Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/76219
Title: Optimization of deployable base stations with guaranteed QoE in disaster scenarios
Authors: Wang, JB
Guo, S 
Cheng, ZX
Li, P
Wu, J
Keywords: Anti-disaster network
Association probability
Coverage probability
Heterogeneous emergency communication networks (ECNs)
Poisson cluster process (PCP)
Issue Date: 2017
Publisher: Institute of Electrical and Electronics Engineers
Source: IEEE transactions on vehicular technology, 2017, v. 66, no. 7, p. 6536-6552 How to cite?
Journal: IEEE transactions on vehicular technology 
Abstract: Reconstructing emergency communication networks (ECNs) quickly after a disaster occurs is critical so that people can share information and confirm their safety. In recent studies, deployable base stations (DBSs) have demonstrated their ability to reconstruct an ECN. However, considering limited resources, it is impossible to deploy DBSs in the whole disaster area. The above shortage can be covered by deploying small-cell networks (i.e., low-power transmission base stations) in areas with high communication demand, e.g., in refuges. Considering the above two-tier ECN, in this paper, we study its performance and optimization issue with the objective of minimizing the number/density of DBSs while guaranteeing acceptable coverage probabilities for both communication tiers. The majority of current research focuses on scenarios where the base stations follow a homogeneous Poisson point process of coverage probability. It is difficult to transfer the results to other applications, e.g., when communication resources are shared, such as by refugees following a disaster. In such cases, the distribution of users is closer to that of a Poisson cluster process. We then investigate the optimization method to minimize the number/density of DBSs. We used Monte Carlo methods with various parameter choices to evaluate the results and to determine the accuracy of our evaluation.
URI: http://hdl.handle.net/10397/76219
ISSN: 0018-9545
EISSN: 1939-9359
DOI: 10.1109/TVT.2016.2630724
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