Deep-sea acoustic communication has attracted widespread attention in recent years. Research on deep-sea acoustic communication channel characteristics is essential for the development and system design of deep-sea acoustic communication technologies. However, the structural and spatiotemporal characteristics of deep-sea high-frequency acoustic communication channels (unlike those of shallow-water acoustic communication channels) are poorly understood. Based on a channel measurement experiment in a typical deep-sea incomplete sound channel environment in the South China Sea, this paper analyzes the structural and spatiotemporal characteristics of high-frequency underwater acoustic channels in the direct-arrival and shadow zones. The channel multipath vertical structure, amplitudes of different path clusters, root mean square (RMS) delay spread, and channel temporal coherence are investigated at different depths. The randomness of different path clusters is quantified as the coefficient of variation. The channels in the shadow zone are characterized by a complex multi-path structure, high RMS delay spread, and low temporal coherence. On the contrary, the channels of the direct-arrival zone show multi-path convergence, low RMS delay spread, and high temporal coherence. Understanding the dynamic changes in these parameters can guide the statistical modeling of channels and the design of communication algorithms in different zones in deep-sea high-frequency acoustic communication scenarios.

Based on experimental data from the deep-sea sound channel axis in the Western Pacific, the statistical distribution law of cluster structure and channel delay spread characteristics are analyzed for three typical receiving depths near the sound channel axis in this paper. A ray theory-based underwater acoustic channel model is used to explain the variations in channel parameters over time and the receiving depth. The results indicate that the underwater acoustic communication channel at the channel axis depth over a 20-km range exhibits a clustered structure that depends on the emission angles of sound rays. For the amplitude characteristics, the amplitude of each cluster follows an inverse Gaussian distribution, with the maximum average amplitude observed when the receiver and transmitter depths are similar. The amplitude of each cluster fluctuation decreases as the receiving depth increases. Regarding delay spread characteristics, the delay spread of each cluster, as well as the maximum and root mean square delay spread of the channel, conform to a Gaussian mixture distribution. The mean and fluctuation of the delay spread parameters increase with the receiving depth. Variations in the cluster structure and channel delay spread characteristics above are primarily attributed to the time-varying sound speed along the propagation paths of sound rays emitted at small upward angles.

Continuous phase modulation (CPM), which is widely used in aviation telemetry and satellite communications, may help improve the performance of underwater acoustic (UWA) communication systems owing to its high spectral and power efficiency. However, applying conventional frequency-domain equalization (FDE) algorithms to CPM signals over time-varying UWA channels considerably degrades performance. Moreover, time-domain equalization algorithms often rely on excessive approximations for symbol detection, compromising overall reception. This study presents an iterative-detection–based time-domain adaptive decision feedback equalization (ID-TDADFE) algorithm that tracks channel variations through symbol-by-symbol detection. The symbol detection in ID-TDADFE fully considers the inherent coding gain of CPM signals can be cascaded with an adaptive equalizer, and enhances symbol detection performance by utilizing joint probability estimation. Numerical simulations with minimum-shift keying (MSK) and Gaussian MSK signals demonstrated that ID-TDADFE significantly improved communication performance over a time-varying UWA channel within one or two iterations. In a sea trial for experimental verification, ID-TDADFE reduced bit errors by 45.08% and 51.8% in the first and second iterations, respectively, compared to FDE.

The continuous phase modulation (CPM) technique is an excellent solution for underwater acoustic (UWA) channels with limited bandwidth and high propagation attenuation. However, the severe intersymbol interference is a big problem for the algorithm applying in shallow water. To solve this problem, an algorithm for prefiltered single-carrier frequency-domain equalization (PF-SCFDE) is presented in this paper. The regular whitening filter is replaced by a prefilter in the proposed algorithm. The output information sequence of this prefilter contains the forward information. To improve the performance, the output of the equalizer, combined with the forward information, is used to make the maximum likelihood estimation. The simulation results with minimum-shift keying and Gaussian-filtered minimum-shift keying signals over shallow water acoustic channels with low root mean square delay spread demonstrate that PF-SCFDE outperformed the traditional single-carrier frequency-domain equalization (SCFDE) by approximately 1 dB under a bit error rate (BER) of 10⁻⁴. A shallow sea trial has demonstrated the effectiveness of PF-SCFDE; PF-SCFDE had a reduction in BER of 18.35% as compared to the traditional SCFDE.

The underwater acoustic (UWA) communication system is characterized by limited bandwidth, while continuous phase modulation (CPM) offers a constant envelope, improving power and spectrum utilization efficiency. However, severe inter-symbol interference (ISI) poses a significant challenge in CPM-based UWA communication. Traditional CPM frequency domain equalization (FDE) combined with simple phase detection neglects the inherent coding gain from CPM, leading to performance degradation. Although Viterbi detection provides high performance, its complexity makes it unsuitable for computationally constrained UWA systems. This paper proposes a symbol detection algorithm based on posterior probabilities combined with FDE (PS-FDE). PS-FDE improves CPM signal detection performance by effectively separating information, applying delay, and performing multiple rounds of information merging. Simulations using minimum shift keying (MSK) and Gaussian MSK signals demonstrate significant performance improvement in just a few iterations over UWA channels. A sea trial further validates the algorithm, showing a 15.83% reduction in bit error rate after three information mergings.

In underwater acoustic (UWA) communications, direct-sequence spread spectrum (DSSS) employing a Rake receiver (Rake-DSSS) is a fundamental system. However, its performance is highly susceptible to the characteristics of the UWA channel. Accurate performance evaluation is critical for selecting optimal system parameters under diverse communication requirements. While Monte Carlo simulation (MCS) is a common evaluation method, it suffers from high computational complexity. Conversely, theoretical error probability calculations are often inaccurate due to inadequate modeling of the effective symbol energy and noise power after Rake combining. To address these limitations, this paper proposes an accurate closed-form error probability calculation method for Rake-DSSS systems (EP-RD) in complex UWA channels. EP-RD eliminates the need for computationally intensive MCS while significantly improving evaluation accuracy. This is achieved through precise corrections for symbol energy, derived from analyzing intersymbol interference under the given channel conditions, and noise power, based on analyzing noise superposition during the Rake combining process. Numerical simulations utilizing sea trial measured UWA channels demonstrate that EP-RD achieves high calculation accuracy and robustness. Specifically, the percentage error in bit error rate (BER) estimation between EP-RD and MCS is less than 1.5% at a BER of 10^-3.