数字通信信号调制方式自动识别技术研究
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摘要
调制方式是区分不同性质通信信号的一个重要特征。所谓调制方式的自动识别,指的是在给定一段未知调制信息的接收信号的前提下,不需要人工干预就可以判断出通信信号的调制方式,并估计出相应的调制参数。调制方式的自动识别不论是在军事应用还是民用或商业应用上都具有重大意义。
通信信号调制识别的研究已经开展了将近20年,目前已有的算法大致可以分为基于假设检验的最大似然方法和基于特征提取的模式识别方法。多数基于假设检验的最大似然类方法具有较高的计算复杂度并且对模型失配问题较为敏感,这在很大程度上限制了它们在实际通信环境中的应用;另一方面,基于特征提取的模式识别方法,通常形式简单易于实现,在适当条件下可以获得近似最优的识别性能,而且在模型失配的情况下性能较为稳健,具有较高的实用性。数字通信信号的调制方式自动识别问题直到现在仍然是一个活跃且富有挑战性的研究课题。
本文集中研究数字通信信号的调制方式自动识别问题,预期的目标是得到性能稳定、复杂度低、在实际环境中表现良好的调制识别算法。本文首先对现有算法进行了全面的总结,指出了每一类方法的特点和适用环境,以及它们存在的不足,并指出了调制识别问题的难点所在和研究方向。在此基础上,本文完成的工作主要有:
●研究了数字通信信号的谱线特征。采用不同调制方式的数字通信信号经非线性变换后,往往在频谱上呈现出不同的离散谱线特征。本文详细分析了常见数字调制方式的平方谱与四次方谱的谱线特征,从理论上推导了谱线的成因、位置和强度。仿真实验表明,信号谱线特征在不同信噪比及多径衰落信道环境下具有良好的稳健性。
●提出了一种针对恒包络数字通信信号的调制方式识别方法,其主要特点是不需要符号速率、载波初相、定时同步等先验信息,而且还能够区分线性调制和非线性调制。仿真实验表明本文的方法在较低信噪比条件下仍可以获得较高的正确识别率,具有很强的实用性。
●提出了一种多进制CPM信号的调制阶数识别方法。该方法分析了多进制CPM信号与二进制CPM信号的谱线特征之间的联系,并在此基础上实现了多进制CPM信号的调制阶数识别。
●研究高阶累量特征在调制识别问题中的应用。考察了高阶累量的估计误差性能以及影响估计性能的因素,在此基础上讨论调制识别问题中对累量形式与阶数的选择方法。
●提出了一种适用于多径衰落环境下的高阶PSK/QAM信号识别方法。该方法结合分级盲均衡处理技术对信道多径衰落效应的干扰进行有效抑制,并选择合适的累量组合形式完成调制识别。仿真实验证明,在一定信噪比条件的保证下,该方法对调制阶数较高的信号仍然可以获得近似于100%的正确识别概率。
●作为调制识别的辅助技术,提出了一种适合于全响应CPM信号的线性盲均衡与调制指数盲估计的联合算法。该算法在使用线性均衡器对CPM信号进行均衡的同时,可以对未知调制指数进行准确的估计。算法的性能在计算机仿真实验中得到验证。
●提出了一种针对单通道混合信号的调制识别方法。该方法首先分析推导了信号谱线特征与高阶累量特征在混合信号模型中的变化情况,然后在此基础上构建分类特征量,提出了针对单通道两路混合信号的调制识别方法。该方法尤其对解决PCMA信号的识别问题有重要意义。
Modulation scheme is one of the most important characteristics used to distinguish communication signals. So called automatic modulation classification (AMC) specifies that, given a received communication signal with unknown modulation information, the modulation type and relevant modulation parameters of the communication signal can be identified without any manipulation. The research of automatic modulation classification is of significance in both militarily and civilian applications.
Research on automatic modulation classification has been carried out for at least two decades, and two general classes of AMC algorithms can be crystallized, likelihood-based (LB) and feature-based (FB). The former usually suffer from computational complexity, and are sensitive to model mismatches. This limits their practical application. The FB approach, on the other hand, is simple to implement, with near-optimal performance, when designed properly, and robust to model mismatches. In general, AMC is an active and challenging task so far.
