Abstract
Stochastic geometry models have been attracting attention as tractable models of wireless communication networks. Most prior studies on such models assume that the wireless nodes are placed according to homogeneous Poisson point processes (PPPs); that is, their spatial correlation is ignored. Recently, a stochastic geometry model of downlink cellular networks was proposed in which the wireless base stations (BSs) are deployed according to the Ginibre point process (GPP). The GPP can express repulsion between BSs. On the other hand, the uplink analysis is more complicated than the downlink one since the transmit power of each mobile user depends on its location. In this study, we propose two approximation models for uplink cellular networks in which BSs are deployed according to the GPP. For these models, we derive computable representations for two performance indices and investigate the impact of varying the power control parameter on the network performance.
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