Abstract
The rapid growth of small cells is driving cellular network toward randomness and heterogeneity. The multi-tier heterogeneous network (HetNet) addresses the massive connectivity demands of the emerging cellular networks. Cellular networks are usually modeled by placing each tier (e.g macro, pico and relay nodes) deterministically on a grid which ignores the spatial randomness of the nodes. Several works were idealized for not capturing the interference which is a major performance bottleneck. Overcoming such limitation by realistic models is much appreciated. Multi-tier relay cellular network is studied in this paper, In particular, we consider {mathscr {K}}-tier transmission modeled by factorial moment and stochastic geometry and compare it with a single-tier, traditional grid model and multi-antenna ultra-dense network (UDN) model to obtain tractable rate coverage and coverage probability. The locations of the relays, base stations, and users nodes are modeled as a Poisson Point Process. The results showed that the proposed model outperforms the traditional multi-antenna UDN model and its accuracy is confirmed to be similar to the traditional grid model. The obtained results from the proposed and comparable models demonstrate the effectiveness and analytical tractability to study the HetNet performance.
Highlights
Cellular networks evolve from planned cells to irregularly dense multi-tier networks to satisfy the exponential growth of the wireless data traffic [45]
The collective coexistence of these low power BSs is termed as small cells and the high power BSs are termed as macrocells, so the resulting network is usually known as a heterogeneous network (HetNet) [15,28]
We wish to introduce a general framework for studying arbitrary functions of the stationary Poisson Point Process (PPP) formed by the signal-tointerference-and-noise ratio (SINR) values experienced by a typical user
Summary
Cellular networks evolve from planned cells to irregularly dense multi-tier networks to satisfy the exponential growth of the wireless data traffic [45]. The resulting SINR consists of multiple random complex variables, without considering the interference randomness in small-cell network [55] and cellular network distribution [51] These models are not tractable because they are highly idealized, complex system-level simulation is used to evaluate the coverage probability and rate coverage. The BS positions are agnostic to the wireless signal propagation, which makes the power that a relay or user receives from any population of BSs look as if they originated from PPP-distributed BSs [46] This facilitates the network performance computation metrics such as the coverage probability [39,53], with its lower and upper bound derivations. It is imperative to characterize the randomly distributed performance of two-tier network by using factorial moment and stochastic geometry to derive closed-form bounds for the rate coverage and coverage probability
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
