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arXiv · 1901.02005

Deep Learning Assisted Antenna Selection in Untrusted Relay Networks

Rugui Yao·Yuxin Zhang·Shengyao Wang·Nan Qi·Theodoros A. Tsiftsis·Nikos I. Miridakis
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Abstract

This letter mainly studies the transmit antenna selection(TAS) based on deep learning (DL) scheme in untrusted relay networks. In previous work, we discover that machine learning (ML)-based antenna selection schemes have small performance degradation caused by complicated coupling relationship between achievable secrecy rate and the channel gains. To solve the issue, we here introduce deep neural network (DNN) to decouple the complicated relationship. The simulation results show the DNN scheme can achieve better decoupling and thus perform almost the same performance with conventional exhausted searching scheme.

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Rugui Yao, Yuxin Zhang, Shengyao Wang, Nan Qi, Theodoros A. Tsiftsis, Nikos I. Miridakis. 2019-01-07. Deep Learning Assisted Antenna Selection in Untrusted Relay Networks. https://arxiv.org/abs/1901.02005

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