EconPapers    
Economics at your fingertips  
 

Review on Spectrum Sharing Approaches Based on Fuzzy and Machine Learning Techniques in Cognitive Radio Networks

Abdul Sikkandhar Rahamathullah (), Merline Arulraj () and Guruprakash Baskaran ()
Additional contact information
Abdul Sikkandhar Rahamathullah: Sethu Institute of Technology
Merline Arulraj: Sethu Institute of Technology
Guruprakash Baskaran: Sethu Institute of Technology

A chapter in New Trends in Computational Vision and Bio-inspired Computing, 2020, pp 1615-1622 from Springer

Abstract: Abstract Recently Cognitive Radio Networks (CRN) are used for improving the efficiency of spectrum usage. It can select spectrum and operate in a adaptive manner. The spectrum sharing has to be allocated and used efficiently for knowing the performance of CRN. The paper analyzes the different spectrum techniques with its merits and limitations. The existing works namely centralized, distributed, cooperative and non cooperative schemes are investigated. From study it can be concluded that fuzzy based approaches in CRN are more efficient.

Keywords: CRN; Spectrum; Allocation; Slot (search for similar items in EconPapers)
Date: 2020
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-030-41862-5_165

Ordering information: This item can be ordered from
http://www.springer.com/9783030418625

DOI: 10.1007/978-3-030-41862-5_165

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().

 
Page updated 2026-06-08
Handle: RePEc:spr:sprchp:978-3-030-41862-5_165