Statistical Analysis of Self-Organizing Networks with Biased Cell Association and Interference Avoidance

TL;DR

This paper develops an analytical framework using stochastic geometry and higher-order statistics to evaluate the performance of heterogeneous self-organizing networks with biased cell association and interference avoidance, considering realistic fading models.

Contribution

It introduces a comprehensive analytical model for self-organizing heterogeneous networks incorporating advanced interference mitigation techniques and realistic fading, validated by simulations.

Findings

Almost blank subframes reduce interference by about 12dB.

Analytical results closely match Monte Carlo simulations.

Higher picocell density necessitates more advanced interference control.

Abstract

In this work, we assess the viability of heterogeneous networks composed of legacy macrocells which are underlaid with self-organizing picocells. Aiming to improve coverage, cell-edge throughput and overall system capacity, self-organizing solutions, such as range expansion bias, almost blank subframe and distributed antenna systems are considered. Herein, stochastic geometry is used to model network deployments, while higher-order statistics through the cumulants concept is utilized to characterize the probability distribution of the received power and aggregate interference at the user of interest. A compre- hensive analytical framework is introduced to evaluate the performance of such self-organizing networks in terms of outage probability and average channel capacity with respect to the tagged receiver. To conduct our studies, we consider a shadowed fading channel model incorporating log-normal shadowing and Nakagami-m fading. Results show that the analytical framework matches well with numerical results obtained from Monte Carlo simulations. We also observed that by simply using almost blank subframes the aggregate interference at the tagged receiver is reduced by about 12dB. Although more elaborated interference control techniques such as, downlink bitmap and distributed antennas systems become needed, when the density of picocells in the underlaid tier gets high.