paper-with-me

Papers

Power-Efficient Deceptive Wireless Beamforming Against Eavesdroppers

2025-03-06 · Georgios Chrysanidis, Antonios Argyriou, Le-Nam Tran, YanMing Zhang, Yanwei Liu

Eavesdroppers of wireless signals want to infer as much as possible regarding the transmitter (Tx). Popular methods to minimize information leakage to the eavesdropper include covert communication, directional modulation, and beamforming with nulling. In this paper we do not attempt to prevent information leakage to the eavesdropper like the previous methods. Instead we propose to beamform the wireless signal at the Tx in such a way that it incorporates deceptive information. The beamformed orthogonal frequency division multiplexing (OFDM) signal includes a deceptive value for the Doppler (velocity) and range of the Tx. To design the optimal baseband waveform with these characteristics, we define and solve an optimization problem for power-efficient deceptive wireless beamforming (DWB). The relaxed convex Quadratic Program (QP) is solved using a heuristic algorithm. Our simulation results indicate that our DWB scheme can successfully inject deceptive information with low power consumption, while preserving the shape of the created beam.

📄 PDF Abstract BibTeX arXiv:2503.04599

Code (0)

등록된 구현이 없습니다.

Similar Papers 제목 키워드 기반

Robust Multi-Beam Secure mmWave Wireless Communication for Hybrid Wiretapping Systems

2024-07-19 · Bin Qiu, Wenchi Cheng, Wei zhang

In this paper, we consider the physical layer (PHY) security problem for hybrid wiretapping wireless systems in millimeter wave transmission, where active eavesdroppers (AEs) and passive eavesdroppers (PEs) coexist to in…

valid

Deep Reinforcement Learning Based Intelligent Reflecting Surface for Secure Wireless Communications

2020-02-27 · Helin Yang, Zehui Xiong, Jun Zhao, Dusit Niyato 외

In this paper, we study an intelligent reflecting surface (IRS)-aided wireless secure communication system for physical layer security, where an IRS is deployed to adjust its surface reflecting elements to guarantee secu…

Deep Reinforcement Learningreinforcement-learningReinforcement Learning (RL)

Robust Secure Communications in Near-Field ISCAP Systems with Extremely Large-Scale Antenna Array

2025-05-21 · Zixiang Ren, Siyao Zhang, Ling Qiu, Derrick Wing Kwan Ng 외

This paper investigates robust secure communications in a near-field integrated sensing, communication, and powering (ISCAP) system, in which the base station (BS) is equipped with an extremely large-scale antenna array …

Secure Communications in Near-Filed ISCAP Systems with Extremely Large-Scale Antenna Arrays

2024-05-22 · Zixiang Ren, Siyao Zhang, Xinmin Li, Ling Qiu 외

This paper investigates secure communications in a near-field multi-functional integrated sensing, communication, and powering (ISCAP) system with an extremely large-scale antenna arrays (ELAA) equipped at the base stati…

Optimizing Model Splitting and Device Task Assignment for Deceptive Signal Assisted Private Multi-hop Split Learning

2025-07-09 · Dongyu Wei, Xiaoren Xu, Yuchen Liu, H. Vincent Poor 외 arxiv

In this paper, deceptive signal-assisted private split learning is investigated. In our model, several edge devices jointly perform collaborative training, and some eavesdroppers aim to collect the model and data informa…

Reinforcement Learning