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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.
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 October 7, 2025)