M.S. (Master of Science)
Department of Electrical Engineering
Estimation of links in a Wireless Sensor Network and using such estimates to decide between all the multiple paths available in a network is important. There are several link estimation methods available. This thesis evaluates the performance of PRR based method (P-success method), suggested in the ZigBee specification and LQI based method (LQI method) used by different organizations, in various scenarios. The performance of these two link cost estimation methods is also compared under Wi-Fi interference. This comparison is done using a network simulator (NS3). It is observed that, if there is no Wi-Fi interference, both the P-success and LQI methods perform very similarly. In the presence of Wi-Fi interference, P-success method performs better than the LQI method. Based on the observations from the comparison of the two link cost estimation methods, this thesis proposes an improvement by combining the two existing methods into a new method called Pl + LQI method. Performance of the new method was evaluated by comparing it with P-success and LQI method. This new method (P l + LQI) performs similarly as the P-Success method in scenarios with Wi-Fi interference, and perform similarly, or better than the LQI-based method in scenarios without Wi-Fi interference.
Meka, Srikar, "Improving Link Quality Estimation in Zigbee Networks" (2019). Graduate Research Theses & Dissertations. 7432.
Northern Illinois University
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