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作 者:刘高辉[1] 任倩楠 LIU Gaohui;REN Qiannan(College of Automation and Information Engineering,Xi’an University of Technology,Xi’an,Shaanxi 710048,China)
机构地区:[1]西安理工大学自动化与信息工程学院,陕西西安710048
出 处:《信号处理》2021年第5期788-795,共8页Journal of Signal Processing
基 金:国家自然科学基金(61671375)。
摘 要:针对传统干扰抑制方法对正交频分复用(Orthogonal Frequency Division Multiplexing,OFDM)信号带内多路单载波通信干扰抑制难度大的问题,本文提出了一种基于学习字典和符号同步信息的干扰抑制方法。根据不同通信信号之间形态成分的差异,使用K-奇异值分解(K-Singular Value Decomposition,K-SVD)算法对OFDM信号和多路干扰信号依次进行训练,得到符合各信号特征的过完备字典,确保各信号间的有效区分。在使用过完备字典对干扰信号进行稀疏分解时,先利用符号同步信息对干扰样本信号进行符号周期分段,再利用正交匹配追踪算法(Orthogonal Matching Pursuit,OMP)算法进行稀疏分解以提高不同符号周期内干扰信号的分解精度。最后在接收端采用对消法依次对重构后的干扰信号进行抑制。仿真结果表明所提方法可有效地对2PSK和MSK、2PSK和2FSK干扰模型进行抑制,相比于传统的频域置零法可有效提升系统性能。Aiming at the difficulty of traditional interference suppression methods for orthogonal frequency division multiplexing(OFDM)signal in-band multiple single-carrier communication interference suppression,an interference suppression method based on learning dictionary and symbol synchronization information was proposed.According to the difference of morphological components between different communication signals,the K-singular value decomposition(K-SVD)algorithm was used to train the OFDM signal and multiple interference signals in turn to obtain the over-complete dictionary that met the characteristics of each signal.To ensure the effective distinction between the signals.When the over-complete dictionary was used to sparsely decompose the interference signal,first used the symbol synchronization information to segment the interference sample signal,and then used the orthogonal matching pursuit(OMP)algorithm for sparse decomposition to improve the decomposition accuracy of interference signals in different symbol periods.Finally,the cancellation method was used at the receiving end to sequentially suppress the reconstructed interference signals.The simulation results show that the proposed method can effectively suppress the interference models composed of 2PSK and MSK,2PSK and 2FSK,and can effectively improve the system performance compared with the traditional frequency domain nulling method.
分 类 号:TN973.21[电子电信—信号与信息处理]
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