학술논문

Sensing-Assisted Communication in Vehicular Networks With Intelligent Surface
Document Type
Periodical
Source
IEEE Transactions on Vehicular Technology IEEE Trans. Veh. Technol. Vehicular Technology, IEEE Transactions on. 73(1):876-893 Jan, 2024
Subject
Transportation
Aerospace
Sensors
Array signal processing
Closed-form solutions
Channel estimation
Vehicle-to-everything
Fading channels
Wireless sensor networks
Intelligent surface
integrated sensing and communication
sensing-assisted communication
beamforming
phase shift design
vehicular networks
Language
ISSN
0018-9545
1939-9359
Abstract
The recent development of integrated sensing and communications (ISAC) technology offers new opportunities to meet high-throughput and low-latency communication as well as high-resolution localization requirements in vehicular networks. However, considering the limited transmit power of the road site units (RSUs) and the relatively small radar cross section (RCS) of vehicles with random reflection coefficients, the power of echo signals may be too weak to be utilized for effective target detection and tracking. Moreover, high-frequency signals usually suffer from large fading loss when penetrating vehicles, which seriously degrades the communication service quality of users inside vehicles. To handle this issue, we propose a novel sensing-assisted communication scheme by employing an intelligent omni-surface (IOS) on the surface of vehicles to enhance both sensing and communication (S&C) performance. To this end, we first propose a two-stage ISAC protocol, including the joint S&C stage and the communication-only stage, to fulfil more efficient communication performance improvements benefited from sensing. The achievable communication rate maximization problem is formulated by jointly optimizing the transmit beamforming, the IOS phase shifts, and the duration of the joint S&C stage. However, solving this ISAC optimization problem is highly non-trivial since inaccurate estimation and measurement information renders the achievable rate lack of closed-form expression. To handle this issue, we first derive a closed-form expression of the approximate achievable rate under uncertain location information, and then unveil a sufficient and necessary condition for the existence of the joint S&C stage to offer useful insights for practical system design. Moreover, two typical scenarios including interference-limited and noise-limited cases are analyzed to provide a performance bound and a low-complexity algorithm for the considered systems. Finally, simulation results demonstrate the effectiveness of the proposed sensing-assisted communication scheme in achieving a higher achievable rate with lower transmit power requirements.