Analysis of Heterogeneous Cellular Networks under Frequency Diversity and Interference Correlation

TL;DR

This paper develops a realistic stochastic model for heterogeneous cellular networks with frequency diversity, analyzing how interference correlation impacts rate coverage and highlighting the importance of considering spectrum diversity for accurate performance assessment.

Contribution

Introduces a novel stochastic model for K-tier HCNs that accounts for interference correlation across spectrum, providing more accurate rate coverage analysis.

Findings

Ignoring interference correlation overestimates data rates.

Spectrum diversification significantly improves performance at low to moderate data rates.

Interference correlation reduces the benefits of frequency diversity.

Abstract

Analyzing heterogeneous cellular networks (HCNs) has become increasingly complex, particularly due to irregular base station locations, massive deployment of small cells, and flexible resource allocation. The latter is usually not captured by existing stochastic models for analytical tractability. In this work, we develop a more realistic stochastic model for a generic $K$-tier HCN, where users are served in the downlink under frequency diversity. We derive the rate coverage probability for this case, taking into account the interference correlation across different parts of the allocated spectrum. Our results indicate that ignoring this type of correlation may considerably overestimate the offered date rate. Furthermore, the gain of spectrum diversification is significant, particularly at low to moderate target data rates.