PROJECT TITLE :
Cell Association in Dense Heterogeneous Cellular Networks - 2018
Coverage evaluation of heterogeneous multi-tier cellular networks (HetNets) is typically based mostly on simplifying assumptions on cell association (CA): the resource needed by, and sensible limitations of pilot measurements are overlooked. Also, the bottom station (BS) providing the strongest signal-to-interference ratio among all BSs is always the serving BS (a perfect CA (iCA)). Consequently, the resultant analysis falls in need of characterizing HetNets' coverage in practical settings. We therefore propose an analytical framework for modeling a sensible CA (pCA) by considering pilot measurement, pilot sensitivity at the users, and the amount of pilot measurements, KP. Using tools from stochastic geometry, we have a tendency to obtain the coverage with pCA in both Rayleigh and Nakagami environments. We tend to propose an algorithm to obtain the optimal KP and its partitioning among the BSs in several tiers that maximizes the coverage. Our analysis provides key insights in designing dense HetNets. For dense networks, scale invariance achievable underneath iCA is shown unsustained with pCA. Additionally, dense HetNets are pilot-neutral, and hence their performance is not tormented by pilot sensitivity. Our in depth simulations ensure the accuracy of our analysis and also the proposed algorithm, and demonstrate the result of pCA in comparison with iCA.
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