RADIO FREQUENCY INTERFERENCE DETECTION AND AUTOMATIC MODULATION RECOGNITION BASED ON MASK RCNN

The increasing complexity of wireless communication conditions presents noteworthy obstacles to the adaptability and flexibility of cognitive radio systems. The latter can alleviate the problem of spectrum shortages through proper spectrum management. However, cognitive radio has difficulty distinguishing between signals of interest and interference, which can be a general enemy since it is undesirable because it influences the signal's quality.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2024-09-19
DOI
https://doi.org/10.5281/zenodo.14203798
Primary Topic
Cognitive Radio Networks and Spectrum Sensing
Type
article
Field-Weighted Citation Impact
0.00
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article

RADIO FREQUENCY INTERFERENCE DETECTION AND AUTOMATIC MODULATION RECOGNITION BASED ON MASK RCNN

Zenodo (CERN European Organization for Nuclear Research)
Cognitive Radio Networks and Spectrum Sensing
article

RADIO FREQUENCY INTERFERENCE DETECTION AND AUTOMATIC MODULATION RECOGNITION BASED ON MASK RCNN

article en

Abstract

The increasing complexity of wireless communication conditions presents noteworthy obstacles to the adaptability and flexibility of cognitive radio systems. The latter can alleviate the problem of spectrum shortages through proper spectrum management. However, cognitive radio has difficulty distinguishing between signals of interest and interference, which can be a general enemy since it is undesirable because it influences the signal's quality.

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 54%
Cognitive Radio Networks and Spectrum Sensing
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RADIO FREQUENCY INTERFERENCE DETECTION AND AUTOMATIC MODULATION RECOGNITION BASED ON MASK RCNN · Zenodo (CERN European Organization for Nuclear Research) (2024) | TGRS Research Map | TGRS