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Fast Steerable Wireless Backhaul Reconfiguration
Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Mathematics and Computer Science (from 2013).ORCID iD: 0000-0002-4961-5087
University Center of Defense, Spain.
Stevens Institute of Technology, United States.
Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Mathematics and Computer Science (from 2013).ORCID iD: 0000-0002-9446-8143
2019 (English)In: Proceedings of the 2019 IEEE Global Communications Conference: Mobile and Wireless Networks, Dec 9-13, 2019, Big island, Hawaii, USA, IEEE, 2019, article id 9014319Conference paper, Published paper (Refereed)
Abstract [en]

Future mobile traffic growth will require 5G cellular networks to densify the deployment of small cell base stations (BS). As it is not feasible to form a backhaul (BH) by wiring all BSs to the core network, directional mmWave links can be an attractive solution to form BH links, due to their large available capacity. When small cells are powered on/off or traffic demands change, the BH may require reconfiguration, leading to topology and traffic routing changes. Ideally, such reconfiguration should be seamless and should not impact existing traffic. However, when using highly directional BH antennas which can be dynamically rotated to form new links, this can become time- consuming, requiring the coordination of BH interface movements, link establishment and traffic routing. In this paper, we propose greedy-based heuristic algorithms to solve the BH reconfiguration problem in real-time. We numerically compare the proposed algorithms with the optimal solution obtained by solving a mixed integer linear program (MILP) for smaller instances, and with a sub- optimal reduced MILP for larger instances. The obtained results indicate that the greedy-based algorithms achieve good quality solutions with significantly decreased execution time.

Place, publisher, year, edition, pages
IEEE, 2019. article id 9014319
Keywords [en]
5G, Backhaul, Heuristics, MmWave
National Category
Computer Sciences
Research subject
Computer Science
Identifiers
URN: urn:nbn:se:kau:diva-76278DOI: 10.1109/GLOBECOM38437.2019.9014319ISI: 000552238606092Scopus ID: 2-s2.0-85081967755ISBN: 9781728109626 (print)OAI: oai:DiVA.org:kau-76278DiVA, id: diva2:1384973
Conference
2019 IEEE Global Communications Conference, GLOBECOM 2019
Note

Konferensbidraget ingick som manuskript i Santos doktorsavhandling (2020): Towards Resilient and Reconfigurable Software-defined Wireless Backhaul Networks.

Available from: 2020-01-13 Created: 2020-01-13 Last updated: 2020-08-24Bibliographically approved
In thesis
1. Towards Resilient and Reconfigurable Software-defined Wireless Backhaul Networks
Open this publication in new window or tab >>Towards Resilient and Reconfigurable Software-defined Wireless Backhaul Networks
2020 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

The increase of mobile devices and services over the last decade has led to unprecedented mobile traffic growth. To cope with the increasing demands, fifth generation (5G) network architectures have been designed to provide the required capacity using a large number of small cells (SCs). However, a dense deployment of SCs requires a robust and scalable backhaul to transport the access traffic towards the Internet. In this thesis, we explore the application of the Software-defined Networking (SDN) paradigm for the management of a wireless backhaul. With SDN, the data and control planes are separated and the network is managed by a centralized entity. To that end, we provide multiple contributions that focus on achieving resilient and reconfigurable wireless backhaul networks. Firstly, we propose an SDN-based architecture to manage the wireless backhaul. Our architecture is integrated in practical testbed environments, where we use an SDN controller to configure the forwarding plane and wireless backhaul links. Secondly, we evaluate SDN-based resiliency in the wireless backhaul. We achieve that by implementing fast-failover resiliency with OpenFlow group tables and by using the bidirectional-forwarding detection protocol (BFD) to monitor the state of the backhaul links. Finally, we develop algorithms that calculate the necessary reconfiguration operations to transition between different wireless backhaul topologies, while minimizing the impact on existing user traffic. We consider that the backhaul nodes can be powered on/off and are equipped with steerable antennas that can be aligned to form links with different neighbors. Our optimization problems are modeled as mixed integer linear programs (MILP) that are optimally solved using exact mathematical programming methods. In addition, we develop greedy-based heuristic algorithms that solve the same problems and obtain good quality solutions in short time.

Abstract [en]

The increase of mobile devices and services over the last decade has led to unprecedented mobile traffic growth. To cope with the increasing demands, fifth generation (5G) network architectures have been designed to provide the required capacity using a large number of small cells (SCs). However, a dense deployment of SCs requires a robust and scalable backhaul to transport the access traffic towards the Internet.

In this thesis, we explore the application of the Software-defined Networking (SDN) paradigm for the management of a wireless backhaul. To that end, we provide multiple contributions that focus on achieving resilient and reconfigurable wireless backhaul networks. Firstly, we propose an SDN-based architecture to manage the wireless backhaul. Our architecture is integrated in practical testbed environments, where we use an SDN controller to configure the forwarding plane and wireless backhaul links. Secondly, we evaluate SDN-based fast-failover resiliency in the wireless backhaul. Finally, we develop several algorithms that orchestrate different backhaul reconfiguration operations with minimal impact on existing user traffic.

Place, publisher, year, edition, pages
Karlstad: Karlstads universitet, 2020. p. 42
Series
Karlstad University Studies, ISSN 1403-8099 ; 2020:9
Keywords
5G, heterogeneous networks, mmWave, resiliency, SDN, wireless backhaul
National Category
Computer Sciences
Research subject
Computer Science
Identifiers
urn:nbn:se:kau:diva-76286 (URN)978-91-7867-092-5 (ISBN)978-91-7867-102-1 (ISBN)
Public defence
2020-03-06, 21A342, Karlstad, 09:15 (English)
Opponent
Supervisors
Note

Article 6 and 7 part of thesis as manuscripts, now published.

Available from: 2020-02-14 Created: 2020-01-13 Last updated: 2022-03-10Bibliographically approved

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Santos, RicardoKassler, Andreas

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