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Stochastic geometry modeling and analysis of single- and multi-cluster wireless networks

Azimi Abarghouyi, S. M ; Sharif University of Technology | 2018

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  1. Type of Document: Article
  2. DOI: 10.1109/TCOMM.2018.2841366
  3. Publisher: Institute of Electrical and Electronics Engineers Inc , 2018
  4. Abstract:
  5. This paper develops a stochastic geometry-based approach for the modeling and analysis of single- and multi-cluster wireless networks. We first define finite homogeneous Poisson point processes to model the number and locations of the transmitters in a confined region as a single-cluster wireless network. We study the coverage probability for a reference receiver for two strategies; closest-selection, where the receiver is served by the closest transmitter among all transmitters, and uniform-selection, where the serving transmitter is selected randomly with uniform distribution. Second, using Matern cluster processes, we extend our model and analysis to multi-cluster wireless networks. Here, two types of receivers are modeled, namely, closed- and open-access receivers. Closed-access receivers are distributed around the cluster centers of the transmitters according to a symmetric normal distribution and can be served only by the transmitters of their corresponding clusters. Open-access receivers, on the other hand, are placed independently of the transmitters and can be served by all transmitters. In all cases, the link distance distribution and the Laplace transform (LT) of the interference are derived. We also derive closed-form lower bounds on the LT of the interference for single-cluster wireless networks. The impact of different parameters on the performance is also investigated. © 1972-2012 IEEE
  6. Keywords:
  7. Clustered wireless networks ; Matern cluster process ; Poisson point process ; Stochastic geometry ; Laplace transforms ; Normal distribution ; Stochastic systems ; Transmitters ; Wireless networks ; Cluster centers ; Coverage probabilities ; Link distance ; Model and analysis ; Uniform distribution ; Geometry
  8. Source: IEEE Transactions on Communications ; Volume 66, Issue 10 , 2018 , Pages 4981-4996 ; 00906778 (ISSN)
  9. URL: https://ieeexplore.ieee.org/document/8368129