The focus of our study in this dissertation is on the automatic modulation classification of digital communication signals. The classification algorithm with robust performance, low computation complexity and high practical is expected achieved. In the dissertation, a comprehensive survey of current AMC techniques in a systematic way is provided. For different algorithms, the main characteristics are described and the bottle-necks are highlighted. Based on it, some further research topics are point out. The main contribution of this dissertation can be summarized as follows:
Spectrum line features of digital communication signals are analyzed. With the nonlinearities applied to the complex envelope of the digital communication signals, signals of different modulation schemes always manifest themselves in spectrum line feature. A complete theoretical analysis for the square and quartic spectrum line feature is carried out. The spectrum line's existence, position and amplitude are deduced. Computer simulation results indicate that the spectrum line can properly be extracted even in the serious noisy and multi-path fading environments.
A novel modulation classification approach for constant modulus digital modulation signals is proposed. The proposed approach doesn't need the prior knowledge of symbol rate, carrier phase, timing recovery, and so on, and can classify the linear and nonlinear digital modulation schemes. Simulation result illustrate that the proposed approach can achieve satisfying classification performance even when the SNR is lower, which shows the proposed approach is feasible and practical.
A modulation order recognition algorithm for M-ary CPM signals is proposed. The relationship of spectrum line feature between M-ary and binary CPM signals is deduced. Based on it, the modulation order can be recognized correctly for M-ary CPM signals.
We investigated the application of higher order cumulant in AMC. Estimation error performance and affected factors of higher order cumulant are reviewed, and the strategy of selection of cumulant order is pointed out.
A new approach to classification of higher order PSK/QAM signals in multipath fading environments is presented. The proposed approach, in which the two-step equalization strategy and higher-order cumulants based classifier are adopted, can effectively classify the PSK and higher-order QAM signals. The performance of proposed approach is evaluated by the computer simulations, which shows it has better classification ability.
As an auxiliary technique, a joint algorithm for blind equalization and modulation index estimation of full-response CPM signals is proposed. The new algorithm, based on the analysis of solutions to the traditional CM criterion with input of CPM signals, can simultaneously achieve blind equalization of channel and estimation of unknown modulation index. Simulation results illustrate the performance of the algorithm.
We proposed an effective modulation classification algorithm aimed at single-channel mixed communication signals. The diversification of cumulant and spectrum line feature of mixed signals is analyzed. Then they are utilized to active the classification of common digital modulation types. This modulation classification algorithm can help supply model information for PCMA system models.
通信信号调制识别的研究已经开展了将近20年,目前已有的算法大致可以分为基于假设检验的最大似然方法和基于特征提取的模式识别方法。多数基于假设检验的最大似然类方法具有较高的计算复杂度并且对模型失配问题较为敏感,这在很大程度上限制了它们在实际通信环境中的应用;另一方面,基于特征提取的模式识别方法,通常形式简单易于实现,在适当条件下可以获得近似最优的识别性能,而且在模型失配的情况下性能较为稳健,具有较高的实用性。数字通信信号的调制方式自动识别问题直到现在仍然是一个活跃且富有挑战性的研究课题。
本文集中研究数字通信信号的调制方式自动识别问题,预期的目标是得到性能稳定、复杂度低、在实际环境中表现良好的调制识别算法。本文首先对现有算法进行了全面的总结,指出了每一类方法的特点和适用环境,以及它们存在的不足,并指出了调制识别问题的难点所在和研究方向。在此基础上,本文完成的工作主要有:
●研究了数字通信信号的谱线特征。采用不同调制方式的数字通信信号经非线性变换后,往往在频谱上呈现出不同的离散谱线特征。本文详细分析了常见数字调制方式的平方谱与四次方谱的谱线特征,从理论上推导了谱线的成因、位置和强度。仿真实验表明,信号谱线特征在不同信噪比及多径衰落信道环境下具有良好的稳健性。
●提出了一种针对恒包络数字通信信号的调制方式识别方法,其主要特点是不需要符号速率、载波初相、定时同步等先验信息,而且还能够区分线性调制和非线性调制。仿真实验表明本文的方法在较低信噪比条件下仍可以获得较高的正确识别率,具有很强的实用性。
●提出了一种多进制CPM信号的调制阶数识别方法。该方法分析了多进制CPM信号与二进制CPM信号的谱线特征之间的联系,并在此基础上实现了多进制CPM信号的调制阶数识别。
●研究高阶累量特征在调制识别问题中的应用。考察了高阶累量的估计误差性能以及影响估计性能的因素,在此基础上讨论调制识别问题中对累量形式与阶数的选择方法。
●提出了一种适用于多径衰落环境下的高阶PSK/QAM信号识别方法。该方法结合分级盲均衡处理技术对信道多径衰落效应的干扰进行有效抑制,并选择合适的累量组合形式完成调制识别。仿真实验证明,在一定信噪比条件的保证下,该方法对调制阶数较高的信号仍然可以获得近似于100%的正确识别概率。
●作为调制识别的辅助技术,提出了一种适合于全响应CPM信号的线性盲均衡与调制指数盲估计的联合算法。该算法在使用线性均衡器对CPM信号进行均衡的同时,可以对未知调制指数进行准确的估计。算法的性能在计算机仿真实验中得到验证。
●提出了一种针对单通道混合信号的调制识别方法。该方法首先分析推导了信号谱线特征与高阶累量特征在混合信号模型中的变化情况,然后在此基础上构建分类特征量,提出了针对单通道两路混合信号的调制识别方法。该方法尤其对解决PCMA信号的识别问题有重要意义。
