A K-Means Algorithm Approach for Classifying Wireless Signal Loss Using RTT and Bandwidth

Bikramjit Dasgupta, Damian Valles, S. McClellan
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引用次数: 1

Abstract

This paper shows that with bandwidth and round-trip time statistics, data analytics can be used to classify three characteristic phenomena in wireless signal use: decreases in bandwidth due to signal over-saturation, signal attenuation due to increasing distance, and signal improvement due to decreasing distance. Using a K-Means algorithm, bandwidth and round-trip time trends were clustered correctly by signal loss type with a 99.98% accuracy rating with 10,000 validation samples.
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基于RTT和带宽的无线信号损失分类的k -均值算法
本文表明,通过带宽和往返时间统计,数据分析可以对无线信号使用中的三种特征现象进行分类:信号过饱和导致的带宽减少,距离增加导致的信号衰减,距离减少导致的信号改善。使用K-Means算法,在10000个验证样本中,带宽和往返时间趋势按信号损失类型正确聚类,准确率达到99.98%。
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