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Top1. Introduction
Due to exponential growth in mobile data demand, as a result of the proliferation of data-thirsty applications and non-uniform user density, the cellular networks are forced to deploy heterogeneous Networks (HetNets). Several low power classes of transmission nodes associated with picocells and femtocells are deployed along with long range traditional macro base stations (BSs) making a significant increase in transmitter density (Kishore, 2003; Wu, 2004; Chandrasekhar, 2008, 2009). Due to scarcity of available spectrum, to achieve maximum throughput, the HetNet goes for universal frequency reuse with simultaneous use of total available spectrum by all co-existing tiers making the system interference-limited (Lin, 2011; Cheng, 2011). In such type of networks, the strength of the interference signal at the user terminal is much higher than the thermal noise power that significantly reduces the coverage probability.
By deploying the demand specific transmission nodes, the network topology deviates from conventional hexagonal grid to a random one that can be modeled with a stochastic point process. The point process that captures almost all network properties is Poisson point process (PPP) (Andrews, 2010; Lee, 2012; Błaszczyszyn, 2013, Perez, 2011). A k tier HetNet can be visualized as a set of same number of independent homogeneous PPPs with different densities (Błaszczyszyn & Keeler, 2015).
Though significant improvement in throughput is promised, the major drawback in successful commercial implementation of a HetNet is its low coverage probability in various locations of the network. The coverage probability is the probability of signal-to-interference-plus-noise-ratio (SINR) at the user end that is above the given threshold. The extensive analysis for SINR and coverage probability for single-tier network is given in (Keeler, Blaszczyszyn, & Karray, 2013) and the references therein and for multi-tier networks in (Błaszczyszyn, 2015; Dhillon, 2012; Błaszczyszyn, 2013).
The strategies proposed in literature to improve the SINR are broadly classified as network cooperation (NC) and interference cancelation (IC) (Akoum, 2010; Giovanidis, 2014; Zhang, 2013a; Zhang, 2012; Zhang, 2013b; Wildemeersch, 2014). With NC based strategies, significant improvement in SINR is being achieved by combining signals of ‘n’ strongest transmitters to serve single user (Akoum, 2010; Giovanidis, 2014; Zhang, 2013a). A Laplace technique based mathematical model for coverage probability analysis under stochastic geometry-based cooperation strategies is being developed in (Giovanidis & Baccelli, 2014). With IC based strategies, the servicing node with strongest received signal strength, cancels the (n-1) subsequent strongest interfering signals. With these strategies, significant improvement in coverage probability has been registered in HetNet (Zhang, 2012; Zhang, 2013b; Wildemeersch, 2014).