Joint Uplink-Downlink Capacity and Coverage Optimization via Site-Specific Learning of Antenna Settings

TL;DR

This paper introduces a data-driven, scalable framework for jointly optimizing antenna parameters in 5G networks to enhance coverage and capacity, significantly outperforming existing default and optimization methods.

Contribution

It presents a novel joint UL-DL antenna parameter optimization method using Bayesian-inspired algorithms, improving network performance in a scalable and efficient manner.

Findings

Over 60% increase in sum-log-rate compared to conventional Bayesian optimization.

Over 80% reduction in outage probability compared to baseline settings.

Significant improvements over 3GPP default antenna configurations.

Abstract

We propose a novel framework for optimizing antenna parameter settings in a heterogeneous cellular network. We formulate an optimization problem for both coverage and capacity - in both the downlink (DL) and uplink (UL) - which configures the tilt angle, vertical half-power beamwidth (HPBW), and horizontal HPBW of each cell's antenna array across the network. The novel data-driven framework proposed for this non-convex problem, inspired by Bayesian optimization (BO) and differential evolution algorithms, is sample-efficient and converges quickly, while being scalable to large networks. By jointly optimizing DL and UL performance, we take into account the different signal power and interference characteristics of these two links, allowing a graceful trade-off between coverage and capacity in each one. Our experiments on a state-of-the-art 5G NR cellular system-level simulator developed by AT&T Labs show that the proposed algorithm consistently and significantly outperforms the 3GPP default settings, random search, and conventional BO. In one realistic setting, and compared to conventional BO, our approach increases the average sum-log-rate by over 60% while decreasing the outage probability by over 80%. Compared to the 3GPP default settings, the gains from our approach are considerably larger. The results also indicate that the practically important combination of DL throughput and UL coverage can be greatly improved by joint UL-DL optimization.