Optimization of Spectrum Allocation in Cognitive Radio and Dynamic Spectrum Access Networks

Bibliographic Details
Main Author:	Zhang, Tao
Language:	English
Published:	Wright State University / OhioLINK 2012
Subjects:	Computer Engineering Computer Science
Online Access:	http://rave.ohiolink.edu/etdc/view?acc_num=wright1364171144

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spelling	ndltd-OhioLink-oai-etd.ohiolink.edu-wright13641711442021-08-03T05:21:10Z Optimization of Spectrum Allocation in Cognitive Radio and Dynamic Spectrum Access Networks Zhang, Tao Computer Engineering Computer Science Spectrum has become a treasured commodity. However, many licensed frequency bands exclusively assigned to the primary license holders (also called primary users) remain relatively unused or under-utilized for most of the time. Allowing other users (also called secondary users) without a license to operate in these bands with no interference becomes a promising way to satisfy the fast growing needs for frequency spectrum resources. A cognitive radio adapts to the environment it operates in by sensing the spectrum and quickly decides on appropriate frequency bands and transmission parameters to use in order to achieve certain performance goals.One of the most important issues in cognitive radio networks (CRNs) is intelligent channel allocation which will improve the performance of the network and spectrum utilization. The objective of this dissertation is to address the channel allocation optimization problem in cognitive radio and DSA networks under both centralized architecture and distributed architecture. By centralized architecture we mean the cognitive radio and DSA networks are infrastructure based. That is, there is a centralized device which collects all information from other cognitive radios and produces a channel allocation scheme. Then each secondary user follows the spectrum allocation and accesses the corresponding piece of spectrum. By distributed architecture we mean that each secondary user inside the cognitive radio and DSA networks makes its own decision based on local information on the spectrum usage. Each secondary user only considers the spectrum usage around itself.We studied three common objectives of the channel allocation optimization problem, including maximum network throughput (MNT), max-min fairness (MMF), and proportional fairness (PF). Given different optimization objectives, we developed mathematical models in terms of linear programing and non-linear programing formulations, under the centralized architecture. We also designed a unified framework with different heuristic algorithms for different optimization objectives and the best results from different algorithms can be automatically chosen without manual intervention. We also conducted additional work on spectrum allocation under distributed architecture. First, we studied the channel availability prediction problem. Since there is a lot of usable statistic information on spectrum usage from national and regional agencies, we presented a Bayesian inference based prediction method, which utilizes prior information to make better prediction on channel availability. Finally a distributed channel allocation algorithm is designed based on the channel prediction results. We illustrated that the interaction behavior between different secondary users can be modeled as a game, in which the secondary users are denoted as players and the channels are denoted as resources. We proved that our distributed spectrum allocation algorithm can achieve to Nash Equilibrium, and is Pareto optimal. 2012 English text Wright State University / OhioLINK http://rave.ohiolink.edu/etdc/view?acc_num=wright1364171144 http://rave.ohiolink.edu/etdc/view?acc_num=wright1364171144 unrestricted This thesis or dissertation is protected by copyright: all rights reserved. It may not be copied or redistributed beyond the terms of applicable copyright laws.
collection	NDLTD
language	English
sources	NDLTD
topic	Computer Engineering Computer Science
spellingShingle	Computer Engineering Computer Science Zhang, Tao Optimization of Spectrum Allocation in Cognitive Radio and Dynamic Spectrum Access Networks
author	Zhang, Tao
author_facet	Zhang, Tao
author_sort	Zhang, Tao
title	Optimization of Spectrum Allocation in Cognitive Radio and Dynamic Spectrum Access Networks
title_short	Optimization of Spectrum Allocation in Cognitive Radio and Dynamic Spectrum Access Networks
title_full	Optimization of Spectrum Allocation in Cognitive Radio and Dynamic Spectrum Access Networks
title_fullStr	Optimization of Spectrum Allocation in Cognitive Radio and Dynamic Spectrum Access Networks
title_full_unstemmed	Optimization of Spectrum Allocation in Cognitive Radio and Dynamic Spectrum Access Networks
title_sort	optimization of spectrum allocation in cognitive radio and dynamic spectrum access networks
publisher	Wright State University / OhioLINK
publishDate	2012
url	http://rave.ohiolink.edu/etdc/view?acc_num=wright1364171144
work_keys_str_mv	AT zhangtao optimizationofspectrumallocationincognitiveradioanddynamicspectrumaccessnetworks
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Optimization of Spectrum Allocation in Cognitive Radio and Dynamic Spectrum Access Networks

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