# Optimizing Unlicensed Band Spectrum Sharing With Subspace-Based Pareto Tracing

arXiv: https://arxiv.org/abs/2102.09047 · HTML: https://mlsanity.com/paper/2102.09047/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 3 of its 18 references that are in the map.
- First posted on arXiv 2 Feb 2021.

## Builds on (most cited first, 3 of 3)

- [Fair Coexistence of Scheduled and Random Access Wireless Networks: Unlicensed LTE/WiFi](https://mlsanity.com/paper/1605.00409/) (2016)
- [On the Fairness of Wi-Fi and LTE-LAA Coexistence](https://mlsanity.com/paper/1805.03501/) (2018)
- [Tracing locally Pareto optimal points by numerical integration](https://mlsanity.com/paper/2004.10820/) (2020)

## Abstract (arXiv)

To meet the ever-growing demands of data throughput for forthcoming and deployed wireless networks, new wireless technologies like Long-Term Evolution License-Assisted Access (LTE-LAA) operate in shared and unlicensed bands. However, the LAA network must co-exist with incumbent IEEE 802.11 Wi-Fi systems. We consider a coexistence scenario where multiple LAA and Wi-Fi links share an unlicensed band. We aim to improve this coexistence by maximizing the key performance indicators (KPIs) of these networks simultaneously via dimension reduction and multi-criteria optimization. These KPIs are network throughputs as a function of medium access control protocols and physical layer parameters. We perform an exploratory analysis of coexistence behavior by approximating active subspaces to identify low-dimensional structure in the optimization criteria, i.e., few linear combinations of parameters for simultaneously maximizing KPIs. We leverage an aggregate low-dimensional subspace parametrized by approximated active subspaces of throughputs to facilitate multi-criteria optimization. The low-dimensional subspace approximations inform visualizations revealing convex KPIs over mixed active coordinates leading to an analytic Pareto trace of near-optimal solutions.