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中文核心期刊

FANG Tao, HUA Bo, WEI Jiali, WANG Kai, LIU Jin, WANG Biao. Non-cooperative underwater acoustic OFDM intra-class modulation recognition based on subcarrier channel model blind equalization[J]. ACTA ACUSTICA, 2024, 49(5): 1061-1072. DOI: 10.12395/0371-0025.2023059
Citation: FANG Tao, HUA Bo, WEI Jiali, WANG Kai, LIU Jin, WANG Biao. Non-cooperative underwater acoustic OFDM intra-class modulation recognition based on subcarrier channel model blind equalization[J]. ACTA ACUSTICA, 2024, 49(5): 1061-1072. DOI: 10.12395/0371-0025.2023059

Non-cooperative underwater acoustic OFDM intra-class modulation recognition based on subcarrier channel model blind equalization

  • In order to address the problem of insufficient robustness in the traditional orthogonal frequency division multiplexing (OFDM) intra-class modulation recognition features within underwater acoustic multipath channel, which has resulted in recognition method failures, this paper studies the intra-class modulation recognition method of underwater acoustic OFDM based on blind equalization of subcarrier channel model, including BPSK, QPSK, 8PSK and 16QAM modulations. Firstly, the block strategy for OFDM subcarrier mapping symbols is proposed based on the channel characteristics. Then, the expectation maximization (EM) algorithm is employed to process the subcarrier mapping symbols within each block to estimate the channel fading coefficient and noise power under the block strategy. The K-means clustering algorithm is utilized to obtain the channel fading coefficient corresponding to the block mapping symbols, and this coefficient is used as the initial value for the EM algorithm, thereby facilitating rapid convergence. Finally, the intra-class modulation recognition of OFDM is realized by maximum likelihood (ML) classifier. The simulation and experimental results show that the proposed EM-Block-ML method can achieve highly reliable intra-class modulation recognition of OFDM in underwater acoustic multipath channel, verifying the effectiveness of the proposed recognition method.
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