Date of Award
Master of Applied Science (MASc)
Electrical and Computer Engineering
Traditional wireless sensor networks (WSNs) working in the license-free spectrum suffer from uncontrolled interference as the license-free spectrum becomes increasingly crowded. Designing a WSN based on cognitive radio can be promising in the near future in order to provide data transmissions with quality of service requirements. In this thesis, we introduce a cognitive radio sensor network (CRSN) and analyze its performance for supporting real-time traffic. The network devices opportunistically access vacant (or available) channels in the licensed spectrum. When the current channel becomes unavailable, the devices can switch to a new channel.
Three types of real-time traffic are considered, constant-bit-rate (CBR) traffic, bursty traffic, and Poisson traffic. For the CBR traffic, a fixed number of packets are generated periodically; for the bursty traffic, a burst of packets are generated periodically and the number of packets in each burst is random; and for the Poisson traffic, the packet arrivals follow Poisson process. We derive the average packet transmission delay for each type of the traffic. The analytical results are verified by computer simulations. Our results indicate that real-time traffic can be effectively supported in the CRSN, and packets with the Poisson arrivals may experience longer average delay than the bursty arrivals.
Feng, Shen, "Delay Performance for Supporting Real-time Traffic in a Cognitive Radio Sensor Network" (2010). Open Access Dissertations and Theses. Paper 4528.
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