Active-IRS-Enabled Target Detection
This letter studies an active intelligent reflecting surface (IRS)-enabled non-line-of-sight (NLoS) target detection system, in which an active IRS equipped with active reflecting elements and sensors is strategically deployed to facilitate target detection in the NLoS region of the base station (BS) by processing echo signals through the BS-IRS-target-IRS link. First, we design an optimal detector based on the Neyman-Pearson (NP) theorem and derive the corresponding detection probability. Intriguingly, it is demonstrated that the optimal detector can exploit both the BS's transmit signal and the active IRS's reflection noise for more effective detection. Subsequently, we jointly optimize the transmit beamforming at the BS and the reflective beamforming at the active IRS to maximize the detection probability, subject to the maximum transmit power constraint at the BS, as well as the maximum amplification power and gain constraints at the active IRS. Finally, simulation results unveil that the proposed joint beamforming design significantly enhances the detection probability, with the active IRS outperforming its fully- and semi-passive counterparts in detection performance.
Code (0)
등록된 구현이 없습니다.
Methods 이 논문이 사용한 방법론
Similar Papers 제목 키워드 기반
An Overview on IRS-Enabled Sensing and Communications for 6G: Architectures, Fundamental Limits, and Joint Beamforming Designs
This paper presents an overview on intelligent reflecting surface (IRS)-enabled sensing and communication for the forthcoming sixth-generation (6G) wireless networks, in which IRSs are strategically deployed to proactive…
Integrated sensing and communicationISACparameter estimationReplay Attack Detection Based on Parity Space Method for Cyber-Physical Systems
The replay attack detection problem is studied from a new perspective based on parity space method in this paper. The proposed detection methods have the ability to distinguish system fault and replay attack, handle both…
Machine Learning-Driven Anomaly Detection for 5G O-RAN Performance Metrics
The ever-increasing reliance of critical services on network infrastructure coupled with the increased operational complexity of beyond-5G/6G networks necessitate the need for proactive and automated network fault manage…
Anomaly DetectionMulti-target Detection for Reconfigurable Holographic Surfaces Enabled Radar
Multi-target detection is one of the primary tasks in radar-based localization and sensing, typically built on phased array antennas. However, the bulky hardware in the phased array restricts its potential for enhancing …
Exploring Highly Quantised Neural Networks for Intrusion Detection in Automotive CAN
Vehicles today comprise intelligent systems like connected autonomous driving and advanced driving assistance systems (ADAS) to enhance the driving experience, which is enabled through increased connectivity to infrastru…
Autonomous DrivingIntrusion DetectionMulti-class Classification