Open AccessDistributed Channel Allocation Using Kernel Density Estimation in Cognitive Radio Networks
Author(s) -
Ahmed M. Ejaz,
Kim Joo Seuk,
Mao Runkun,
Song Ju Bin,
Li Husheng
Publication year - 2012
Publication title -
etri journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.295
H-Index - 46
eISSN - 2233-7326
pISSN - 1225-6463
DOI - 10.4218/etrij.12.0211.0537
Subject(s) - cognitive radio , channel (broadcasting) , computer science , network packet , channel allocation schemes , idle , throughput , schedule , computer network , kernel density estimation , parametric statistics , algorithm , wireless , telecommunications , mathematics , statistics , estimator , operating system
Typical channel allocation algorithms for secondary users do not include processes to reduce the frequency of switching from one channel to another caused by random interruptions by primary users, which results in high packet drops and delays. In this letter, with the purpose of decreasing the number of switches made between channels, we propose a nonparametric channel allocation algorithm that uses robust kernel density estimation to effectively schedule idle channel resources. Experiment and simulation results demonstrate that the proposed algorithm outperforms both random and parametric channel allocation algorithms in terms of throughput and packet drops.