Characterization of base station deployment distribution and coverage in heterogeneous networks

Abstract

Considering different types of base stations (BSs) in future cellular networks are overlapping deployment with the status of dense, multi-tier and heterogeneous in general, how to optimize the real BS deployment becomes a complicated problem. Based on it, repulsive BS dataset and clustering BS dataset are statically characterized with various types of spatial point processes. It shows that the improvement of coverage probability between 1-tier and 2-tier network fluctuates as the signal-to-interference ratio (SIR) threshold increases for different datasets. The authors' proposed hybrid model fits well with repulsive BS dataset, while the log-Gaussian Cox point process (LGCP) and Cauchy model are reasonable models for clustering BS dataset. Besides, in order to dynamically analyze the coverage problem affected by adding new BSs, a cell boundary constructed by an irregular circle is introduced under an equal SIR constraint, and a BS placement scheme is proposed to place new BSs at the points of minimum interference. Numerical results show that the coverage probability may increase after adding BSs in the target area of heterogeneous network by using the proposed scheme. However, as the density of femto BS reaches a certain value, its coverage may remain unchanged even after adding more femto BSs.