Physical layer identity authentication method based on deep support vector description method
An identity authentication and support vector technology, applied in neural learning methods, climate sustainability, sustainable communication technology, etc., can solve problems such as key leakage, increase communication resources and computing resource consumption, and decipher ciphertext.
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[0055] The physical layer identity authentication based on the deep support vector description method in the present invention is described by taking a communication scenario including one legal information sender, one legal information receiver and three attackers as an example. In this example, the number of transmit antennas of the MIMO-OFDM communication system is N T = 2, the number of receiving antennas N R =2, the number of subcarriers N S = 256. The time delay of each path and the fading at all levels of the multipath fading channel are shown in Table 1, and the signal-to-noise ratio is 1 dB.
[0056] It includes the following steps:
[0057] Step 1: Collect CSI data between legal users at T (in this example, T=2000) times as a training data set, where each record is the CSI data at time t (t=1, 2,...T) , called a training sample. The T value determines the number of training samples. Too few training samples will reduce the generalization ability of the authentic...
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