Analysis of Load Balancing and Interference Management in Heterogeneous Cellular Networks

To meet the current cellular capacity demands, proactive offloading is required in heterogeneous cellular networks (HetCNets) comprising of different tiers of base stations (BSs), e.g., small-cell BSs (sBSs) and conventional macro-cell BSs (mBSs). Each tier differs from the others in terms of BS transmit power, spatial density, and association bias. Consequently, the coverage range of each tier BSs is also different from others. Due to low transmit power, a fewer number of users are associated to an sBS as compared with mBS. Thus, inefficient utilization of small-cell resources occurs. To balance the load across the network, it is necessary to push users to the underloaded small cells from the overloaded macro-cells. In co-channel deployed HetCNets, mBSs cause heavy inter-cell interference (ICI) to the offloaded users, which significantly affects the network performance gain. To address this issue, we develop a tractable analytical network model abating ICI using reverse frequency allocation (RFA) scheme along with cell range expansion-based user association. We probabilistically characterize coverage probability and user rate while considering RFA with and without selective sBS deployment. Our results demonstrate that selective sBS deployment outperforms other deployment methods.