Antenna Selection With Beam Squint Compensation for Integrated Sensing and Communications

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dc.authorscopusidAhmet Mete Elbir / 55362509900
dc.authorwosidAhmet Mete Elbir / X-3731-2019
dc.contributor.authorElbir, Ahmet Mete
dc.contributor.authorAbdallah, Asmaa
dc.contributor.authorÇelik, Abdülkadir
dc.contributor.authorEltawil, Ahmed M.
dc.date.accessioned2025-06-04T10:21:38Z
dc.date.available2025-06-04T10:21:38Z
dc.date.issued2024
dc.departmentİstinye Üniversitesi, Mühendislik ve Doğa Bilimleri Fakültesi, Elektrik-Elektronik Mühendisliği Bölümü
dc.description.abstractNext-generation wireless networks strive for higher communication rates, ultra-low latency, seamless connectivity, and high-resolution sensing capabilities. To meet these demands, terahertz (THz) band signal processing is envisioned as a key technology offering wide bandwidth and sub-millimeter wavelength. Furthermore, THz integrated sensing and communications (ISAC) paradigm has emerged to jointly access the spectrum and reduce the hardware costs through a unified platform. To address the challenges in THz propagation, THz-ISAC systems employ extremely large antenna arrays to improve the beamforming gain for communications with high data rates and sensing with high resolution. However, the cost and power consumption of implementing fully digital beamformers are prohibitive. While hybrid analog/digital beamforming can be a potential solution, the use of subcarrier-independent analog beamformers leads to the beam-squint phenomenon where different subcarriers observe distinct directions because of adopting the same analog beamformer across all subcarriers. In this paper, we develop a sparse array architecture for THz-ISAC with hybrid beamforming to provide a cost-effective solution. We analyze the antenna selection problem under beam-squint influence and introduce a manifold optimization approach for hybrid beamforming design. To reduce computational and memory costs, we propose novel algorithms leveraging grouped subarrays, quantized performance metrics, and sequential optimization. These approaches yield a significant reduction in the number of possible subarray configurations, which enables us to devise a neural network with classification model to accurately perform antenna selection. Numerical simulations show that the proposed approach exhibits up to 95% lower complexity for large antenna arrays while maintaining satisfactory communications with approximately 6% loss in the achievable rate. © 2024 IEEE.
dc.identifier.citationElbir, A. M., Abdallah, A., Celik, A., & Eltawil, A. M. (2024). Antenna selection with beam squint compensation for integrated sensing and communications. IEEE Journal of Selected Topics in Signal Processing.
dc.identifier.doi10.1109/JSTSP.2024.3378909
dc.identifier.endpage870
dc.identifier.issn19324553
dc.identifier.issue5
dc.identifier.scopusqualityQ1
dc.identifier.startpage857
dc.identifier.urihttp://dx.doi.org/10.1109/JSTSP.2024.3378909
dc.identifier.urihttps://hdl.handle.net/20.500.12713/7293
dc.identifier.volume18
dc.identifier.wosWOS:001394750300005
dc.identifier.wosqualityQ1
dc.indekslendigikaynakScopus
dc.indekslendigikaynakWeb of Science
dc.institutionauthorElbir , Ahmet Mete
dc.institutionauthoridAhmet Mete Elbir / 0000-0003-4060-3781
dc.language.isoen
dc.publisherInstitute of Electrical and Electronics Engineers Inc.
dc.relation.ispartofIEEE Journal on Selected Topics in Signal Processing
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectAntenna Selection
dc.subjectIntegrated Sensing and Communications
dc.subjectMachine Learning
dc.subjectMassive MIMO
dc.subjectTerahertz
dc.titleAntenna Selection With Beam Squint Compensation for Integrated Sensing and Communications
dc.typeArticle

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