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Wei-Ping Zhu

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Aug 2026

Secure Wireless Information Transfer and Energy Harvesting in HAPS-Based Networks

High-altitude platform station (HAPS) serves as a promising enabler for wide-area connectivity of low-power wireless devices, particularly in remote and underserved regions. However, the strong line-of-sight characteristics of HAPS links increase the risk of eavesdropping, while the limited energy budget of ground devices remains a major operational constraint. In this work, we propose a secure wireless information and energy harvesting framework for HAPS-based networks in the presence of spatially distributed eavesdroppers. The proposed system integrates friendly jamming and power transfer nodes equipped with null-steering capability antennas, such that they not only degrade the reception quality at eavesdroppers but also act as additional radio-frequency energy sources for legitimate users. A time-switching wireless information and power transfer architecture is adopted at the user side. Under this framework, we derive tractable expressions for the joint rate-energy coverage and the average secrecy rate using stochastic geometry tools. Numerical and Monte Carlo results validate the developed analysis and reveal key design trade-offs among the time allocation factor, null-steering-zone radius around each user, and jammer transmit power. In particular, the results show that properly coordinated null-steering jamming can simultaneously support secure communication and adequate wireless power transfer, while an appropriate choice of system parameters, such as time allocation factor and jamming power, is required to balance harvested energy, communication reliability, and secrecy performance.

Khaled M. Humadi, Günes Karabulut-Kurt, W. Ajib et al. · 0 citations
#edge computing Open access Aug 2026

Collaborative resource allocation in UAV-assisted MEC networks: A heterogeneous MAPPO scheme

This paper proposes a heterogeneous multi-agent proximal policy optimization (MAPPO)-based framework where both user devices and UAVs act as heterogeneous agents and utilizes a centralized training and decentralized execution (CTDE) paradigm to enable collaborative strategies between computing requesters and providers.

Ming Cheng, Canlin Zhu, Jiang-Hang Tang et al. · 0 citations