Terahertz-Band Joint Ultra-Massive MIMO Radar-Communications: Model-Based and Model-Free Hybrid Beamforming

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dc.authoridChatzinotas, Symeon/0000-0001-5122-0001
dc.authoridElbir, Ahmet M./0000-0003-4060-3781
dc.authorwosidChatzinotas, Symeon/D-4191-2015
dc.authorwosidElbir, Ahmet M./X-3731-2019
dc.contributor.authorElbir, Ahmet M.
dc.contributor.authorMishra, Kumar Vijay
dc.contributor.authorChatzinotas, Symeon
dc.date.accessioned2023-07-26T11:55:08Z
dc.date.available2023-07-26T11:55:08Z
dc.date.issued2021
dc.departmentDÜ, Mühendislik Fakültesi, Elektrik-Elektronik Mühendisliği Bölümüen_US
dc.description.abstractWireless communications and sensing at terahertz (THz) band are increasingly investigated as promising short-range technologies because of the availability of high operational bandwidth at THz. In order to address the extremely high attenuation at THz, ultra-massive multiple-input multiple-output (MIMO) antenna systems have been proposed for THz communications to compensate propagation losses. However, the cost and power associated with fully digital beamformers of these huge antenna arrays are prohibitive. In this paper, we develop wideband hybrid beamformers based on both model-based and model-free techniques for a new group-of-subarrays (GoSA) ultra-massive MIMO structure in low-THz band. Further, driven by the recent developments to save the spectrum, we propose beamformers for a joint ultra-massive MIMO radar-communications system, wherein the base station serves multi-antenna user equipment (RX), and tracks radar targets by generating multiple beams toward both RX and the targets. We formulate the GoSA beamformer design as an optimization problem to provide a trade-off between the unconstrained communications beamformers and the desired radar beamformers. To mitigate the beam split effect at THz band arising from frequency-independent analog beamformers, we propose a phase correction technique to align the beams of multiple subcarriers toward a single physical direction. Additionally, our design also exploits second-order channel statistics so that an infrequent channel feedback from the RX is achieved with less channel overhead. To further decrease the ultra-massive MIMO computational complexity and enhance robustness, we also implement deep learning solutions to the proposed model-based hybrid beamformers. Numerical experiments demonstrate that both techniques outperform the conventional approaches in terms of spectral efficiency and radar beampatterns, as well as exhibiting less hardware cost and computation time.en_US
dc.description.sponsorshipERC Project AGNOSTICen_US
dc.description.sponsorshipThis work was supported in part by the ERC Project AGNOSTIC. The guest editor coordinating the review of this manuscript and approving it for publication was Dr. Christos Masouros.en_US
dc.identifier.doi10.1109/JSTSP.2021.3117410
dc.identifier.endpage1483en_US
dc.identifier.issn1932-4553
dc.identifier.issn1941-0484
dc.identifier.issue6en_US
dc.identifier.scopus2-s2.0-85119590739en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.startpage1468en_US
dc.identifier.urihttps://doi.org/10.1109/JSTSP.2021.3117410
dc.identifier.urihttps://hdl.handle.net/20.500.12684/13006
dc.identifier.volume15en_US
dc.identifier.wosWOS:000725793300017en_US
dc.identifier.wosqualityQ1en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.institutionauthorElbir, Ahmet M.
dc.language.isoenen_US
dc.publisherIeee-Inst Electrical Electronics Engineers Incen_US
dc.relation.ispartofIeee Journal of Selected Topics In Signal Processingen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.snmz$2023V1Guncelleme$en_US
dc.subjectRadar; Mimo Communication; Array Signal Processing; Bandwidth; Hardware; Antenna Arrays; Radar Antennas; Hybrid Beamforming; Joint Radar-Communications; Terahertz; Ultramassive Mimo; Deep Learningen_US
dc.subjectMillimeter-Wave; Thz Communications; Signal; Systems; Design; Attenuation; Selection; Mmwave; Array; Ghzen_US
dc.titleTerahertz-Band Joint Ultra-Massive MIMO Radar-Communications: Model-Based and Model-Free Hybrid Beamformingen_US
dc.typeArticleen_US

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