While reinforcement learning-based underwater acoustic adaptive modulation shows promise for enabling environment-adaptive communication as supported by extensive simulation-based research,its practical performance re...While reinforcement learning-based underwater acoustic adaptive modulation shows promise for enabling environment-adaptive communication as supported by extensive simulation-based research,its practical performance remains underexplored in field investigations.To evaluate the practical applicability of this emerging technique in adverse shallow sea channels,a field experiment was conducted using three communication modes:orthogonal frequency division multiplexing(OFDM),M-ary frequency-shift keying(MFSK),and direct sequence spread spectrum(DSSS)for reinforcement learning-driven adaptive modulation.Specifically,a Q-learning method is used to select the optimal modulation mode according to the channel quality quantified by signal-to-noise ratio,multipath spread length,and Doppler frequency offset.Experimental results demonstrate that the reinforcement learning-based adaptive modulation scheme outperformed fixed threshold detection in terms of total throughput and average bit error rate,surpassing conventional adaptive modulation strategies.展开更多
Shallow-water seabed reverberation presents a critical disturbance in acoustic propagation,affecting the target detection performance of monostatic sonar.This paper proposes a novel seabed reverberation model integrat...Shallow-water seabed reverberation presents a critical disturbance in acoustic propagation,affecting the target detection performance of monostatic sonar.This paper proposes a novel seabed reverberation model integrating Gaussian beam tracing with seabed scattering physics.The model synthesizes time-domain reverberation signals by superimposing scattering signals received across multiple propagation paths.It accurately resolves scattering signals along distinct paths and enables simulation of reverberation under diverse shallow-water environments by adjusting the marine parameters.Furthermore,we model the seabed reverberation signals in the time domain and the space domain for a cylindrical transceiver array,and provide a detailed statistical characterization of the simulated seabed reverberation signals.Finally,shallow-water seabed reverberation experiments were conducted with a cylindrical transceiver array.Comparisons between shallow-water seabed reverberation measurements and simulation estimates at various sites and transceiver depths demonstrate that the proposed seabed reverberation model can efficiently simulate shallow-water seabed reverberation.展开更多
基金funding from the National Key Research and Development Program of China(No.2018YFE0110000)the National Natural Science Foundation of China(No.11274259,No.11574258)the Science and Technology Commission Foundation of Shanghai(21DZ1205500)in support of the present research.
文摘While reinforcement learning-based underwater acoustic adaptive modulation shows promise for enabling environment-adaptive communication as supported by extensive simulation-based research,its practical performance remains underexplored in field investigations.To evaluate the practical applicability of this emerging technique in adverse shallow sea channels,a field experiment was conducted using three communication modes:orthogonal frequency division multiplexing(OFDM),M-ary frequency-shift keying(MFSK),and direct sequence spread spectrum(DSSS)for reinforcement learning-driven adaptive modulation.Specifically,a Q-learning method is used to select the optimal modulation mode according to the channel quality quantified by signal-to-noise ratio,multipath spread length,and Doppler frequency offset.Experimental results demonstrate that the reinforcement learning-based adaptive modulation scheme outperformed fixed threshold detection in terms of total throughput and average bit error rate,surpassing conventional adaptive modulation strategies.
基金The Youth Project of National Natural Science Foundation of China under contract No.12304507the Natural Science Foundation of Guangdong Province,China under contract No.2024A1515011512+2 种基金the Stable Supporting Fund of Acoustic Science and Technology Laboratory under contract No.JCKYS2025SSJS010the Fundamental Research Funds for the Central Universities under contract No.20720240108the Special Project for Marine Economy Development of Guangdong Province,China under contract No.GDNRC2023-47.
文摘Shallow-water seabed reverberation presents a critical disturbance in acoustic propagation,affecting the target detection performance of monostatic sonar.This paper proposes a novel seabed reverberation model integrating Gaussian beam tracing with seabed scattering physics.The model synthesizes time-domain reverberation signals by superimposing scattering signals received across multiple propagation paths.It accurately resolves scattering signals along distinct paths and enables simulation of reverberation under diverse shallow-water environments by adjusting the marine parameters.Furthermore,we model the seabed reverberation signals in the time domain and the space domain for a cylindrical transceiver array,and provide a detailed statistical characterization of the simulated seabed reverberation signals.Finally,shallow-water seabed reverberation experiments were conducted with a cylindrical transceiver array.Comparisons between shallow-water seabed reverberation measurements and simulation estimates at various sites and transceiver depths demonstrate that the proposed seabed reverberation model can efficiently simulate shallow-water seabed reverberation.
