In November 2012, an experiment demonstrating biological mimicry method for covert underwater acoustic communication (UAC) was conducted at Lianhua Lake in Heilongjiang China. Dolphin whistles were used for synchronization while dolphin clicks were used as information carrier. The time interval between dolphin clicks conveys the information bits. Channel estimates were obtained with matching pursuit (MP) algorithm, which is useful for sparse channel estimation. Adaptive RAKE Equalization was employed at the receiver. Bit error rates were less than 10−4 with 37 bits per second data rate in the lake trial.

Due to the high cost of sea trials and the variability of sea states, the duration of experiments is usually too short to fully verify underwater acoustic communication (UAC) performance in a real-ocean environment. Moreover, traditional UAC channel simulators also face issues of inaccurate environmental parameters or mismatched statistical models. To tackle these challenges, we propose UACC-GAN, a data-driven stochastic channel simulator for UAC, offering an innovative solution for channel data augmentation. UACC-GAN uses the generative adversarial network model to learn the latent space of the measured channel data set and then maps the random sampling points in this space into a new time-varying impulse response (TVIR). Our simulator is validated using the small-scale WATERMARK data set collected at sea. The results indicate that the generated TVIR has a realistic delay–Doppler spread and can reproduce time-varying delay path characteristics. The cumulative distribution of multiple 0-D properties also proves the realism of the entire distribution of the generated channel data set. In addition, by relying on the continuity of the latent space, UACC-GAN generates channel characteristics with random fluctuations, such as Doppler spectrum shape, delay energy distribution, and tap covariance, which contributes to more diverse communication testing conditions. Finally, we pass frequency-hopping spread spectrum and orthogonal frequency-division multiplexing communication signals through the generated and measured channels. The comparable results of simulated bit error rate (BER) and actual BER underline the value of the UACC-GAN simulator for communication system design and testing.

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.

To improve the throughput of underwater acoustic (UWA) networking, the In-band full-duplex (IBFD) communication is one of the most vital pieces of research. The major drawback of IBFD-UWA communication is Self-Interference (SI). This paper presents a digital SI cancellation algorithm for asynchronous IBFD-UWA communication system. We focus on two issues: one is asynchronous communication dissimilar to IBFD radio communication, the other is nonlinear distortion caused by power amplifier (PA). First, we discuss asynchronous IBFD-UWA signal model with the nonlinear distortion of PA. Then, we design a scheme for asynchronous IBFD-UWA communication utilizing the non-overlapping region between SI and intended signal to estimate the nonlinear SI channel. To cancel the nonlinear distortion caused by PA, we propose an Over-Parameterization based Recursive Least Squares (RLS) algorithm (OPRLS) to estimate the nonlinear SI channel. Furthermore, we present the OPRLS with a sparse constraint to estimate the SI channel, which reduces the requirement of the length of the non-overlapping region. Finally, we verify our concept through simulation and the pool experiment. Results demonstrate that the proposed digital SI cancellation scheme can cancel SI efficiently.