Quadrature amplitude modulation within-class identification method based on image processing under multipath channel

Abstract

The invention discloses a quadrature amplitude modulation within-class identification method based on image processing under multipath channel, which mainly solves the deficiencies about low identification rate under low signal to noise ratio and requirement on large amount of stored data in the prior art, and which is implemented by the following steps: firstly recovering a received signal to a baseband; then implementing multimode equalization on a baseband sampling sequence; mapping the processed baseband sampling sequence to a complex plane and converting the baseband sampling sequence into a binary picture; extracting a characteristic quantity F1 describing image outline and a characteristic quantity F2 distinguishing 16QAM from 64QAM; and comparing the characteristic quantity F1 with a set image outlet threshold th1 to identify whether the signal is a 32QAM signal, if not, comparing the characteristic quantity F2 with a set peak height threshold th2 to identify the signal as either a 16QAM signal or a 64QAM signal. The method can realize, over 5dB, up to 97% of identification rate for MQAM within-class signal under the environment of multipath channel and low signal to noiseratio, and can be used for the necessary modulation system identification subsequent to signal detection and prior to the demodulation of signal.

Description

technical field [0001] The invention belongs to the technical field of communication, and relates to an identification method for MQAM signals of multi-ary system quadrature amplitude modulation under the condition of multi-path channel and low signal-to-noise ratio, which is applied in automatic modulation mode identification. Background technique [0002] Automatic mode recognition (AMC) refers to a technology that automatically identifies the modulation type of the signal by observing and analyzing the sampled data of the received signal in a fading channel. It is a step between signal detection and signal demodulation, and plays an important role in both military and civilian applications. However, there are few researches on intra-class recognition of MQAM signals. Most of the existing research focuses on the ideal Gaussian channel environment, and the recognition rate is not high under the condition of low signal-to-noise ratio, which cannot meet the needs of practical...

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Problems solved by technology

See Lin Yang, Zhi Ji, XiaodongXu, Xuchu Dai and Peixia Xu, "Modulation Classification In Multipath FadingEnvironments", ISWCS 2007 on 17-19 Oct.2007, pp.171-174. Using equalization technology to eliminate the influence of multi-path channels, different from the method of Paris, Lin Yang then extracted the feature quantity based on the high-order cumulative quantity for classification, which belongs to the category of pattern recognition, but the recognition rate of this method is relatively low

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