%0 Journal Article %T MPPSK通信系统中的检测与信道编码的研究
Research on Detection and Channel Coding in MPPSK Communication System %A 盛晶晶 %A 陈贤卿 %J Hans Journal of Wireless Communications %P 49-57 %@ 2163-3991 %D 2020 %I Hans Publishing %R 10.12677/HJWC.2020.105007 %X
为了尽可能地利用有限的频谱资源,本文根据多元位置相移键控(MPPSK)调制信号的特点,研究基于多分类支持向量机(SVM)的非线性方法在低阶MPPSK通信系统中的检测性能,并对SVM输入特征向量做降维处理,降低系统复杂度。为了进一步提升MPPSK系统在低信噪比下的误码率性能,本文引入低密度奇偶校验码(LDPC)作为信道编码用以抵抗信道噪声。仿真结果表明,多分类SVM非线性检测在较少的特征向量维数中,可获得最多10 dB的信噪比增益,经LDPC译码后系统性能可进一步提升8 dB。因而,在MPPSK通信系统中选择多分类SVM方法不仅可以提升检测性能,而且抗干扰能力更强,传输码率更高。
In order to make the best use of the limited spectrum resources, this paper studies the detection performance of the nonlinear method based on the multiple classification support vector machine (SVM) in the low-order multiple position phase-shift keying (MPPSK) communication system according to the characteristics of MPPSK modulated signals, and the dimension-reduction processing for the input feature vectors of SVM is performed, so that the complexity of system is reduced. In order to further improve the bit error rate performance of MPPSK system at the low signal noise rate (SNR), the low density parity check code (LDPC) is introduced by this paper as the channel coding to resist the channel noise. The simulation results have shown that the maximum SNR gain of 10 dB at the less feature vector dimensions can be obtained by the multiple classification SVM nonlinear detection, and the system performance can be further increased by the 8 dB after decoding by the LDPC. Therefore, the multiple classification SVM method is chosen in the MPPSK communication system, not only can the detection performance is improved, but also the anti-interference ability is stronger and the transmission code rate is higher.
%K 多元位置相移键控,多分类支持向量机,非线性检测,低密度奇偶校验码
M-Position Phase-Shift Keying %K Multiple Classification Support Vector Machine %K Nonlinear Detection %K Low Density Parity Check Code %U http://www.hanspub.org/journal/PaperInformation.aspx?PaperID=37988