Quantifying and Modeling Spectrum Opportunities in a Real Wireless Environment

Interference avoidance schemes based on dynamic spectrum access can be exploited by wireless sensor networks in order to mitigate the interference induced by collocated wireless devices. Developing models that can accurately describe the variations of spectrum opportunities over frequency and time is a key challenge for the energy efficient design of those access schemes. Previous works addressing this problem have considered interference-controlled environments, where a single packet flown has been artificially generated and the spectrum opportunities arising among the bursty transmissions of the considered network have been characterized. In this paper we consider instead a real environment with heterogeneous wireless devices and perform measurements for analyzing spectrum utilization over the 2.4 GHz ISM band: we statistically characterize the distribution of idle periods and investigate how spectrum occupancy varies over a time-frame of several days. The results we obtain can be of great utility while simulating the performance of different access schemes or dimensioning spectrum sensing algorithms and provide insights that can be used to select the most appropriate interference avoidance approach.