Machine Learning-Based Antenna Selection in Untrusted Relay Networks

Rugui Yao, Yuxin Zhang, Nan Qi, Theodoros A. Tsiftsis, Yinsheng Liu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

This paper studies the transmit antenna selection based on machine learning (ML) schemes in untrusted relay networks. First, the exhaustive search antenna selection scheme is stated. Then, we implement three ML schemes, namely, the support vector machine-based scheme, the naïve-Bayes-based scheme, and the k-nearest neighbors-based scheme, which are applied to select the best antenna with the highest secrecy rate. The simulation results are presented in terms of system secrecy rate and secrecy outage probability. From the simulation, it can be concluded that the proposed ML-based antenna selection schemes can achieve the same performance without amplification at the relay, or small performance degradation with transmitted power constraint at the relay, comparing with exhaustive search scheme. However, when the training is completed, the proposed schemes can perform the antenna selection with a small computational complexity.

Original languageEnglish
Title of host publication2019 2nd International Conference on Artificial Intelligence and Big Data, ICAIBD 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages323-328
Number of pages6
ISBN (Electronic)9781728108315
DOIs
Publication statusPublished - May 2019
Event2nd International Conference on Artificial Intelligence and Big Data, ICAIBD 2019 - Chengdu, China
Duration: May 25 2019May 28 2019

Publication series

Name2019 2nd International Conference on Artificial Intelligence and Big Data, ICAIBD 2019

Conference

Conference2nd International Conference on Artificial Intelligence and Big Data, ICAIBD 2019
CountryChina
CityChengdu
Period5/25/195/28/19

    Fingerprint

Keywords

  • k-nearest neighbors
  • naive-Bayes
  • support vector machine
  • transmit antenna selection
  • untrusted relay networks

ASJC Scopus subject areas

  • Computer Science Applications
  • Information Systems and Management
  • Control and Optimization
  • Computer Vision and Pattern Recognition
  • Artificial Intelligence

Cite this

Yao, R., Zhang, Y., Qi, N., Tsiftsis, T. A., & Liu, Y. (2019). Machine Learning-Based Antenna Selection in Untrusted Relay Networks. In 2019 2nd International Conference on Artificial Intelligence and Big Data, ICAIBD 2019 (pp. 323-328). [8837004] (2019 2nd International Conference on Artificial Intelligence and Big Data, ICAIBD 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICAIBD.2019.8837004