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http://dx.doi.org/10.3837/tiis.2019.07.006

Single-channel Demodulation Algorithm for Non-cooperative PCMA Signals Based on Neural Network  

Wei, Chi (China National Digital Switching System Engineering and Technological Research Center)
Peng, Hua (China National Digital Switching System Engineering and Technological Research Center)
Fan, Junhui (China National Digital Switching System Engineering and Technological Research Center)
Publication Information
KSII Transactions on Internet and Information Systems (TIIS) / v.13, no.7, 2019 , pp. 3433-3446 More about this Journal
Abstract
Aiming at the high complexity of traditional single-channel demodulation algorithm for PCMA signals, a new demodulation algorithm based on neural network is proposed to reduce the complexity of demodulation in the system of non-cooperative PCMA communication. The demodulation network is trained in this paper, which combines the preprocessing module and decision module. Firstly, the preprocessing module is used to estimate the initial parameters, and the auxiliary signals are obtained by using the information of frequency offset estimation. Then, the time-frequency characteristic data of auxiliary signals are obtained, which is taken as the input data of the neural network to be trained. Finally, the decision module is used to output the demodulated bit sequence. Compared with traditional single-channel demodulation algorithms, the proposed algorithm does not need to go through all the possible values of transmit symbol pairs, which greatly reduces the complexity of demodulation. The simulation results show that the trained neural network can greatly extract the time-frequency characteristics of PCMA signals. The performance of the proposed algorithm is similar to that of PSP algorithm, but the complexity of demodulation can be greatly reduced through the proposed algorithm.
Keywords
Single-channel demodulation; PCMA signals; neural network; PSP algorithm;
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