Combined modulation recognition method based on clustering and support vector machine

Abstract

The invention provides a combined modulation recognition method based on clustering and a support vector machine in order to overcome the shortcoming of low modulation recognition rate of a clustering algorithm with a low signal to noise ratio. According to the method, a characteristic parameter of a modulation signal is extracted by using the clustering algorithm according to a phase shift keying / quadrature amplitude modulation (PSK / QAM) mode based on a constellation diagram; and a modulation mode for a signal is recognized through the support vector machine, so that the modulation recognition rate of a system is increased. The method comprises the following steps of: aiming at the PSK / QAM mode based on the constellation diagram, reconstructing the constellation diagram of a receiving signal by using the clustering algorithm; and obtaining an effective function value, which can reflect an outstanding difference of modulation types under different clustering central numbers, as the characteristic parameter input into the support vector machine by constructing an effectiveness evaluation function. In order to overcome the shortcoming that two common algorithms of one to multiple and one to one have high calculation complexity when the support vector machine recognizes multiple types, the support vector machine is trained by adopting a hierarchical algorithm.

Description

technical field [0001] The invention relates to an automatic modulation recognition realization scheme based on clustering and support vector machines, belonging to the technical field of communication. Background technique [0002] With the development of communication technology, communication signals adopt different modulation methods in a wide frequency band, and the modulation parameters of these signals are also different. The automatic modulation recognition of digital signals can determine the modulation mode of the signal under the condition of various modulation signals and noise interference, which plays an important role in both civil and military fields. As the system and modulation styles of communication signals become more complex and diverse, the modulation identification of communication signals is particularly important and urgent. [0003] At present, the research methods of automatic recognition of modulation modes can be divided into two categories: th...

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Problems solved by technology

[0007] However, in previous modulation recognition algorithms, such as cluster-based modulation recognition algorithms, when the signal-to-noise ratio of the received signal is low, the recognition rate of the modulation scheme is very low

So that it cannot provide a reliable basis for further signal processing, such as correct demodulation, analysis or interference

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