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

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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… Click to show full abstract

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 $$K>2$$K>2 and its close-form expression in the case of $$K=2$$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 $$34.88 \%$$34.88% in the case of the path loss exponent $$\alpha = 3$$α=3; (2) the effect of the density of BSs on the user association probability is infinitesimal.

Keywords: using joint; joint scheduling; model based; point process; based poisson; poisson point

Journal Title: Wireless Personal Communications
Year Published: 2019

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