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| DOI | 10.1007/978-3-031-67162-3_5 | ||
| Año | 2024 | ||
| Tipo |
Citas Totales
Autores Afiliación Chile
Instituciones Chile
% Participación
Internacional
Autores
Afiliación Extranjera
Instituciones
Extranjeras
To explore the use of intelligent reflecting surface (IRS) technology to improve target detection in an integrated sensing and communication (ISAC) system, this paper investigates the joint active and passive beamforming design for ISAC system equipped with IRS. An optimization problem is formulated to maximize the signal-to-noise ratio (SNR) at the base station (BS) while ensuring a minimum signal-to-interference-plus-noise-ratio (SINR) at each communication user (CU). An alternative algorithm is proposed to tackle this non-convex problem, and the problem is decomposed into three sub-problems. In the first sub-problem, the semi-definite relaxation (SDR) algorithm is used to solve the communication and sensing beamformers. A receive combining vector at the base station is derived from an equivalent Rayleigh-quotient problem in the second sub-problem. Lastly, the Successive Convex Approximation (SCA) based algorithm is applied to yield the IRS phase shift solution in the third sub-problem. The optimization algorithm alternates between these three steps until convergence is achieved. Simulation results demonstrate the effectiveness of the proposed beamforming algorithm, showcasing its superiority over the matched filter (MF) approach.
| Revista | ISSN |
|---|---|
| Lecture Notes Of The Institute For Computer Sciences, Social Informatics And Telecommunications Engineering | 1867-8211 |
| Ord. | Autor | Género | Institución - País |
|---|---|---|---|
| 1 | Awad, Safa | - |
Tongji University - China
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| 2 | Wang, Rui | - |
Tongji University - China
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| 3 | Soto, Ismael | - |
Universidad de Santiago de Chile - Chile
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| Fuente |
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| National Natural Science Foundation of China |
| Science and Technology Innovation Plan Of Shanghai Science and Technology Commission |
| Natural Science Foundation of Shanghai Municipality |
| Shanghai Automobile Foundation |
| Agradecimiento |
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| This work was sponsored by the National Natural Science Foundation of China under Grant 62271352, the Shanghai Science and Technology Innovation Action Plan Project No. 21220713100, the Natural Science Foundation of Shanghai under Grant 22ZR1465100, and the Shanghai Automobile Foundation under Grant 1905. |