Cross-Technology Interference (CTI) badly harms the transmission reliability for low-power networks such as ZigBee at 2.4-GHz band. Though promising, channel hopping still faces challenges because the increasingly dense deployment of CTI leaves very few available channels. Selecting a good channel with the least overhead is crucial but challenging. Most of the existing works are heuristic methods that choose a channel far from the current one to avoid adjacent channels that may be correlatively interfered by CTI with a wider bandwidth such as WiFi. However, we observe that the correlated channels influenced by the same CTI source do not necessarily have the same channel qualities and even the opposite state, due to the uneven spectrum power density of CTI. Such channel opportunities are unexplored and wasted. In this article, we propose CoHop, a quantitative correlation-based channel hopping method for low-power wireless networks. We establish a quantitative model that describes the correlation of channel qualities to capture channel opportunities and calculate channel quality without probing, to reduce probing overhead. The probing sequence is optimized based on the Pearson Correlation Coefficient and the prediction-based probing algorithm. We implement CoHop on TinyOS and evaluate its performance in various environments. The experimental results show that CoHop can increase the Packet Reception Ratio by 80%, compared with existing methods.
Is local blacklisting relevant in slow channel hopping low-power wireless networks?