Modulation scheme is one of the most important characteristics used to distinguish communication signals. So called automatic modulation classification (AMC) specifies that, given a received communication signal with unknown modulation information, the modulation type and relevant modulation parameters of the communication signal can be identified without any manipulation. The research of automatic modulation classification is of significance in both militarily and civilian applications.
Research on automatic modulation classification has been carried out for at least two decades, and two general classes of AMC algorithms can be crystallized, likelihood-based (LB) and feature-based (FB). The former usually suffer from computational complexity, and are sensitive to model mismatches. This limits their practical application. The FB approach, on the other hand, is simple to implement, with near-optimal performance, when designed properly, and robust to model mismatches. In general, AMC is an active and challenging task so far.
The focus of our study in this dissertation is on the automatic modulation classification of digital communication signals. The classification algorithm with robust performance, low computation complexity and high practical is expected achieved. In the dissertation, a comprehensive survey of current AMC techniques in a systematic way is provided. For different algorithms, the main characteristics are described and the bottle-necks are highlighted. Based on it, some further research topics are point out. The main contribution of this dissertation can be summarized as follows:
Spectrum line features of digital communication signals are analyzed. With the nonlinearities applied to the complex envelope of the digital communication signals, signals of different modulation schemes always manifest themselves in spectrum line feature. A complete theoretical analysis for the square and quartic spectrum line feature is carried out. The spectrum line's existence, position and amplitude are deduced. Computer simulation results indicate that the spectrum line can properly be extracted even in the serious noisy and multi-path fading environments.
A novel modulation classification approach for constant modulus digital modulation signals is proposed. The proposed approach doesn't need the prior knowledge of symbol rate, carrier phase, timing recovery, and so on, and can classify the linear and nonlinear digital modulation schemes. Simulation result illustrate that the proposed approach can achieve satisfying classification performance even when the SNR is lower, which shows the proposed approach is feasible and practical.
A modulation order recognition algorithm for M-ary CPM signals is proposed. The relationship of spectrum line feature between M-ary and binary CPM signals is deduced. Based on it, the modulation order can be recognized correctly for M-ary CPM signals.
We investigated the application of higher order cumulant in AMC. Estimation error performance and affected factors of higher order cumulant are reviewed, and the strategy of selection of cumulant order is pointed out.
A new approach to classification of higher order PSK/QAM signals in multipath fading environments is presented. The proposed approach, in which the two-step equalization strategy and higher-order cumulants based classifier are adopted, can effectively classify the PSK and higher-order QAM signals. The performance of proposed approach is evaluated by the computer simulations, which shows it has better classification ability.
As an auxiliary technique, a joint algorithm for blind equalization and modulation index estimation of full-response CPM signals is proposed. The new algorithm, based on the analysis of solutions to the traditional CM criterion with input of CPM signals, can simultaneously achieve blind equalization of channel and estimation of unknown modulation index. Simulation results illustrate the performance of the algorithm.
We proposed an effective modulation classification algorithm aimed at single-channel mixed communication signals. The diversification of cumulant and spectrum line feature of mixed signals is analyzed. Then they are utilized to active the classification of common digital modulation types. This modulation classification algorithm can help supply model information for PCMA system models.
引文
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