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Modulation identification method under MIMO related channel based on machine learning algorithm

A technology of machine learning and modulation recognition, applied in the field of communication, can solve the problem of difficulty in signal recognition at the receiving end

Active Publication Date: 2016-10-26
BEIJING UNIV OF POSTS & TELECOMM
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AI Technical Summary

Problems solved by technology

In the multi-antenna MIMO correlation channel, due to the existence of antenna correlation, multipath delay, and channel noise, it brings difficulties to signal identification at the receiving end
In particular, the existence of antenna correlation has brought a severe test to the signal modulation recognition at the receiving end

Method used

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  • Modulation identification method under MIMO related channel based on machine learning algorithm
  • Modulation identification method under MIMO related channel based on machine learning algorithm
  • Modulation identification method under MIMO related channel based on machine learning algorithm

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Embodiment Construction

[0108] The present invention will be further described in detail below in conjunction with the accompanying drawings.

[0109] A modulation recognition method under MIMO correlation channel based on machine learning algorithm, such as figure 1As shown, an extreme learning machine is designed and applied to verify the performance of the channel. Firstly, the modulating signal is divided into three categories, φ 1 ={BPSK,QPSK,8PSK},φ 2 ={16QAM,64QAM},φ 3 ={φ 1 ,φ 2}; where φ 1 and φ 2 represent signals of the same category, φ 3 Represents different types of mixed signals; secondly, the signal is passed through the MIMO related channel, and the parameter characteristics of the signal are extracted at the receiving end; finally, the machine learning algorithm completes the modulation classification of the signal. The invention verifies the system performance of the machine learning algorithm under signal blind identification, multipath effect caused by MIMO channel and dif...

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Abstract

A modulation identification method under an MIMO related channel based on a machine learning algorithm of the invention belongs to the field of communication. The method comprises the specific steps as follows: first, space-time coding is performed on each data flow of a communication transmitter, and code words are emitted out through Nt transmitting antennas; then, a correlation matrix (as shown in the description) of a receiver and a correlation matrix (as shown in the description) of the transmitter are received, and an MIMO channel matrix H is calculated; the received signal on each receiving antenna is calculated according to the MIMO channel matrix H and corrected; and finally, each receiving antenna extracts the features of the corresponding corrected signal, training test is performed on the extracted feature values, and a modulation identification mode to which a sample belongs is calculated. The advantages are as follows: the method has strong robustness and generalization ability to non-Gaussian channels, and modulation system identification under a more complex environment can be realized through parameter iteration; and by extracting high-order moment and high-order cumulant features, the signal feature difference is obvious under high signal-to-noise ratio, and the classification of a machine learning algorithm is facilitated.

Description

technical field [0001] The invention belongs to the field of communication, in particular to a modulation recognition method under a MIMO related channel based on a machine learning algorithm. Background technique [0002] In wireless communication, in order to make full use of communication resources, communication signal systems and modulation styles are becoming more and more diverse and complex, resulting in constant changes in the communication environment. Modulation. In many applications, it is necessary to monitor the activity of communication signals, distinguish the nature of the signals, and even intercept the transmitted information content; for example, in civil applications, relevant functional departments need to monitor civilian communication signals to achieve interference identification and electromagnetic spectrum management. In military applications, the communications intelligence system, as an important means of communications electronic warfare and in...

Claims

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Application Information

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IPC IPC(8): H04L27/00H04B7/04
CPCH04B7/0413H04L27/0012
Inventor 赵成林刘晓凯王鹏彪许方敏李斌章扬
Owner BEIJING UNIV OF POSTS & TELECOMM
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