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For my project I need to evaluate large amounts of wlan signal strength measurements.

Measurement is in dBm which is a logarithmic scale for milli watt (so every 3dBm the milliwatts double) where 0dBm is 1 milliwatt and -100 dBm is 0.1 pW. Received Wlan Signal Strengths are usally from -30dBm (very good) to -95 dBm (very bad).

These 2 examples were one Router measureing another's received signal strength:

  • First is the measurment over time; the red line is a naiive linear regression line. The blue and yellow plot bands are the 60% and 80% confidence intervalls; green dotted line is mean

  • The second graph shows the frequency distribtuion and the red line is the CDF of a normal distribution with given mean and std dev

Distribution 1: (Samplesize: 500, Mean: -49.51, Median: -49, Mode: -49, σ: 1.77) Brainwavez Signal Strength over Time Brainwavez Frequency Distribution

Distribution 2 (Samplesize: 500, Mean: -64.41, Median: -64, Mode: -64, σ: 3.02) NodeSignal Strength over Time NodeFrequency Distribution

Practically everytime I get mean = median = mode (with +/-1) but a nice distribution curve that fits a normal distribution CDF only with high measurements.

My question is how would you classify this distribution? I heard log-normal but a CDF did not fit any of my distributions.

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I suspect that it's not one distribution but a mixture of distributions, where each one relates to a specific state of the system (don't know enough about routers) or maybe there are events happening (like RF interference) at some times which increase/lower the signal strength. If you can relate the large changes, especially in the 2nd plot after 19:00, to some other information like what the router is actually doing, you might get more insight.

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  • $\begingroup$ ill give you the bounty since there were no other answers in time $\endgroup$ – Patrick Favre Oct 28 '14 at 13:14

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