关键词: 全双工, 中继选择, 物理层安全, 机器学习, 集成学习, 随机森林

Abstract:

Using the ensemble learning algorithm to solve the secure relay selection problem can reduce the real-time processing delay and computational complexity, when the wireless systems that with fast-changing channel state information (CSI) or multi-hop relay situation. The secure relay selection problem of a full-duplex relay system is modeled as a multi-class classification problem, which is solved by the random forest (RF) algorithm. The CSI of the legitimate channel and eavesdropping channel is taken as the input of the training model, and the index of the relay node which can maximize the system security capacity is taken as the output of the training model. The implementation of the proposed scheme is divided into three phases: training data preparation, model building and result prediction. In the training data preparation phase, as the input features demanded by the RF algorithm are discrete values, feature extraction methods based on both uniform and non-uniform quantization algorithms are proposed to transform the CSI into finite discrete values. Finally, simulation experiments are conducted to verify the performance of the proposed scheme.

Key words: full-duplex, relay selection, physical layer security, machine learning, ensemble learning, random forest