Authors :
Teenu Paul, Shiji Abhraham.
Volume/Issue :
Volume 3 - 2018, Issue 5 - May
Google Scholar :
https://goo.gl/DF9R4u
Scribd :
https://goo.gl/oaSCyL
Thomson Reuters ResearcherID :
https://goo.gl/3bkzwv
Abstract :
To achieve spectrum allocation in cognitive radio grids, channel gain among primary transmitter and receiver is essential for cognitive transmitter. For CT to sense primary signals and to evaluate prime channel gain, new methods such as Maximum Likelihood estimator (ML) as well as Median Based estimator (MB) be proposed. ML principle is adopted to examine received prime signals, thus developed ML estimator. Then Median Based estimator is offered for reducing computational complication of ML estimator, such that CT can calculate interference temperature ofprime system and attain spectrum distribution. Through simulation outcomes, valuation error remains 0.015 in both estimators. To further decreasing unwanted noise, a level based reduction methodbe there used.
Keywords :
Cognitive Radio, Channel gain, Maximum likelihood, Median based Estimation error, Interference.
To achieve spectrum allocation in cognitive radio grids, channel gain among primary transmitter and receiver is essential for cognitive transmitter. For CT to sense primary signals and to evaluate prime channel gain, new methods such as Maximum Likelihood estimator (ML) as well as Median Based estimator (MB) be proposed. ML principle is adopted to examine received prime signals, thus developed ML estimator. Then Median Based estimator is offered for reducing computational complication of ML estimator, such that CT can calculate interference temperature ofprime system and attain spectrum distribution. Through simulation outcomes, valuation error remains 0.015 in both estimators. To further decreasing unwanted noise, a level based reduction methodbe there used.
Keywords :
Cognitive Radio, Channel gain, Maximum likelihood, Median based Estimation error, Interference.
