Throughput Analysis of Proportional Fair Scheduling For Sparse and Ultra-Dense Interference-Limited OFDMA/LTE Networks

TL;DR

This paper develops a precise analytical performance model for proportional fair scheduling in LTE networks, accounting for interference and ultra-dense deployments, validated by simulations showing improved throughput estimation accuracy.

Contribution

It introduces a closed-form model that accurately predicts long-term throughput in LTE and 5G-like ultra-dense networks considering interference and SINR distributions.

Findings

Model achieves higher accuracy than existing methods

Validates the model with realistic network simulations

Effective for interference-limited and ultra-dense deployments

Abstract

Various system tasks like interference coordination, handover decisions, admission control etc. in current cellular networks require precise mid-term (spanning over a few seconds) performance models. Due to channel-dependent scheduling at the base station, these performance models are not simple to obtain. Furthermore, LTE cellular systems are interference-limited, hence, the way interference is modelled is crucial for the accuracy. In this paper we present a closed-form analytical performance model for proportional fair scheduling in OFDMA/LTE networks. The model takes into account a precise SINR distribution into account. We refine our model with respect to uniform modulation and coding, as applied in LTE networks. Furthermore, the analytical analysis is extended also for ultra-dense deployments likely to happen in the 5-th generation of cellular networks. The resulting analytical performance model is validated by means of simulations considering realistic network deployments. Compared with related work, our model demonstrates a significantly higher accuracy for long-term throughput estimation.