Subcarrier modulation identification of underwater acoustic OFDM based on block expectation maximization and likelihood

Abstract

The low identification rate of the Orthogonal frequency division multiplexing (OFDM) based subcarrier modulation in underwater acoustic multipath channel is an important issue. Therefore, we proposed a novel Expectation Maximization-Block-Quasi Hybrid Likelihood Ratio Test (EM-Block-QHLRT) method which effectively improved the identification rate while using the blind channel impulse response (CIR) estimation and likelihood. Initially, CIR is obtained by using clustering, and then the CIR is updated iteratively by EM-Block method. Further, the subcarrier modulation is identified using QHLRT. The influence of iteration times, the length of symbol and influence of the number of blocks in EM are analyzed by using extensive simulation. The identification rate of subcarrier modulation of binary phase shift keying (BPSK), QPSK, 8PSK and 16QAM are presented using different signal noise ratio (SNR). In addition, the identification rate of subcarrier modulation based on Average Likelihood Rate Test (ALRT) as well as QHLRT with EM are compared. Simulation results showed that the identification rate of the proposed EM-Block-QHLRT method can reach to more than 90% when SNR is higher than 5 dB. Finally, the performance of the proposed EM-Block-QHLRT method is verified using sea trial data.