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Conference Paper: Joint Radar and Multicast-Unicast Communication: A NOMA Aided Framework

TitleJoint Radar and Multicast-Unicast Communication: A NOMA Aided Framework
Authors
Issue Date2022
Citation
IEEE International Conference on Communications, 2022, v. 2022-May, p. 4541-4546 How to Cite?
AbstractThe novel concept of non-orthogonal multiple access (NOMA) aided joint radar and multicast-unicast communication (Rad-MU-Com) is investigated. Employing the same spectrum resource, a multi-input-multi-output (MIMO) dual-functional radar-communication (DFRC) base station detects the radar-centric user (R-user), while transmitting mixed multicast-unicast messages both to the R-user and to the communication-centric user (C-user). In particular, the multicast information is intended for both the R- and C-users, whereas the unicast information is only intended for the C-user. More explicitly, NOMA is employed to facilitate this double spectrum sharing, where the multicast and unicast signals are superimposed in the power domain and the superimposed communication signals are also exploited as radar probing waveforms. A beamformer-based NOMA-aided joint Rad-MU-Com framework is proposed for the system having a single R-user and a single C-user. Based on this framework, the unicast rate maximization problem is formulated by optimizing the beamformers employed, while satisfying the rate requirement of multicast and the predefined accuracy of the radar beam pattern. The resultant non-convex optimization problem is solved by a penalty-based iterative algorithm to find a high-quality near-optimal solution. Finally, our numerical results reveal that significant performance gains can be achieved by the proposed scheme over the benchmark schemes.
Persistent Identifierhttp://hdl.handle.net/10722/349782
ISSN

 

DC FieldValueLanguage
dc.contributor.authorMu, Xidong-
dc.contributor.authorLiu, Yuanwei-
dc.contributor.authorGuo, Li-
dc.contributor.authorLin, Jiaru-
dc.contributor.authorHanzo, Lajos-
dc.date.accessioned2024-10-17T07:00:46Z-
dc.date.available2024-10-17T07:00:46Z-
dc.date.issued2022-
dc.identifier.citationIEEE International Conference on Communications, 2022, v. 2022-May, p. 4541-4546-
dc.identifier.issn1550-3607-
dc.identifier.urihttp://hdl.handle.net/10722/349782-
dc.description.abstractThe novel concept of non-orthogonal multiple access (NOMA) aided joint radar and multicast-unicast communication (Rad-MU-Com) is investigated. Employing the same spectrum resource, a multi-input-multi-output (MIMO) dual-functional radar-communication (DFRC) base station detects the radar-centric user (R-user), while transmitting mixed multicast-unicast messages both to the R-user and to the communication-centric user (C-user). In particular, the multicast information is intended for both the R- and C-users, whereas the unicast information is only intended for the C-user. More explicitly, NOMA is employed to facilitate this double spectrum sharing, where the multicast and unicast signals are superimposed in the power domain and the superimposed communication signals are also exploited as radar probing waveforms. A beamformer-based NOMA-aided joint Rad-MU-Com framework is proposed for the system having a single R-user and a single C-user. Based on this framework, the unicast rate maximization problem is formulated by optimizing the beamformers employed, while satisfying the rate requirement of multicast and the predefined accuracy of the radar beam pattern. The resultant non-convex optimization problem is solved by a penalty-based iterative algorithm to find a high-quality near-optimal solution. Finally, our numerical results reveal that significant performance gains can be achieved by the proposed scheme over the benchmark schemes.-
dc.languageeng-
dc.relation.ispartofIEEE International Conference on Communications-
dc.titleJoint Radar and Multicast-Unicast Communication: A NOMA Aided Framework-
dc.typeConference_Paper-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1109/ICC45855.2022.9838951-
dc.identifier.scopuseid_2-s2.0-85137263060-
dc.identifier.volume2022-May-
dc.identifier.spage4541-
dc.identifier.epage4546-

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