Blind Separation Algorithm for Non-cooperative PCMA Signal Based on Feedforward Neural Network

被引：0
|
作者：
Guo Y.-M. [1 ]
Peng H. [1 ]
Yang Y. [2 ]
机构：
[1] PLA Information Engineering University, Zhengzhou, 450002, Henan
[2] 61886 Troops of PLA, Beijing
来源：
Tien Tzu Hsueh Pao/Acta Electronica Sinica | 2019年 / 47卷 / 02期
关键词：
Blind separation; Neural network; Non-cooperative; Paired Carrier Multiple Access (PCMA);
D O I：
10.3969/j.issn.0372-2112.2019.02.007
中图分类号：
学科分类号：
摘要：
Aiming at the high complexity in blind separation of PCMA mixed signals with non-cooperative reception, the separation algorithm based on feedforward neural network is proposed. By setting up a neural network separation platform and avoiding the traditional idea of maximum a posteriori probability, the blind separation algorithm with low complexity and high performance can be realized. Simulation results show that the neural network can greatly exploit the intrinsic information of the signal, and 10-3 orders of bit error rate performance is achieved with 7 dB of signal-to-noise ratio to QPSK modulated PCMA signals, accompanied by the declining complexity of the arithmetic square root level compared with the PSP algorithm. © 2019, Chinese Institute of Electronics. All right reserved.
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页码：302 / 307
页数：5
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