Evolution Toward Data-Driven Spectrum Sharing: Opportunities and Challenges

As the demand for wireless services continues to grow, the need for efficient and effective management of the radio frequency (RF) spectrum becomes increasingly important. A spectrum management approach based on data analysis and interpretation i.e. data-driven, offers a solution as it provides valu...

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Bibliographic Details
Published in:IEEE access Vol. 11; pp. 99680 - 99692
Main Authors: Brown, Colin, Ghasemi, Amir
Format: Journal Article
Language:English
Published: Piscataway IEEE 2023
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Data analysis
Data models
Data-driven spectrum management
database-assisted spectrum sharing
Decision making
dynamic spectrum access
Interference
Radio frequency
Radio spectrum management
Spread spectrum communication
ISSN:2169-3536, 2169-3536
Online Access:Get full text
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Summary:As the demand for wireless services continues to grow, the need for efficient and effective management of the radio frequency (RF) spectrum becomes increasingly important. A spectrum management approach based on data analysis and interpretation i.e. data-driven, offers a solution as it provides valuable insights into spectrum usage patterns, demand, and the potential for harmful interference in shared spectrum scenarios. This paper focuses on the opportunities and challenges of incorporating diverse data sources into the management of spectrum, with a specific emphasis on spectrum sharing, particularly within database-assisted spectrum sharing systems. The benefits of adopting a data-driven approach to these systems are demonstrated through simulation of specific case studies. These studies indicate the potential for achieving up to a 60% greater density of spectrum use compared to conventional approaches, while also effectively managing harmful interference.
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ISSN:2169-3536
2169-3536
DOI:10.1109/ACCESS.2023.3315246