ST-SDFE) with successive soft interference cancellation. Evaluated by the undersea 2008 Surface Processes and Acoustic Communications Experiment, the improved sparse Bayesian learning channel estimation algorithm outperforms the conventional Bayesian algorithms in terms of the robustness and complexity, while enjoying better estimation accuracy than the orthogonal matching pursuit and the improved proportionate normalized least mean squares algorithms. We have also verified that the proposed ST-SDFE TEQ significantly outperforms the low-complexity minimum mean square error TEQ in terms of the bit error rate and error propagation.

Frequency-Domain Turbo Equalization with Soft Successive Interference Cancellation for Single Carrier MIMO Underwater Acoustic Communications

This paper proposes a low-complexity frequency-domain turbo equalizer (FDTE) combined with phase rotation compensation and soft successive interference cancellation (SSIC) for single carrier multiple-input multiple-output (MIMO) underwater acoustic (UWA) communications. Different from existing time-domain turbo equalizers in MIMO UWA systems, the proposed receiver implements low-complexity turbo equalization in the frequency domain to combat severe inter-symbol interference (ISI) and employs a layered structure to cope with unbalanced MIMO channels. Soft, rather than hard, successive interference cancellation (SIC) is employed in the layered iterative turbo detection to alleviate co-channel interference (CCI), and phase compensation is utilized within the layered FDTE to mitigate phase rotation. The proposed scheme was evaluated by the SPACE08 experiment conducted in a shallow area of the Atlantic Ocean in October 2008. The 2-transducer 12-hydrophone MIMO system communicated with quaternary phase shift keying (QPSK) and 8-phase shift keying (8PSK) modulation schemes over 200 m and 1000 m ranges, where the proposed FDTE-SSIC scheme achieved low bit error rates (BERs) with only a few iterations. Simulation results also demonstrated that the proposed FDTE-SSIC receiver provided lower BER than one-layer FDTE receivers with comparable complexity.

Low‐complexity turbo detection for single‐carrier low‐density parity‐check‐coded multiple‐input multiple‐output underwater acoustic communications

ABSTRACTA low‐complexity turbo detection scheme is proposed for single‐carrier multiple‐input multiple‐output (MIMO) underwater acoustic (UWA) communications using low‐density parity‐check (LDPC) channel coding. The low complexity of the proposed detection algorithm is achieved in two aspects: first, the frequency‐domain equalization technique is adopted, and it maintains a low complexity irrespective of the highly dispersive UWA channels; second, the computation of the soft equalizer output, in the form of extrinsic log‐likelihood ratio, is performed with an approximating method, which further reduces the complexity. Moreover, attributed to the LDPC decoding, the turbo detection converges within only a few iterations. The proposed turbo detection scheme has been used for processing real‐world data collected in two different undersea trials: WHOI09 and ACOMM09. Experimental results show that it provides robust detection for MIMO UWA communications with different modulations and different symbol rates, at different transmission ranges. Copyright © 2011 John Wiley & Sons, Ltd.

Bandwidth-efficient frequency-domain equalization for single carrier multiple-input multiple-output underwater acoustic communications

This paper proposes a single carrier (SC) receiver scheme with bandwidth-efficient frequency-domain equalization (FDE) for underwater acoustic (UWA) communications employing multiple transducers and multiple hydrophones. Different from the FDE methods that perform FDE on a whole data block, the proposed algorithm implements an overlapped-window FDE by partitioning a large block into small subblocks. A decision-directed channel estimation scheme is incorporated with the overlapped-window FDE to track channel variations and improve the error performance. The proposed algorithm significantly increases the length of each block and keeps the same number of training symbols per block, hence achieving better data efficiency without performance degradation. The proposed scheme is tested by the undersea data collected in the Rescheduled Acoustic Communications Experiment (RACE) in March 2008. Without coding, the 2-by-12 MIMO overlapped-window FDE reduces the average bit error rate (BER) over traditional SC-FDE schemes by 74.4% and 84.6% for the 400 m and 1000 m range systems, respectively, at the same data efficiency. If the same BER performance is required, the proposed algorithm has only 8.4% transmission overhead, comparing to over 20% overhead in other existing UWA OFDM and SC-FDE systems. The improved data efficiency and/or error performance of the proposed FDE scheme is achieved by slightly increased computational complexity over traditional SC-FDE schemes.

Channel Equalization for Single Carrier MIMO Underwater Acoustic Communications

Multiple-input multiple-output (MIMO) underwater acoustic (UWA) channels introduce both space-time interference (STI) and time-varying phase distortion for transmitted signals. In such cases, the equalized symbols produced by conventional equalizer aiming for STI cancelation suffer phase rotation and thus cannot be reliably detected. In this paper, we propose a new equalization scheme for high data rate single carrier MIMO UWA channels. Different from existing methods employing joint equalization and symbolwise phase tracking technology, the proposed scheme decouples the interference cancelation (IC) operation and the phase compensation operation, leading to a generalized equalizer structure combining an IC equalizer with a phase compensator. The decoupling of the two functionalities leads to robust signal detection, which is most desirable in practical UWA applications. MIMO linear equalizer (LE) is adopted to remove space-time interference, and a groupwise phase estimation and correction method is used to compensate the phase rotation. In addition, the layered space-time processing technology is adopted to enhance the equalization performance. The proposed equalization scheme is tested to be very robust with extensive experimental data collected at Kauai, Hawaii, in September 2005, and Saint Margaret's Bay, Nova Scotia, Canada, in May 2006.