Keywords :
Beaulieu-Xie (Be-Xi) distributed channels; cooperative destination jamming; energy harvesting; hybrid heuristic optimization algorithm; secrecy performance; uncrewed aerial vehicle (UAV); Beaulieu-xie distributed channel; Cooperative destination jamming; Distributed channels; Energy; Heuristic optimization algorithms; Hybrid heuristic optimization algorithm; Hybrid heuristics; Performance; Secrecy performance; Uncrewed aerial vehicle; Uncrewed aerial vehicles; Electronic, Optical and Magnetic Materials; Control and Systems Engineering; Aerospace Engineering; Transportation; Electrical and Electronic Engineering
Abstract :
[en] Uncrewed aerial vehicles (UAVs) have emerged as a state-of-the-art solution for establishing communication in remote and obstructed areas. However, before UAVs can be integrated into existing communication infrastructure, it is essential to address the energy constraints and security concerns arising from their line-of-sight links. This article focuses on a UAV-enabled communication system in which a UAV relay facilitates information transfer from the source to the destination nodes when the direct link is heavily shadowed or obstructed. A nearby terrestrial passive eavesdropper can intercept information transmitted through the source-to-UAV and UAV-to-destination links. To address this, we utilize destination-aided cooperative jamming. Additionally, we consider simultaneous wireless information and power transfer (SWIPT) at the UAV to provide the energy required for data transmission. In particular, the UAV utilizes a hybrid-SWIPT technique to harvest energy from the radio-frequency signals. For this setup, we derive accurate expressions of secrecy outage probability and system secrecy throughput (SST) over Beaulieu-Xie distributed channels. Using the SST expression, we formulate an SST maximization problem to jointly optimize the transmit powers, power allocation, SWIPT coefficients, and UAV's 3-D position. The formulated problem is solved using the hybrid heuristic framework, combining continuous genetic and particle swarm optimization algorithms. Numerical results demonstrate the significant enhancement in information secrecy of the system with the proposed hybrid scheme and also provide valuable insights into the system's behavior.
Funding text :
Received 19 November 2024; revised 20 March 2025; accepted 6 May 2025. Date of publication 9 May 2025; date of current version 25 August 2025. This work was supported in part by the Mathematical Research Impact Centric Support (MATRICS) Grant from SERB DST, Government of India under Project MTR/2022/000035, and in part by the Slovak Research and Development Agency under Project APVV-23-0512. (Corresponding author: Devendra Singh Gurjar.) Gaurav Kumar Pandey and Devendra Singh Gurjar are with the Department of Electronics and Communication Engineering, National Institute of Technology Silchar, Silchar 788010, India (e-mail: gaurav_rs@ece.nits.ac.in; dsgurjar@ece.nits.ac.in).
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