Abstract
Wireless sensor networks (WSN) commonly use ZigBee to communicate, especially when low power consumption is demanded. ZigBee may however provide unpredictable throughput although transmission distances are short. This is especially evident in difficult environments with complicated reflections and various materials through which radio signals need to pass through. Distributed scheduling based on cognitive networking principles may improve both network predictability and overall throughput. This paper presents measurements of key parameters for such cognitive scheduling, and discusses their potential for predicting suitable per-node transmission rates. Results include variability of throughput, RSSI and LQI observed for different transmission powers, transmission ranges, and number of transmitting nodes.
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Wolosz, K., Bodin, U., Riliskis, L. (2012). A Measurement Study for Predicting Throughput from LQI and RSSI. In: Bellalta, B., et al. Multiple Access Communications. MACOM 2012. Lecture Notes in Computer Science, vol 7642. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34976-8_10
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DOI: https://doi.org/10.1007/978-3-642-34976-8_10
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-34975-1
Online ISBN: 978-3-642-34976-8
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