A Safe Relay Selection Method Based on Random Forest Uniform Quantization Feature Extraction

Abstract

The invention belongs to the technical field of wireless communication, relates to the technical field of physical layer security, and particularly relates to a method for selecting a safe relay based on random forest uniform quantization feature extraction, including constructing a full-duplex multi-relay system model; respectively obtaining relay nodes, The reachable capacity of the destination node and the eavesdropping node, calculate the security capacity of the system under these reachable capacities, and find out the relay node index that optimizes the system security performance; extract the channel required by the RF integrated learning algorithm based on the uniform quantization algorithm Discrete eigenvalues ​​of state information; build a full-duplex relay system safety relay selection model based on RF integrated learning methods, and select relay nodes according to the model; the present invention has a full-duplex relay with multiple relay nodes In the system, the security relay selection is modeled as a multi-class classification problem, and the optimal relay is selected to improve system security performance by constructing a random forest ensemble learning algorithm model.

Description

A Secure Relay Selection Method Based on Random Forest Uniform Quantization Feature Extraction technical field The invention belongs to the technical field of wireless communication, relates to the technical field of physical layer security, and in particular relates to a A secure relay selection method for uniform quantized feature extraction in machine forests. Background technique [0002] Due to the openness of wireless signals, ensuring the safe transmission of data is an important prerequisite for the application of wireless communication systems. Wyne first proposed a new type of security technology, physical layer security technology, in 1975. such as information theory and cryptography tables By effectively utilizing the inherent random characteristics of wireless channels, such as environmental fading, path loss and environmental noise, user Interference, etc., can reduce the signal quality of malicious users eavesdropping, and through signal design and sign...

AI Technical Summary

Problems solved by technology

The integrated learning algorithm integrates multiple individual classification algorithms, which overcomes the inherent defects of low accuracy and overfitting of individual classification algorithms

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