Empirical Statistical Model for LTE Downlink Channel Occupancy
(English)Manuscript (preprint) (Other academic)
This paper develops an empirical statistical channel occupancy model for downlink long-term evolution (LTE) cellular systems. The model is based on statistical distributions mixtures for the holding times of the channels. Moreover, statistical distribution of the time when the channels are free is also considered. The data is obtained through an extensive measurement campaign performed in Stockholm, Sweden. Two types of mixtures are considered, namely, exponential and log-normal distributions to fit the measurement findings. The log-likelihood of both mixtures is used as a quantitative measure of the goodness of fit. Moreover, finding the optimal number of linearly combined distributions using the Akaike information criterion (AIC) is investigated. The results show that good fitting can be obtained by using either exponential or log-normal distributions mixture. Even though, the fitting is done for a representative case with a tempo-spatial consideration, the model is yet applicable in general for LTE and other cellular systems in a wider sense.
LTE, Cellular Traffic, Channel Occupancy Model, Exponential Mixture Fitting, Log-normal Mixture Fitting, Akaike Information Criterion (AIC).
Electrical Engineering, Electronic Engineering, Information Engineering
Research subject Information and Communication Technology
IdentifiersURN: urn:nbn:se:hig:diva-19029OAI: oai:DiVA.org:hig-19029DiVA: diva2:789573