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• W2963536698 abstract "In this paper, a dynamic spectrum management framework is proposed to improve spectrum resource utilization in a multi-access edge computing (MEC) in autonomous vehicular network (AVNET). To support the increasing communication data traffic and guarantee quality-of-service (QoS), spectrum slicing, spectrum allocating, and transmit power controlling are jointly considered. Accordingly, three non-convex network utility maximization problems are formulated to slice spectrum among base stations (BSs), allocate spectrum among autonomous vehicles (AVs) associated with a BS, and control transmit powers of BSs, respectively. Through linear programming relaxation and first-order Taylor series approximation, these problems are transformed into tractable forms and then are jointly solved through an alternate concave search (ACS) algorithm. As a result, the optimal spectrum slicing ratios among BSs, optimal BS-vehicle association patterns, optimal fractions of spectrum resources allocated to AVs, and optimal transmit powers of BSs are obtained. Based on our simulation, a high aggregate network utility is achieved by the proposed spectrum management scheme compared with two existing schemes." @default.
• W2963536698 created "2019-07-30" @default.
• W2963536698 creator A5025221904 @default.
• W2963536698 creator A5062950866 @default.
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• W2963536698 date "2020-07-01" @default.
• W2963536698 modified "2023-10-06" @default.
• W2963536698 title "Spectrum Management for Multi-Access Edge Computing in Autonomous Vehicular Networks" @default.
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• W2963536698 doi "https://doi.org/10.1109/tits.2019.2922656" @default.
• W2963536698 hasPublicationYear "2020" @default.
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