寬帶無線電通信信號中的調(diào)制識別
發(fā)布時間：2019-01-29 05:17
【摘要】：在快速發(fā)展的無線通信技術(shù)領(lǐng)域,通信體制不斷發(fā)展更新,通信信號的調(diào)制方式日益增加;以及各種通信之間相互干擾,通信環(huán)境日益復雜,因此,調(diào)制信號的自動調(diào)制識別技術(shù)在通信領(lǐng)域應用是非常廣泛的,這其中包括在民用方面的應用和軍事領(lǐng)域的應用,尤其是在非協(xié)作通信過程中,調(diào)制識別過程是必不可少的。此外,在衛(wèi)星通信中,大多數(shù)采用MPSK(M-ary Phase Shift Keying)與MQAM(M-ary Quadrature Amplitude Modulation)等調(diào)制信號進行信息的傳遞,因此,這兩類信號的類內(nèi)調(diào)制識別是本文中的重點。本文主要對數(shù)字信號調(diào)制識別算法進行研究,對比各種調(diào)制識別算法的優(yōu)缺點,結(jié)合現(xiàn)有的各種算法提出了能高效地對MPSK與MQAM信號進行類內(nèi)識別的算法。本文主要分為如下四個部分:首先,對數(shù)字信號的調(diào)制識別過程進行介紹,目前調(diào)制識別的基本方式是基于模式識別的方法或者決策論的算法。其次,分析研究目前各種有關(guān)調(diào)制識別的基本方法,包括:基于時域特征參數(shù)提取的算法、基于最大似然估計的算法、基于幅度矩的算法、基于小波變換的算法,并對各種方法進行仿真。根據(jù)仿真結(jié)果進行比較,分析目前各方法的優(yōu)缺點。然后,主要對MPSK信號的類內(nèi)調(diào)制識別算法進行研究,在對各種算法的有效性進行對比之后,采用基于神經(jīng)網(wǎng)絡(luò)分類器的方法對信號進行調(diào)制識別。這種算法中,采用信號的高階累積量作為識別的特征參數(shù),分類器采用基于BP神經(jīng)網(wǎng)絡(luò)的分類器。仿真結(jié)果表明,此算法具有很好的抗噪聲性能,在低信噪比下,對BPSK、QPSK、8PSK、16PSK等信號有很高的識別效率。最后,對MQAM信號的類內(nèi)識別算法進行研究。主要采用了兩種算法對MQAM信號進行類內(nèi)識別:基于星座圖聚類的算法、基于幅度值最大似然估計的方法。仿真結(jié)果表明,基于星座圖聚類的算法在一定信噪比情況下,能有效識別4QAM、16QAM、32QAM、64QAM、128QAM、256QAM;而對矩形星座圖的MQAM,采用最大似然估計的方法可以實現(xiàn)低信噪比下的調(diào)制識別。
[Abstract]:In the field of rapid development of wireless communication technology, the communication system is constantly developing and updating, and the modulation mode of communication signal is increasing day by day. And the communication environment is becoming more and more complex, so the automatic modulation recognition technology of modulated signals is widely used in the field of communication, including civil applications and military applications. Especially in the process of non-cooperative communication, modulation recognition is essential. In addition, in satellite communication, MPSK (M-ary Phase Shift Keying) and MQAM (M-ary Quadrature Amplitude Modulation) and other modulation signals are mostly used to transmit information. Therefore, the in-class modulation recognition of these two kinds of signals is the focus of this paper. In this paper, the modulation recognition algorithms of digital signals are studied, and the advantages and disadvantages of various modulation recognition algorithms are compared. Combined with the existing algorithms, an algorithm which can efficiently identify the MPSK and MQAM signals within the class is proposed. This paper is divided into four parts as follows: firstly, the modulation recognition process of digital signal is introduced. At present, the basic method of modulation recognition is based on pattern recognition or the algorithm of decision theory. Secondly, the basic methods of modulation recognition are analyzed and studied, including the algorithm based on time domain feature parameter extraction, the algorithm based on maximum likelihood estimation, the algorithm based on amplitude moment, and the algorithm based on wavelet transform. Various methods are simulated. According to the simulation results, the advantages and disadvantages of the current methods are analyzed. Then, this paper mainly studies the algorithm of intra-class modulation recognition of MPSK signal. After comparing the effectiveness of various algorithms, the method based on neural network classifier is used to identify the signal. In this algorithm, the high order cumulant of the signal is used as the feature parameter, and the classifier is based on the BP neural network. The simulation results show that the algorithm has good anti-noise performance and has high recognition efficiency for BPSK,QPSK,8PSK,16PSK signals under low SNR. Finally, the algorithm of MQAM signal recognition in class is studied. Two kinds of algorithms are mainly used to identify MQAM signals: constellation clustering algorithm and amplitude maximum likelihood estimation method. Simulation results show that the algorithm based on constellation clustering can effectively identify 4QAM16QAM-32QAM-64QAM-128QAM-256QAMunder a certain SNR. The maximum likelihood estimation (MLE) method for the MQAM, of the rectangular constellation can be used to realize the modulation recognition at low signal-to-noise ratio (SNR).
【學位授予單位】：電子科技大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：TN911.3
本文編號：2417683
[Abstract]:In the field of rapid development of wireless communication technology, the communication system is constantly developing and updating, and the modulation mode of communication signal is increasing day by day. And the communication environment is becoming more and more complex, so the automatic modulation recognition technology of modulated signals is widely used in the field of communication, including civil applications and military applications. Especially in the process of non-cooperative communication, modulation recognition is essential. In addition, in satellite communication, MPSK (M-ary Phase Shift Keying) and MQAM (M-ary Quadrature Amplitude Modulation) and other modulation signals are mostly used to transmit information. Therefore, the in-class modulation recognition of these two kinds of signals is the focus of this paper. In this paper, the modulation recognition algorithms of digital signals are studied, and the advantages and disadvantages of various modulation recognition algorithms are compared. Combined with the existing algorithms, an algorithm which can efficiently identify the MPSK and MQAM signals within the class is proposed. This paper is divided into four parts as follows: firstly, the modulation recognition process of digital signal is introduced. At present, the basic method of modulation recognition is based on pattern recognition or the algorithm of decision theory. Secondly, the basic methods of modulation recognition are analyzed and studied, including the algorithm based on time domain feature parameter extraction, the algorithm based on maximum likelihood estimation, the algorithm based on amplitude moment, and the algorithm based on wavelet transform. Various methods are simulated. According to the simulation results, the advantages and disadvantages of the current methods are analyzed. Then, this paper mainly studies the algorithm of intra-class modulation recognition of MPSK signal. After comparing the effectiveness of various algorithms, the method based on neural network classifier is used to identify the signal. In this algorithm, the high order cumulant of the signal is used as the feature parameter, and the classifier is based on the BP neural network. The simulation results show that the algorithm has good anti-noise performance and has high recognition efficiency for BPSK,QPSK,8PSK,16PSK signals under low SNR. Finally, the algorithm of MQAM signal recognition in class is studied. Two kinds of algorithms are mainly used to identify MQAM signals: constellation clustering algorithm and amplitude maximum likelihood estimation method. Simulation results show that the algorithm based on constellation clustering can effectively identify 4QAM16QAM-32QAM-64QAM-128QAM-256QAMunder a certain SNR. The maximum likelihood estimation (MLE) method for the MQAM, of the rectangular constellation can be used to realize the modulation recognition at low signal-to-noise ratio (SNR).
【學位授予單位】：電子科技大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：TN911.3
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