Cell Association in Dense Heterogeneous Cellular Networks

Abstract

Coverage evaluation of heterogeneous multi-tier cellular networks (HetNets) is often based on simplifying assumptions on cell association (CA): the resource required by, and practical limitations of pilot measurements are overlooked. Also, the base station (BS) providing the strongest signal-to-interference ratio among all BSs is always the serving BS (an ideal CA (iCA)). Consequently, the resultant analysis falls short of characterizing HetNets’ coverage in practical settings. We therefore propose an analytical framework for modeling a practical CA (pCA) by considering pilot measurement, pilot sensitivity at the users, and the number of pilot measurements, $K_P$ . Using tools from stochastic geometry, we obtain the coverage with pCA in both Rayleigh and Nakagami environments. We propose an algorithm to obtain the optimal $K_P$ and its partitioning among the BSs in different tiers that maximizes the coverage. Our analysis provides key insights in designing dense HetNets. For dense networks, scale invariance achievable under iCA is shown unsustained with pCA. Also, dense HetNets are pilot-neutral, and hence their performance is not affected by pilot sensitivity. Our extensive simulations confirm the accuracy of our analysis and the proposed algorithm, and demonstrate the effect of pCA in comparison with iCA.