Communication signal recognition method based on subtractive clustering algorithm and fuzzy clustering algorithm

Abstract

The invention discloses a communication signal recognition method based on a subtractive clustering algorithm and a fuzzy clustering algorithm. The method comprises the following steps: initializing parameters; setting different initial neighborhood radius values for different subcarriers, and clustering constellation points of a received communication signal by the subtractive clustering algorithm; when the number of subtractive clustering centers is less than a first preset threshold, reducing a neighborhood radius and continually performing subtractive clustering; clustering the constellation points of the communication signal again by the fuzzy clustering algorithm in a way of taking a first preset threshold number of subtractive clustering centers with a higher density in the subtractive clustering centers as an initial center; specifying the initial clustering number of fuzzy clustering, evaluating the rationality of clustering in conjunction with a Xie-Beni index and a relativeradius of a clustered constellation diagram, and iterating the initial clustering number if the clustering is irrational; and comparing a relative radius with the radius of a standard constellation diagram to get the modulation way of the signal, so that a type to which a standard modulation signal belongs is the type of the communication signal.

Description

technical field [0001] The invention relates to the field of communication technology, in particular to a method for identifying communication signals based on subtractive clustering and fuzzy clustering algorithms. Background technique [0002] Modulated signal identification plays a key role in various civil and military fields, such as cognitive radio, spectrum monitoring, etc. In actual wireless communication, multipath channels will cause signal distortion, and signal identification becomes more challenging. At present, in non-cooperative communication, when identifying OFDM signals of different standard protocols, a very important step is to identify effective subcarriers of OFDM. [0003] In the research of modulation recognition based on constellation clustering and neural network, subtractive clustering and fuzzy clustering superposition are used to identify single carrier signals, and the signal can be effectively identified when SNR=15dB, but the field radius val...

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Problems solved by technology

[0005] In view of the above-mentioned deficiencies in the prior art, the communication signal identification method based on subtractive clustering and fuzzy clustering algorithms provided by the present invention solves the problems of low identification rate and high complexity of communication signal identification by existing clustering algorithms

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