Resource allocation algorithm for downlink secure transmission in wireless EH cooperative networks with idle relay-assisted jamming^☆

Abstract

In wireless Energy Harvesting (EH) cooperative networks, we investigate the problem of secure energy-saving resource allocation for downlink physical layer security transmission. Initially, we establish a model for a multi-relay cooperative network incorporating wireless energy harvesting, spectrum sharing, and system power constraints, focusing on physical layer security transmission in the presence of eavesdropping nodes. In this model, the source node transmits signals while injecting Artificial Noise (AN) to mitigate eavesdropping risks, and an idle relay can act as a jamming node to assist in this process. Based on this model, we formulate an optimization problem for maximizing system secure harvesting energy efficiency, this problem integrates constraints on total power, bandwidth, and AN allocation. We proceed by conducting a mathematical analysis of the optimization problem, deriving optimal solutions for secure energy-saving resource allocation, this includes strategies for power allocation at the source and relay nodes, bandwidth allocation among relays, and power splitting for the energy harvesting node. Thus, we propose a secure resource allocation algorithm designed to maximize secure harvesting energy efficiency. Finally, we validate the correctness of the theoretical derivation through Monte Carlo simulations, discussing the impact of parameters such as legitimate channel gain, power splitting factor, and the number of relays on secure harvesting energy efficiency of the system. The simulation results show that the proposed secure energy-saving resource allocation algorithm effectively enhances the security performance of the system.

Keywords

Wireless cooperative network / Physical layer security / Energy harvesting / Resource allocation / Spectrum sharing / Secure energy efficiency

CRediT authorship contribution statement

Xintong Zhou: Writing - review & editing, Writing - original draft, Methodology, Investigation. Kun Xiao: Writing - review & editing, Supervision, Data curation. Feng Ke: Supervision, Resources, Project administration.

Declaration of Competing Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgements

This work was supported by the National Natural Science Foundation of China (NSFC) [grant numbers 62171188]; the Guangdong Provincial Key Laboratory of Human Digital Twin [Grant 2022B1212010004].

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