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Autonomous Relocation of Mobile Base Stations in Emergency Scenarios

Published

Author(s)

Kamran Sayrafian, Ladan Rabieekenari, John Baras

Abstract

Limited access to communication services is one of the challenges that emergency personnel and first responders could face during environmental disasters or other emergencies. Networking infrastructure can breakdown during a catastrophe. At the same time, unusual peaks in traffic load could lead to much higher blocking probability for critical communication. A possible solution for such scenarios is through the use of mobile cellular base stations that can be quickly deployed in the disaster area. These mobile cells can effectively complement the existing undamaged infrastructure or enable a temporary emergency network by themselves. Given the limited capacity of each cell, variable and spatially non-uniform traffic across the disaster area can make a big impact on the network performance. Not only judicious deployment of the cells can help to meet the coverage and capacity demands across the area, but also intelligent relocation strategies can optimally match the network resources to potentially changing traffic demands.In practical scenarios, these mobile base stations may not be able to relocate to all positions within the target field. Such prohibited areas introduce additional constraints on designing an intelligent relocation strategy. We propose a decentralized relocation algorithm that enables mobile cells to adapt their positions in response to potentially changing traffic patterns in a field with prohibited areas. These traffic sources can be either user’s equipment or IoT devices that are generating valuable environmental data. The proposed solution can also be extended to cellular-based IoT networks such as NBIoT. Extensive simulations show considerable improvement in supporting spatially variable traffic throughout the target field.
Conference Dates
September 12, 2017
Conference Location
Graz
Conference Title
Dependable Wireless Communications and Localization for the IoT

Citation

Sayrafian, K. , Rabieekenari, L. and Baras, J. (2017), Autonomous Relocation of Mobile Base Stations in Emergency Scenarios, Dependable Wireless Communications and Localization for the IoT, Graz, -1, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=923634 (Accessed June 17, 2024)

Issues

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Created September 12, 2017, Updated May 13, 2020