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Bi-Criteria Radio Spectrum Sharing with Subspace-Based Pareto Tracing

Published

Author(s)

Zachary J. Grey, Susanna Mosleh, Jake Rezac, Yao Ma, Jason Coder, Andrew Dienstfrey

Abstract

Radio spectrum is a scarce resource. To meet demands, new wireless technologies must operate in shared spectrum over unlicensed bands (coexist). We consider coexistence of Long-Term Evolution (LTE) License-Assisted Access (LAA) with incumbent Wi-Fi systems. Our scenario consists of multiple LAA and Wi-Fi links sharing an unlicensed band; we aim to simultaneously optimize performance of both coexistence systems. To do this, we present a technique to continuously estimate the Pareto frontier of parameter sets (traces) which approximately maximize all convex combinations of network throughputs over network parameters. We use a dimensionality reduction approach known as active subspaces to determine that this near-optimal parameter set is primarily composed of two physically relevant parameters. A choice of two-dimensional subspace enables visualizations augmenting explainability and the reduced-dimension convex problem results in approximations which dominate random grid search.
Citation
IEEE Transactions on Communications

Keywords

Optimization methods, Wireless LAN, Communication system performance, Multidimensional signal processing

Citation

Grey, Z. , Mosleh, S. , Rezac, J. , Ma, Y. , Coder, J. and Dienstfrey, A. (2022), Bi-Criteria Radio Spectrum Sharing with Subspace-Based Pareto Tracing, IEEE Transactions on Communications, [online], https://doi.org/10.1109/TCOMM.2022.3161516, https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=932886 (Accessed August 18, 2022)
Created March 22, 2022, Updated March 28, 2022