Spectrum Usage Estimating and Predicting

Abstract

In this study, made from observations in 4 different locations in Doha, the first location is close to the education campus with an open and flat area, the second location is the trade zone, the third location is a region with high buildings near the city center, and the fourth location is selected as the factory and workshop area. Three different algorithms, Bayes Based Analysis, Largest Sense Estimation, and Naive Bayes classifier, were used to estimate and predict spectrum usage on a data set, with 1 minute observation for each location, with a total of 4320 different readings in the 700 - 3000 MHz spectrum. The optimum solution was sought for the prediction and estimation of its use. After the optimum method was chosen, the relationship of the chosen method with the past and previous situations was examined. As a result of these algorithms, Bayes Based algorithm was chosen as the most suitable algorithm and performance was measured as %88.94.