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Inclusion of “Self-x” Properties in the SESAME-Based Wireless Backhaul for Support of Higher Performance

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Engineering Applications of Neural Networks (EANN 2017)

Abstract

Based on the actual framework of the SESAME 5G-PPP EU-funded project, we identify the importance of the related wireless backhauling within the broader 5G innovative framework, with the pure aim of using small cells together with suitable network virtualization techniques for serving multiple tenants in a modern architectural approach. The virtualization of the network nodes and the wireless links allow for the development of a suitable SDN controller intending to perform network slicing, where the wireless backhaul resources are shared and assigned on a per-tenant basis. In order to apply SON features as they are also applied at the access radio level, the SDN controller is responsible for collecting and evaluating status information of the network (link qualities, status of wireless interfaces, ongoing traffic), thus resulting to self-planning, self-optimization and self-healing attributes.

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Notes

  1. 1.

    For more details, see: http://standards.ieee.org/about/get/802/802.11.html.

  2. 2.

    For more details see, for example: https://en.wikipedia.org/wiki/Self-organizing_network.

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Acknowledgments

The present work has been performed in the scope of the SESAME (“Small cEllS CoordinAtion for Multi-tenancy and Edge services”) European Research Project and has been supported by the Commission of the European Communities (5G-PPP/H2020, Grant Agreement No. 671596).

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Correspondence to Ioannis P. Chochliouros .

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Chochliouros, I.P., Whitehead, A., Sallent, O., Pérez-Romero, J., Spiliopoulou, A.S., Dardamanis, A. (2017). Inclusion of “Self-x” Properties in the SESAME-Based Wireless Backhaul for Support of Higher Performance. In: Boracchi, G., Iliadis, L., Jayne, C., Likas, A. (eds) Engineering Applications of Neural Networks. EANN 2017. Communications in Computer and Information Science, vol 744. Springer, Cham. https://doi.org/10.1007/978-3-319-65172-9_60

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  • DOI: https://doi.org/10.1007/978-3-319-65172-9_60

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