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  4. Large-scale wireless networks: stochastic geometry and ordering
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Large-scale wireless networks: stochastic geometry and ordering

Full metadata

Description

Recently, the location of the nodes in wireless networks has been modeled as point processes. In this dissertation, various scenarios of wireless communications in large-scale networks modeled as point processes are considered. The first part of the dissertation considers signal reception and detection problems with symmetric alpha stable noise which is from an interfering network modeled as a Poisson point process. For the signal reception problem, the performance of space-time coding (STC) over fading channels with alpha stable noise is studied. We derive pairwise error probability (PEP) of orthogonal STCs. For general STCs, we propose a maximum-likelihood (ML) receiver, and its approximation. The resulting asymptotically optimal receiver (AOR) does not depend on noise parameters and is computationally simple, and close to the ML performance. Then, signal detection in coexisting wireless sensor networks (WSNs) is considered. We define a binary hypothesis testing problem for the signal detection in coexisting WSNs. For the problem, we introduce the ML detector and simpler alternatives. The proposed mixed-fractional lower order moment (FLOM) detector is computationally simple and close to the ML performance. Stochastic orders are binary relations defined on probability. The second part of the dissertation introduces stochastic ordering of interferences in large-scale networks modeled as point processes. Since closed-form results for the interference distributions for such networks are only available in limited cases, it is of interest to compare network interferences using stochastic. In this dissertation, conditions on the fading distribution and path-loss model are given to establish stochastic ordering between interferences. Moreover, Laplace functional (LF) ordering is defined between point processes and applied for comparing interference. Then, the LF orderings of general classes of point processes are introduced. It is also shown that the LF ordering is preserved when independent operations such as marking, thinning, random translation, and superposition are applied. The LF ordering of point processes is a useful tool for comparing spatial deployments of wireless networks and can be used to establish comparisons of several performance metrics such as coverage probability, achievable rate, and resource allocation even when closed form expressions for such metrics are unavailable.

Date Created
2014
Contributors
  • Lee, Junghoon (Author)
  • Tepedelenlioğlu, Cihan (Thesis advisor)
  • Spanias, Andreas (Committee member)
  • Reisslein, Martin (Committee member)
  • Kosut, Oliver (Committee member)
  • Arizona State University (Publisher)
Topical Subject
  • Electrical Engineering
  • Stochastic geometry
  • Stochastic Ordering
  • Wireless Communications
  • Wireless Networks
  • Wireless communication systems
  • Computer networks
  • Stochastic geometry
  • Stochastic orders
Resource Type
Text
Genre
Doctoral Dissertation
Academic theses
Extent
xii, 132 p. : ill. (some col.)
Language
eng
Copyright Statement
In Copyright
Reuse Permissions
All Rights Reserved
Primary Member of
ASU Electronic Theses and Dissertations
Peer-reviewed
No
Open Access
No
Handle
https://hdl.handle.net/2286/R.I.24818
Statement of Responsibility
by Junghoon Lee
Description Source
Viewed on July 1, 2014
Level of coding
full
Note
Partial requirement for: Ph.D., Arizona State University, 2014
Note type
thesis
Includes bibliographical references
Note type
bibliography
Field of study: Electrical engineering
System Created
  • 2014-06-09 02:07:27
System Modified
  • 2021-08-30 01:35:54
  •     
  • 1 year 5 months ago
Additional Formats
  • OAI Dublin Core
  • MODS XML

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