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Performance Analysis and Channel Resource Management in Cognitive Radio Sensor Networks

dc.contributor.advisorZhao, Dongmeien_US
dc.contributor.authorLiang, Zhongliangen_US
dc.contributor.departmentElectrical and Computer Engineeringen_US
dc.date.accessioned2014-06-18T16:46:27Z
dc.date.available2014-06-18T16:46:27Z
dc.date.created2011-06-01en_US
dc.date.issued2010-07en_US
dc.description.abstract<p>p.p1 {margin: 0.0px 0.0px 0.0px 0.0px; font: 11.0px Times; color: #464646} p.p2 {margin: 0.0px 0.0px 0.0px 0.0px; font: 11.0px Times; color: #5a5a5a} span.s1 {color: #5a5a5a} span.s2 {color: #303030} span.s3 {color: #6a6a6a} span.s4 {color: #464646} span.s5 {color: #7b7b7b} span.s6 {color: #1a1a1a}</p> <p>Building a wireless sensor network (WSN) based on cognitive radio can be promising in the near future in order to provide data transmissions with quality of service requirements, while avoiding the interference in the license-free spectrum and high cost in accessing dedicated spectrum.</p> <p>p.p1 {margin: 0.0px 0.0px 0.0px 0.0px; font: 11.0px Times; color: #5a5a5a} p.p2 {margin: 0.0px 0.0px 0.0px 0.0px; font: 11.0px Times; color: #464646} p.p3 {margin: 0.0px 0.0px 0.0px 0.0px; font: 11.0px Times; color: #6a6a6a} p.p4 {margin: 0.0px 0.0px 0.0px 0.0px; font: 11.0px Times; color: #7b7b7b} span.s1 {font: 11.5px Times; color: #1a1a1a} span.s2 {color: #464646} span.s3 {color: #6a6a6a} span.s4 {color: #303030} span.s5 {color: #7b7b7b} span.s6 {color: #5a5a5a} span.s7 {color: #1a1a1a} span.s8 {color: #9b9b9b}</p> <p>In this thesis, we design a cognitive radio sensor network (CRSN) that integrates wireless sensor networking and cognitive radio technology, and analyze its performance. The network opportunistically accesses vacant channels in the licensed spectrum. \i\Then the current channel becomes unavailable, the devices switch to another available channel. The network supports both real-time and non-real-time traffic. Delay performance for the real-time traffic and throughput for the non-real- time traffic are studied. Two types of the real-time traffic are considered: bursty traffic where a burst of packets are generated periodically and each burst includes a random number of packets, and Poisson traffic where packet arrivals follow a Poisson process. Analytical models are developed for the average packet transmission delay 'when supporting each type of the real-time traffic, and simulation results of both the average transmission delay and packet drop rate performance are demonstrated . Our results indicate that real-time traffic can be effectively supported in the CRSN. Given the total number of candidate channels that can possibly be used by a CRSN, we consider how to allocate the channels among different clusters in order to maximize the system throughput. A heuristic scheme is designed to find the optimum channel allocations that achieves the same throughput as the exhaustive search method.</p>en_US
dc.description.degreeMaster of Applied Science (MASc)en_US
dc.identifier.otheropendissertations/4414en_US
dc.identifier.other5423en_US
dc.identifier.other2042392en_US
dc.identifier.urihttp://hdl.handle.net/11375/9277
dc.subjectElectrical and Computer Engineeringen_US
dc.subjectElectrical and Computer Engineeringen_US
dc.titlePerformance Analysis and Channel Resource Management in Cognitive Radio Sensor Networksen_US
dc.typethesisen_US

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