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dc.contributor.authorLi, Zhuofei
dc.contributor.authorHu, Fengye
dc.contributor.authorLi, Qihao
dc.contributor.authorLing, Zhuang
dc.contributor.authorChang, Zheng
dc.contributor.authorHämäläinen, Timo
dc.date.accessioned2024-05-30T10:19:24Z
dc.date.available2024-05-30T10:19:24Z
dc.date.issued2024
dc.identifier.citationLi, Z., Hu, F., Li, Q., Ling, Z., Chang, Z., & Hämäläinen, T. (2024). AoI-Aware Waveform Design for Cooperative Joint Radar-Communications Systems with Online Prediction of Radar Target Property. <i>IEEE Transactions on Communications</i>, <i>Early Access</i>. <a href="https://doi.org/10.1109/tcomm.2024.3392748" target="_blank">https://doi.org/10.1109/tcomm.2024.3392748</a>
dc.identifier.otherCONVID_213389205
dc.identifier.urihttps://jyx.jyu.fi/handle/123456789/95369
dc.description.abstractIn this paper, we propose a novel age-of-information (AoI)-aware waveform design scheme for the cooperative joint radar-communications (JRC) system, called AoI-aware Online Prediction (A-OnP) scheme. To be specific, we optimize the power allocation of the orthogonal frequency division multiplexing (OFDM) signal. We aim to maximize the radar mutual information (RMI) with considering the communication data rate (CDR) and AoI performance. Specifically, we design a cognitive operating framework for the JRC system, with a particular emphasis on the closed-loop signal processing for online prediction of the radar target scattering coefficient (TSC). Then, considering the obtained TSC prediction result and corresponding communication performance requirement, we optimize the power allocation of the transmit waveform and the signal-to-interference-plus-noise ratio (SINR) threshold of the communication users. Accordingly, we propose a constraints-splitting coordinate descent (CS-CD) method to solve the formulated non-convex problem by strategically splitting the sum-constraints and assign a quota to each channel, where the allocation criteria is automatically decided during iteration. Simulation results demonstrate that, the cooperative radar-centric communication-constrained (RC-CC) waveform outperforms the separately optimized radar-optimal plus communication-optimal (RO-CO) waveform. Additionally, the A-OnP scheme can increase RMI while meeting the communication CDR and AoI requirements.en
dc.format.mimetypeapplication/pdf
dc.language.isoeng
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)
dc.relation.ispartofseriesIEEE Transactions on Communications
dc.rightsIn Copyright
dc.subject.otherradar
dc.subject.otherOFDM
dc.subject.othersensors
dc.subject.otherradar scattering
dc.subject.otherinterference
dc.subject.otherresource management
dc.subject.othermeasurement
dc.titleAoI-Aware Waveform Design for Cooperative Joint Radar-Communications Systems with Online Prediction of Radar Target Property
dc.typeresearch article
dc.identifier.urnURN:NBN:fi:jyu-202405304133
dc.contributor.laitosInformaatioteknologian tiedekuntafi
dc.contributor.laitosFaculty of Information Technologyen
dc.type.urihttp://purl.org/eprint/type/JournalArticle
dc.type.coarhttp://purl.org/coar/resource_type/c_2df8fbb1
dc.description.reviewstatuspeerReviewed
dc.relation.issn0090-6778
dc.relation.volumeEarly Access
dc.type.versionacceptedVersion
dc.rights.copyright© 2024 IEEE
dc.rights.accesslevelopenAccessfi
dc.type.publicationarticle
dc.subject.ysoanturit
dc.subject.ysointerferenssi (fysiikka)
dc.subject.ysoresurssit
dc.subject.ysomittaus
dc.format.contentfulltext
jyx.subject.urihttp://www.yso.fi/onto/yso/p11460
jyx.subject.urihttp://www.yso.fi/onto/yso/p700
jyx.subject.urihttp://www.yso.fi/onto/yso/p19352
jyx.subject.urihttp://www.yso.fi/onto/yso/p4794
dc.rights.urlhttp://rightsstatements.org/page/InC/1.0/?language=en
dc.relation.doi10.1109/tcomm.2024.3392748
jyx.fundinginformationThis work was supported in part by the scholarship from the China Scholarship Council (No. 202206170004), in part by the Joint Fund for Regional Innovation and Development of the National Natural Science Foundation of China (No.U21A20445), in part by the National Natural Science Foundation of China (No. 62201224, No. 62201148, No. 62071105), in part by the Jilin Province Development and Reform Commission Project (No. 2023C039-1), in part by Jilin Provincial Key Laboratory of Intelligent Sensing and Network Technology (No. 20240302096GX, No. 20230508035RC and No. YDZJ202102CXJD018), in part by the Guangdong Province Basic and Applied Basic Research Foundation (No. 2022KQNCX).
dc.type.okmA1


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