Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/89506
Title: Analysis of heterogeneous wireless networks using Poisson hard-core hole process
Authors: Flint, Ian
Kong, Han-Bae
Privault, Nicolas
Wang, Ping
Niyato, Dusit
Keywords: Stochastic Geometry
Repulsive Point Process
Issue Date: 2017
Source: Flint, I., Kong, H.-B., Privault, N., Wang, P., & Niyato, D. (2017). Analysis of heterogeneous wireless networks using Poisson hard-core hole process. IEEE Transactions on Wireless Communications, 16(11), 7152-7167.
Series/Report no.: IEEE Transactions on Wireless Communications
Abstract: The Poisson point process (PPP) has been widely employed to model wireless networks and analyze their performance. The PPP has the property that nodes are conditionally independent from each other. As such, it may not be a suitable model for many networks, where there exists repulsion among the nodes. In order to address this limitation, we adopt a Poisson hardcore process (PHCP), in which no two nodes can be closer than a repulsion radius from one another. We consider two-tier heterogeneous networks, where the spatial distributions of transmitters in the first-tier and the second-tier networks follow a PHCP and a PPP, respectively. To alleviate inter-tier interference, we consider a guard zone for the first-tier network and presume that the second-tier transmitters located in the zone are deactivated. Under this setup, the activated second-tier transmitters form a Poisson hard-core hole process. We first derive exact computable expressions of the coverage probability and introduce a method to efficiently evaluate the expressions. Then, we provide approximations of the coverage probability, which have lower computational complexities. In addition, as a special case, we investigate the coverage probability of single-tier networks by modeling the locations of transmitters as a PHCP.
URI: https://hdl.handle.net/10356/89506
http://hdl.handle.net/10220/44935
ISSN: 1536-1276
DOI: 10.1109/TWC.2017.2740387
Schools: School of Computer Science and Engineering 
School of Physical and Mathematical Sciences 
Rights: © 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The published version is available at: [http://dx.doi.org/10.1109/TWC.2017.2740387].
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:SCSE Journal Articles

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