Load-Aware Modeling and Analysis of Heterogeneous Cellular Networks

Abstract

Random spatial models are attractive for modeling heterogeneous cellular\nnetworks (HCNs) due to their realism, tractability, and scalability. A major\nlimitation of such models to date in the context of HCNs is the neglect of\nnetwork traffic and load: all base stations (BSs) have typically been assumed\nto always be transmitting. Small cells in particular will have a lighter load\nthan macrocells, and so their contribution to the network interference may be\nsignificantly overstated in a fully loaded model. This paper incorporates a\nflexible notion of BS load by introducing a new idea of conditionally thinning\nthe interference field. For a K-tier HCN where BSs across tiers differ in terms\nof transmit power, supported data rate, deployment density, and now load, we\nderive the coverage probability for a typical mobile, which connects to the\nstrongest BS signal. Conditioned on this connection, the interfering BSs of the\n$i^{th}$ tier are assumed to transmit independently with probability $p_i$,\nwhich models the load. Assuming - reasonably - that smaller cells are more\nlightly loaded than macrocells, the analysis shows that adding such access\npoints to the network always increases the coverage probability. We also\nobserve that fully loaded models are quite pessimistic in terms of coverage.\n

Affiliated Institutions

• Indian Institute of Technology Madras IN

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