On the Performance of the Relay Selection in Multi-hop Cluster-based Wireless Networks with Multiple Eavesdroppers Under Equally Correlated Rayleigh Fading

Authors

  • Pham Minh Nam Industrial University of Ho Chi Minh City image/svg+xml
  • Phong Ngo Dinh Posts and Telecommunications Institute of Technology
  • Nguyen Luong Nhat Posts and Telecommunications Institute of Technology
  • Tu Lam-Thanh Ton Duc Thang University image/svg+xml
  • Thuong Le-Tien Ho Chi Minh City University of Technology image/svg+xml

DOI:

https://doi.org/10.4108/eetinis.v11i3.4728

Keywords:

Eavesdroppers, Equally Correlated Rayleigh Fading, Multi-hop Wireless Networks, Power Allocation, Outage Probablity

Abstract

The performance of multi-hop cluster-based wireless networks under multiple eavesdroppers is investigated in the present work. More precisely, we derive the outage probability (OP) of the considered networks under two relay selection schemes: the channel-gain-based scheme and the random scheme. Although equally correlated Rayleigh fading is taken into consideration, the derived mathematical framework remains tractable. Specifically, we represent the exact expression of the OP under the channel-based scheme in series form, while the OP under the random scheme is computed in a closed-form expression. Additionally, we propose a novel power allocation for each transmitter that strictly satisfies the given intercept probability. Numerical results based on the Monte Carlo method are provided to verify the correctness of the derived framework. These results are also used to identify the influences of various parameters, such as the number of clusters, the number of relays per cluster, and the transmit power.

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Published

02-05-2024

How to Cite

Minh Nam, P., Ngo Dinh, P., Luong Nhat, N., Lam-Thanh, T., & Le-Tien, T. (2024). On the Performance of the Relay Selection in Multi-hop Cluster-based Wireless Networks with Multiple Eavesdroppers Under Equally Correlated Rayleigh Fading. EAI Endorsed Transactions on Industrial Networks and Intelligent Systems, 11(3). https://doi.org/10.4108/eetinis.v11i3.4728