基于前馈神经网络的非合作PCMA信号盲分离算法

doi:10.3969/j.issn.0372-2112.2019.02.007

电子学报 ›› 2019, Vol. 47 ›› Issue (2): 302-307.DOI: 10.3969/j.issn.0372-2112.2019.02.007

基于前馈神经网络的非合作PCMA信号盲分离算法

郭一鸣¹, 彭华¹, 杨勇²

1. 解放军信息工程大学信息系统工程学院, 河南郑州 450002;
2. 61886部队, 北京 100084

收稿日期:2018-01-11 修回日期:2018-06-12 出版日期:2019-02-25
- 通讯作者:
- 郭一鸣
- 作者简介:
- 彭华男,1973年8月出生,江西萍乡人.教授,博士生导师.主要研究方向为软件无线电、通信信号处理等;杨勇男,1988年2月出生,云南大理人,博士.研究方向为航天信号分析处理.
- 基金资助:
- 国家自然科学基金 (No.61401511，No.U1736107）

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

GUO Yi-ming¹, PENG Hua¹, YANG Yong²

1. PLA Information Engineering University, Zhengzhou, Henan 450002, China;
2. 61886 Troops of PLA, Beijing 100084, China

Received:2018-01-11 Revised:2018-06-12 Online:2019-02-25 Published:2019-02-25
- Supported by:
- National Natural Science Foundation of China (No.61401511, No.U1736107)

摘要/Abstract

摘要： 针对非合作接收PCMA混合信号盲分离中高复杂度束缚，提出一种基于前馈神经网络的分离算法，通过搭建神经网络分离平台，规避传统的发送符号遍历思想，实现PCMA混合信号低复杂度高性能盲分离.仿真实验表明，神经网络能够极大挖掘信号内在信息，针对QPSK调制PCMA混合信号，在信噪比7dB时误比特率达到10^-3数量级，并伴随着较PSP分离算法算术平方根级别的复杂度降低.

关键词: 神经网络, 非合作, 成对载波多址复用, 盲分离

Abstract: 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.

Key words: neural network, non-cooperative, Paired Carrier Multiple Access (PCMA), blind separation

中图分类号:

TN911.7

郭一鸣, 彭华, 杨勇. 基于前馈神经网络的非合作PCMA信号盲分离算法[J]. 电子学报, 2019, 47(2): 302-307.

GUO Yi-ming, PENG Hua, YANG Yong . Blind Separation Algorithm for Non-cooperative PCMA Signal Based on Feedforward Neural Network[J]. Acta Electronica Sinica, 2019, 47(2): 302-307.

