A Model Based Poisson Point Process for Downlink Cellular Networks Using Joint Scheduling

© 2019, Springer Science+Business Media, LLC, part of Springer Nature. This paper proposes a model based on a random cellular network to analyse performance of Joint Scheduling in which a typical user measures signal-to-interference-plus-noise ratio (SINR) on different resource blocks from K nearest BSs in order to find out the BS with the highest SINR to establish communication. The paper derives the general form of average coverage probability of a typical user in the case of K> 2 and its close-form expression in the case of K= 2. The analytical results which are verified by Monte Carlo simulation indicates that (1) using the Joint Scheduling can improve the user’s performance up to 34.88 % in the case of the path loss exponent α= 3 ; (2) the effect of the density of BSs on the user association probability is infinitesimal