Dynamic Resource Allocation for Optimized Latency and Reliability in Vehicular Networks

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dc.contributor.authorAshraf, Muhammad Ikramen
dc.contributor.authorLiu, Chen-Fengen
dc.contributor.authorBennis, Mehdien
dc.contributor.authorSaad, Waliden
dc.contributor.authorHong, Choong Seonen
dc.contributor.departmentElectrical and Computer Engineeringen
dc.date.accessioned2019-05-14T13:16:38Zen
dc.date.available2019-05-14T13:16:38Zen
dc.date.issued2018en
dc.description.abstractSupporting ultra-reliable and low-latency communications (URLLC) is crucial for vehicular traffic safety and other mission-critical applications. In this paper, a novel proximity and quality-ofservice-aware resource allocation framework for vehicle-to-vehicle (V2V) communication is proposed. The proposed scheme incorporates the physical proximity and traffic demands of vehicles to minimize the total transmission power over the allocated resource blocks (RBs) under reliability and queuing latency constraints. A Lyapunov framework is used to decompose the power minimization problem into two interrelated sub-problems: RB allocation and power optimization. To minimize the overhead introduced by frequent information exchange between the vehicles and the roadside unit (RSU), the resource allocation problem is solved in a semi-distributed fashion. First, a novel RSU-assisted virtual clustering mechanism is proposed to group vehicles into disjoint zones based on mutual interference. Second, a per-zone matching game is proposed to allocate RBs to each vehicle user equipment (VUE) based on vehicles' traffic demands and their latency and reliability requirements. In the formulated one-to-many matching game, VUE pairs and RBs rank one another using preference relations that capture both the queue dynamics and interference. To solve this game, a semi-decentralized algorithm is proposed using which the VUEs and RBs can reach a stable matching. Finally, a latency-and reliability-aware power allocation solution is proposed for each VUE pair over the assigned subset of RBs. Simulation results for a Manhattan model show that the proposed scheme outperforms the state-of-art baseline and reaches up to 45% reduction in the queuing latency and 94% improvement in reliability.en
dc.description.notesThis work was supported by the U.S. National Science Foundation under Grant CNS-1513697 and Grant CNS-1836802.en
dc.description.sponsorshipU.S. National Science Foundation [CNS-1513697, CNS-1836802]en
dc.format.mimetypeapplication/pdfen
dc.identifier.doihttps://doi.org/10.1109/ACCESS.2018.2876548en
dc.identifier.eissn2169-3536en
dc.identifier.urihttp://hdl.handle.net/10919/89508en
dc.identifier.volume6en
dc.language.isoenen
dc.publisherIEEEen
dc.rightsCreative Commons Attribution 4.0 Internationalen
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en
dc.subject5Gen
dc.subjectLyapunov optimizationen
dc.subjectmatching theoryen
dc.subjectpower optimizationen
dc.subjectultra-reliable low latency communications (URLLC)en
dc.titleDynamic Resource Allocation for Optimized Latency and Reliability in Vehicular Networksen
dc.title.serialIEEE Accessen
dc.typeArticle - Refereeden
dc.type.dcmitypeTexten

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