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Spectrum Slicing in MEC-Assisted ADVNETs

  • California State University Long Beach
  • Memorial University of Newfoundland
  • University of Waterloo

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

Abstract

In this chapter, the spectrum resource management issue is investigated under the MEC-assisted ADVNET architecture proposed in Chap. 2. Specifically, we first propose a dynamic spectrum management framework to improve spectrum resource utilization. Based on this framework, spectrum slicing, spectrum allocating, and transmit power control are then jointly considered, which can help support the increased communication data traffic and guarantee applications’ QoS requirements. Accordingly, we formulate three maximization problems to slice spectrum among BSs, allocate spectrum among AVs associated with a BS, and control transmit powers of BSs, respectively. Via linear programming relaxation and first-order Taylor series approximation, the three problems are transformed into tractable forms and then are jointly solved through an alternate concave search (ACS) algorithm. As a result, optimal results, including spectrum slicing ratios among BSs, BS-vehicle association patterns, fractions of spectrum resources allocated to AVs, and transmit powers of BSs, are obtained. The simulation results demonstrate that a high aggregate network utility can be achieved by the proposed spectrum management scheme compared with existing schemes.

Original languageEnglish
Title of host publicationWireless Networks (United Kingdom)
PublisherSpringer Nature
Pages53-80
Number of pages28
DOIs
StatePublished - 2022
Externally publishedYes

Publication series

NameWireless Networks (United Kingdom)
ISSN (Print)2366-1186
ISSN (Electronic)2366-1445

Keywords

  • Autonomous vehicles
  • Multi-access edge computing
  • NFV
  • QoS-guaranteed service
  • Spectrum resource allocation

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