Modeling and analysis of wireless cognitive radio networks: a geometrical probability approach
Wireless devices and applications have been an unavoidable part of human lives in the past decade. In the past few years, the global mobile data traffic has grown considerably and is expected to grow even faster in future. Given the fact that the number of wireless nodes has significantly increased...
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| Language: | English en |
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2016
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| Online Access: | http://hdl.handle.net/1828/7055 |
| Summary: | Wireless devices and applications have been an unavoidable part of human lives in the past decade. In the past few years, the global mobile data traffic has grown considerably and is expected to grow even faster in future.
Given the fact that the number of wireless nodes has significantly increased, the contention and interference on the license-free industrial, scientific, and medical band has become severer than ever. Cognitive radio nodes were introduced in the past decade to mitigate the issues related to spectrum scarcity.
In this dissertation, we focus on the interference and performance analysis of networks coexisting with cognitive radio networks and address the design and analysis of spectrum allocation and routing for cognitive radio networks. Spectrum allocation enables nodes to construct a link on a common channel at the same time so they can start communicating with each other. We introduce a new approach for the modeling and analysis of interference and spectrum allocation schemes for cognitive radio networks with arbitrarily-shaped network regions.
First, for the first time in the literature, we propose a simple and efficient approach that can derive the distribution of the distance between an arbitrary interior/exterior reference point and a random point within an arbitrary convex/concave irregular polygon. This tool is essential in analyzing important distance-related performance metrics in wireless communication networks.
Second, considering the importance of interference analysis in cognitive radio networks and its important role in designing spectrum allocation schemes, we model and analyze a heterogeneous cellular network consisting of several cognitive femto cells and a coexisting multi-cell network. Besides the cumulative interference, important distance-related performance metrics have been investigated, such as the signal-to-interference ratio and outage probability.
Finally, the spectrum allocation and routing problems in cognitive radio networks have been discussed. Considering a wireless cognitive radio network coexisting with a cellular network with irregular polygon-shaped cells, we have used the tools developed in this dissertation and proposed a joint spectrum allocation and routing scheme. === Graduate |
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