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

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.