Inicio  /  Applied Sciences  /  Vol: 12 Par: 22 (2022)  /  Artículo
ARTÍCULO
TITULO

Clustering-Based Channel Allocation Method for Mitigating Inter-WBAN Interference

Woojin Song and Jaesung Park    

Resumen

In this paper, we propose a channel assignment method that can mitigate the inter-WBAN interference when the density of WBANs is high. To achieve the goal, we group the coexisting WBANs into a set of clusters by using the Louvain algorithm and allocate different channels to the WBANs in the same cluster by using a graph coloring method. By increasing the distance between the WBANs using the same channel, our method reduces the inter-WBAN interference. As a result, compared with the conventional centralized channel allocation method, our method increases the average data rate of a WBAN more than twice even when the number of coexisting WBANs is larger than the number of available channels. Compared with a distributed method involving an iterative process, our method reduces the channel decision time by 94.6% 94.6 % . Furthermore, since our method self-configures the algorithm parameters dynamically according to the topology changes, it can be used without human intervention even when the topology changes.

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