参考文献

[1] Dankberg M.Paired carrier multiple access (PCMA)for satellite communication[A].Pacific Telecommunications Conference[C].Honolulu,Hawaii,1998.787-791.
[2] Li F,Jafarkhani H.Interference cancellation and detection for more than two users[J].International Journal of Engineering Research & Applications,2014,4(1):901-910.
[3] WuC L,Liu Z,Wang X,et al.Single-channel blind source separation of co-frequency overlapped GMSK signals under constant-modulus constraints[J].IEEE Commun Lett,2016,20(3):486-489.
[4] 付迪,高勇.非对称PCMA卫星信号的截获方法[J].现代电子技术,2007,7(7):28-30. Fu D,Gao Y.Signal interception method for asymmetric PCMA satellite communication system[J].Modern Electronic Technique,2007,7(7):28-30.(in Chinese)
[5] RuderMA,Lehmann A,Schober M R,et al.Single antenna interference cancellation for GSM/VAMOS/EDGE using L_p-norm detection and decoding[J].IEEE Transactions on Wireless Communications,2015,14(5):2413-2425.
[6] 万坚,许华,朱中梁.基于独立分量分析的成对载波多址分离新算法[J].通信学报,2006,27(8):41-44. Wan J,Xu H,Zhu Z L.Separation algorithm of paired carrier multiple access based on independent component analysis[J].Journal on Communications,2006,27(8):41-44.
[7] Liu K,Li H,Dai X,et al.Single channel blind separation of cofrequency MPSK signal[A].Communication Internet and Information Technology[C].USA,2006.42-46.
[8] Tu S L,Chen S H,Zheng H,et al.Particle filtering based single-channel blind separation of co-frequency MPSK signals[A].Proceedings of 2007 International Symposium on Intelligent Signal Processing and Communication Systems[C].Xiamen,China,2007.582-585.
[9] Tu S L,Chen S H,Zheng H,et al.On the performance of single-channel blind separation of two co-frequency MPSK signals[C].2007 IEEE Region 10 Conference TENCON,Penang,Malaysia,2007.1-4.
[10] Tu S L,Zheng H,Gu N.Single-channel blind separation of two QPSK signals using per-survivor processing[C].IEEE Asia Pacific Conference on Circuits and Systems,Macao,China,2008.473-476.
[11] 杨勇,张冬玲,彭华,等.利用Gibbs采样的同频混合信号单通道盲分离[J].通信学报,2015,36(4):156-162. Yang Y,Zhang D L,Peng H,et al.Single-channel blind separation of co-frequency modulated signals based on Gibbs sampler[J].Journal on Communications,2015,36(4):156-162.(in Chinese)
[12] Erkelens J,Hendriks R,Heusdens R,et al.Minimum mean-square error estimation of discrete Fourier coefficients with generalized gamma priors[J].IEEE Trans Audio,Speech,Lang Process,2007,15(6):1741-1752.
[13] Hendriks R,Heusdens R,Jensen J.MMSE based noise PSD tracking with low complexity[A].ICASSP[C].Dallas,Texas,USA,2010.4266-4269.
[14] Chen J,Wang Y,Wang D.A feature study for classification-based speech separation at very low signal-to-noise ratio[A].ICASSP[C].Florence,Italy,2014.39-43.
[15] 廖灿辉,周世东,朱中梁.基于最大似然的同频混合信号联合定时估计算法[J].系统工程与电子技术,2010,32(6):1121-1124. Liao C H,Zhou S D,Zhu Z L.ML-based joint timing estimation algorithm for co-frequency signals[J].Systems Engineering and Electronics,2010,32(6):1121-1124.(in Chinese)
[16] 芮国胜,徐彬,张嵩.单通道混合信号的幅度估计算法[J].通信学报,2011,32(12):82-87. Rui G S,Xu B,Zhang S.Amplitude estimation algorithm for single channel mixing signals[J].Journal on Communications,2011,32(12):82-87.(in Chinese)
[17] 万坚,涂世龙,廖灿辉等.通信混合信号盲分离理论与技术[M].北京:国防工业出版社,2012. Wan J,Tu S L,Liao C H,et al.Theory and Technology on Blind Source Separation of Communication Signals[M].Beijing:National Defense Industry Press,2012.(in Chinese)
[18] 杨勇,张冬玲,彭华,等.单通道高阶调制线性混合信号的频偏估计[J].电子学报,2015,43(1):160-165. Yang Y,Zhang D L,Peng H,et al.Frequency offset estimation in single-channel linear mixture of high-order modulated signals[J].Acta Electronica Sinica,2015,43(1):160-165.(in Chinese)
[19] 魏雪娟,等.PCMA系统中干扰信号的频偏与时延联合估计[J].通信学报,2017,38(2):173-182. Wei X J,et al.Joint estimation of interference frequency offset and time delay in PCMA system[J].Journal on Communications,2017,38(2):173-182.(in Chinese)
[20] Wang Yuxuan,Narayanan Arun,Wang Deliang.On training targets for supervised speech separation[J].IEEE/ACM Trans Audio Speech Lang Process,2014,22(12):1849-1858.

基于前馈神经网络的非合作PCMA信号盲分离算法

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

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