Filtered Multitone Modulation Underwater Acoustic Communications Using Low-Complexity Channel-Estimation-Based MMSE Turbo Equalization

Accurate Channel Estimation and Adaptive Underwater Acoustic Communications Based on Gaussian Likelihood and Constellation Aggregation

Achieving accurate channel estimation and adaptive communications with moving transceivers is challenging due to rapid changes in the underwater acoustic channels. We achieve an accurate channel estimation of fast time-varying underwater acoustic channels by using the superimposed training scheme with a powerful channel estimation algorithm and turbo equalization, where the training sequence and the symbol sequence are linearly superimposed. To realize this, we develop a ‘global’ channel estimation algorithm based on Gaussian likelihood, where the channel correlation between (among) the segments is fully exploited by using the product of the Gaussian probability-density functions of the segments, thereby realizing an ideal channel estimation of each segment. Moreover, the Gaussian-likelihood-based channel estimation is embedded in turbo equalization, where the information exchange between the equalizer and the decoder is carried out in an iterative manner to achieve an accurate channel estimation of each segment. In addition, an adaptive communication algorithm based on constellation aggregation is proposed to resist the severe fast time-varying multipath interference and environmental noise, where the encoding rate is automatically determined for reliable underwater acoustic communications according to the constellation aggregation degree of equalization results. Field experiments with moving transceivers (the communication distance was approximately 5.5 km) were carried out in the Yellow Sea in 2021, and the experimental results verify the effectiveness of the two proposed algorithms.

Generalized Frequency Division Multiplexing-Based Low-Power Underwater Acoustic Image Transceiver

In this paper, a low-power underwater acoustic (UWA) image transceiver based on generalized frequency division multiplexing (GFDM) modulation for underwater communication is proposed. The proposed transceiver integrates a low-density parity-check code error protection scheme, adaptive 4-quadrature amplitude modulation (QAM) and 16-QAM strategies, GFDM modulation, and a power assignment mechanism in an UWA image communication environment. The transmission bit error rates (BERs), the peak signal-to-noise ratios (PSNRs) of the received underwater images, and the power-saving ratio (PSR) of the proposed transceiver obtained using 4-QAM and 16-QAM, with perfect channel estimation, and channel estimation errors (CEEs) of 5%, 10%, and 20% were simulated. The PSNR of the received underwater image is 44.46 dB when using 4-QAM with a CEE of 10%. In contrast, PSNR is 48.79 dB when using 16-QAM with a CEE of 10%. When BER is 10^-4, the received UW images have high PSNR values and high resolutions, indicating that the proposed transceiver is suitable for underwater image sensor signal transmission.

Joint Time-Reversal Space-Time Block Coding and Adaptive Equalization for Filtered Multitone Underwater Acoustic Communications

Underwater acoustic (UWA) sensor networks demand high-rate communications with high reliability between sensor nodes for massive data transmission. Filtered multitone (FMT) is an attractive multicarrier technique used in high-rate UWA communications, and can obviously shorten the span of intersymbol interference (ISI) with high spectral efficiency and low frequency offset sensitivity by dividing the communication band into several separated wide sub-bands without guard bands. The joint receive diversity and adaptive equalization scheme is often used as a general ISI suppression technique in FMT-UWA communications, but large receive array for high diversity gain has an adverse effect on the miniaturization of UWA sensor nodes. A time-reversal space-time block coding (TR-STBC) technique specially designed for frequency-selective fading channels can replace receive diversity with transmit diversity for high diversity gain, and therefore is helpful for ISI suppression with simple receive configuration. Moreover, the spatio-temporal matched filtering (MF) in TR-STBC decoding can mitigate ISI obviously, and therefore is of benefit to lessen the complexion of adaptive equalization for post-processing. In this paper, joint TR-STBC and adaptive equalization FMT-UWA communication method is proposed based on the merit of TR-STBC. The proposed method is analyzed in theory, and its performance is assessed using simulation analysis and real experimental data collected from an indoor pool communication trial. The validity of the proposed method is proved through comparing the proposed method with the joint single-input–single-output (SISO) and adaptive equalization method and the joint single-input–multiple-output (SIMO) and adaptive equalization method. The results show that the proposed method can achieve better communication performance than the joint SISO and adaptive equalization method, and can achieve similar performance with more simpler receive configuration as the joint SIMO and adaptive equalization method.

Direct-Mapping-Based MIMO-FBMC Underwater Acoustic Communication Architecture for Multimedia Signals

In this paper, a direct-mapping (DM)-based multi-input multi-output (MIMO) filter bank multi-carrier (FBMC) underwater acoustic multimedia communication architecture (UAMCA) is proposed. The proposed DM-based MIMO-FBMC UAMCA is rare and non-obvious in the underwater multimedia communication research topic. The following are integrated into the proposed UAMCA: A 2 × 2 DM transmission mechanism, a (2000, 1000) low-density parity-check code encoder, a power assignment mechanism, an object-composition petrinet mechanism, adaptive binary phase shift keying modulation and 4-offset quadrature amplitude modulation methods. The multimedia signals include voice, image, and data. The DM transmission mechanism in different spatial hardware devices transmits different multimedia packets. The proposed underwater multimedia transmission power allocation algorithm (UMTPAA) is simple, fast, and easy to implement, and the threshold transmission bit error rates (BERs) and real-time requirements for voice, image, and data signals can be achieved using the proposed UMTPAA. The BERs of the multimedia signals, data symbol error rates of the data signals, power saving ratios of the voice, image and data signals, mean square errors of the voice signals, and peak signal-to-noise ratios of the image signals, for the proposed UAMCA with a perfect channel estimation, and channel estimation errors of 5%, 10%, and 20%, respectively, were explored and demonstrated. Simulation results demonstrate that the proposed 2 × 2 DM-based MIMO-FBMC UAMCA is suitable for low power and high speed underwater multimedia sensor networks.