I have data of received power (traces of 5000 samples)where the large scale fading and small scale fading are mixed. My goal is to analyze the small scale fading. For this reason, I have averaged the measured data to remove the large scale effect.
In the literature, most of the researchers use a moving average length between 10 λ-100 λ. However, My question is how can I make sure if the length of the averaging window is sufficient for removing totally the large scale fading?
Thanks in advance ^_^
Take a look at the mathematics behind what is called time series. There are fundamental statistical answers to that problem there. Streaming databases and measurement theory behind sensor and effector networks at places like NASA's KSC launch complex deal with this issue routinely.
you can use Matlab software to do this
work
please find out code of Matlab from the given below link
https://www.mathworks.com/matlabcentral/answers/315739-how-to-decide-window-size-for-a-moving-average-filter
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