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Several spectrum sensing detection strategies
have been proposed in recent years, including special range
detection calculations based on the maximum a posterior
(MAP) rule, energy detection, and others. Spectrum sensing
plays an important role in enabling cognitive radio (CR)
technologies for the next generation of wireless
communication systems. All of these methods require
setting thresholds, as well as prior knowledge of the noise
distribution. Cooperative spectrum sensing is used to
improve the sensing performance. When GEO
(geostationary) and NGEO (non-geostationary) resultant
systems coexist on the same recurrence, the nongeostationary system should not create a harmful barrier to
the GEO. Several sensing methods have been proposed in
recent years, including specific spectrum sensing
algorithms based on the maximum a posterior (MAP) rule,
energy detection, and others. The machine learning
calculations in this paper are the most advanced for
spectrum detection. With 2000 dataset measurements, we
can also calculate location probability, false alarm
probability, response time, miss detection, throughput and
accuracy.
Keywords:
Terms such as the Maximum a posteriori (MAP), higher order moments (HOM), hypothesis testing, false alarm probability, probability of detection have been used to describe spectrum sensing and cognitive satellite communication.
Cite Article:
"Machine Learning Techniques for improving Spectrum Sensing in Satellite Communication System: Review", International Journal of Science & Engineering Development Research (www.ijrti.org), ISSN:2455-2631, Vol.7, Issue 3, page no.73 - 76, March-2022, Available :http://www.ijrti.org/papers/IJRTI2203013.pdf
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ISSN:
2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator