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Access-aware Backhaul Optimization in 5G

Published: 25 October 2018 Publication History

Abstract

Aggressive demand of future access network services is being translated into the stringent requirement on future backhaul infrastructure. It is not possible to take the backhaul resources for granted anymore; rather, more focused research is required to tackle the challenge of limited resources. It is also anticipated that, to meet the expectation of 5G, access and backhaul networks will work closely and therefore, total separation of their resources may not be possible anymore and joint operation is required. In this paper, we argue that, joint access-backhaul mechanisms is becoming necessary to ensure the best use of the scarce resources. We introduce the problem of statically assigning resources to capacity-limited backhaul links and we provide preliminary results to show the potential benefits of an intelligent access-aware backhaul capacity optimization scheme, where a central controller optimizes backhaul capacity according to corresponding access network requirements. Simulation results show that, with this approach, we are able to carry more traffic in a network limited by its backhaul capacity.

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Cited By

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  • (2021)Dynamic Spectrum Allocation Following Machine Learning-Based Traffic Predictions in 5GIEEE Access10.1109/ACCESS.2021.31223319(143458-143472)Online publication date: 2021
  • (2020)Computation Offloading and Retrieval for Vehicular Edge ComputingACM Computing Surveys10.1145/339206453:4(1-35)Online publication date: 20-Aug-2020
  1. Access-aware Backhaul Optimization in 5G

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    cover image ACM Conferences
    MobiWac'18: Proceedings of the 16th ACM International Symposium on Mobility Management and Wireless Access
    October 2018
    140 pages
    ISBN:9781450359627
    DOI:10.1145/3265863
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    Publication History

    Published: 25 October 2018

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    Author Tags

    1. 5g
    2. backhaul
    3. joint optimization

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    • EU Horizon 2020 research and innovation programme

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    Overall Acceptance Rate 83 of 272 submissions, 31%

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    • (2021)Dynamic Spectrum Allocation Following Machine Learning-Based Traffic Predictions in 5GIEEE Access10.1109/ACCESS.2021.31223319(143458-143472)Online publication date: 2021
    • (2020)Computation Offloading and Retrieval for Vehicular Edge ComputingACM Computing Surveys10.1145/339206453:4(1-35)Online publication date: 20-Aug-2020

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