Abstract

In a recent letter, Guo et al. developed a novel method for inferring the wireless activity of other users by measuring the passive aggregate interference power received on a mobile device. The key objective of their study is to develop a non-intrusive method for activity sensing which does not rely on measurements from a live network. The proposed mobile crowd sensing mechanism relies on the analytical computation of the median of the aggregate interference, to estimate the activity levels in an OFDMA based communication system. A closed form expression for the median is obtained from the computation of the cumulative distribution function (CDF) for the aggregate co-channel interference. In this letter, we highlight that the expressions for the probability density function (PDF) and CDF of the aggregate interference obtained by inversion of the moment generating function (MGF) in Guo and Wang (Eqs. (5) and (6)) are only valid for $\alpha\!=\!4$ and they do not hold in general. Moreover, it is observed that authors employ the median of the aggregate interference, as the expectation of the interference power does not converge. In this letter, we show that this issue can be circumvented by using a non-singular path-loss model.

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