الفهرس 
Title : Development of Spectrum Sharing Protocol for Cognitive Radio Internet of Things
ContantsOnly 14 pages are availabe for public view
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Abstract
Internet of Things (IoT) presents a new life style by developing smart homes, smart grids, smart city, smart transportation, etc., so IoT is developing rapidly. However recent researches focus on developing the IoT applications disregarding the IoT spectrum scarcity problem facing it. Integrating Internet of Things (IoT) technology and Cognitive Radio Networks (CRNs), forming Cognitive Radio Internet of Things (CRIoTs), is an economical solution for overcoming the IoT spectrum scarcity. The aim of this thesis is to solve the problem of spectrum sharing for CRIoT; the work in thesis is presented in three parts, each represents a contribution. Our first contribution is to propose two new protocols to solve the problem of channel status prediction for interweave CRNs. Both protocols use Hidden Markov Model (HMM). In the training stage of both protocols, the available data are trained to produce two HMM models, an idle HMM model and a busy one. Both models are used together to produce the 2-model HMM. In the prediction stage the first protocol uses Bayes theorem and the 2-model HMM, while the second protocol uses Support Vector Machine (SVM) employing the parameters produced from applying the 2-model HMM, named 2-model HMM-SVM. The 2-model HMM-SVM outperforms the classical HMM and 2-model HMM in terms of the true percentage, the inaccuracy and the probability of primary users{u2019} collision (false negative prediction). In our second contribution, we proposed a centralized time slotted packet scheduling protocol for CRIoTs. It uses Discrete Permutation Particle Swarm Optimization (DP-PSO) for scheduling the IoT device packets among the free slots obtained from applying cognitive radio networks’ channel estimation technique proposed in the first part. Our proposed protocol is applied to smart healthcare facility