IEEE - Aerospace and Electronic Systems - May 2023 - 46

Feature Article:
DOI. No. 10.1109/MAES.2022.3233817
Intelligent Spectrum Management for Future
Aeronautical Communications
Eric J. Knoblock , Rafael D. Apaza, and Michael R. Gasper, NASA Glenn
Research Center, Cleveland, OH 44135 USA
Hongxiang Li
Louisville, Louisville, KY 40292 USA
Nathaniel Rose and Neil Adams
, Ruixuan Han, Zhe Wang, and Nora Schimpf, University of
, HX5, LLC, Cleveland, OH 44135 USA
INTRODUCTION
The Advanced Air Mobility (AAM) concept is an initiative
that facilitates emerging aviation markets to develop
air transportation capabilities for the movement of people
and cargo throughout regions of airspace not previously
served by traditional aviation operations. The AAM mission
intends to serve users in local, regional, intraregional,
and urban environments using advanced new aircraft that
use low-noise electric propulsion and possess the capability
of vertical takeoffs and landings. Further, the AAM
community is investigating novel air traffic management
approaches that employ recent technological advances in
automation and computer networking to enable a more
collaborative and information-rich environment.
The complexity of air operations in the AAM environment
will require diverse air-ground and air-air communications
capabilities to ensure safety and crucial
Authors' current address: Eric J. Knoblock and Michael
R. Gasper are with the Communications and Intelligent
System Division, NASA Glenn Research Center, Cleveland,
OH 44135 USA (e-mail: eric.j.knoblock@nasa.gov,
michael.r.gasper@nasa.gov). Rafael D. Aoaza is with the
Aeronautics Mission Office, NASA Glenn Research
Center, Cleveland, OH 44135 USA (e-mail: rafael.d.apaza@nasa.org).
Hongxiang Li, Ruixuan Han, Zhe Wang,
and Nora Schimpf are with the Department of Electrical
and Computer Engineering, University of Louisville,
Louisville, KY 40292 USA (e-mail: h.li@louisville.edu,
ruixuan.han@louisville.edu, zhe.wang@louisville.edu,
nora.schimpf@louisville.edu). Nathaniel Rose and Neil
Adams are with the Communications Branch, HX5,
LLC, Cleveland, OH 44135 USA (e-mail: nathaniel.p.
rose@nasa.gov, neil.s.adams@nasa.gov).
Manuscript received 17 February 2022, revised 5
August 2022; accepted 19 December 2022, and ready
for publication 10 January 2023.
Review handled by Omar Garcia Crespillo.
0885-8985/23/$26.00 ß 2023 IEEE
46
information distribution for users within the airspace [1].
The communications systems of the new aerial users must
seamlessly interconnect to other aircraft and ground assets
for the timely exchange of data for ensured safe travel
throughout varying conditions and environments. As of
this time, the specific communications system specifications
and requirements for AAM applications are
still in formulation. However, the use of fixed, existing
aviation spectrum allocations will not meet the anticipated
communication needs [2].
Accordingly, a collaborative team of researchers at the
National Aeronautics and Space Administration (NASA)
Glenn Research Center and the University ofLouisville, in
support of the agency's Aeronautics Research Mission
Directorate, is investigating concepts and technologies to
modernize the management of aviation spectrum through
the implementation ofadvanced technologies in communications,
networking, artificial intelligence (AI), machine
learning (ML), and others. The intent of this intelligent
spectrum management approach is to improve spectrum
utilization efficiency for aeronautical communications and
to facilitate enhanced airspace capacity. The outcomes
from this research, along with other technological advancements,
are expected to significantly improve the safety and
efficiency of future aviation operations and enable future
operational concepts, including remote piloted aircraft
operation and autonomous flight.
This article describes our ongoing efforts for the proposed
intelligent spectrum management approach, which is
being conducted in three interrelated research and development
areas. The first research area focuses on the development
ofalgorithms to predict air traffic and communications
demands throughout the airspace. Based on these predicted
demands and other inputs, the second research area focuses
on learning-based resource allocations for aeronautical communications.
In particular, two use cases in air-ground and
air-air communications are considered, where the optimization
problems are mathematically formulated and solved by
IEEE A&E SYSTEMS MAGAZINE
MAY 2023
https://orcid.org/0000-0003-4898-2704 https://orcid.org/0000-0002-9336-2128 https://orcid.org/0000-0002-3773-4011
IEEE - Aerospace and Electronic Systems - May 2023

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