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On Performance of Weighted Fusion Based Spectrum Sensing in Fading Channels
Author(s) -
Srinivas Nallagonda,
Shravan Kumar Bandari,
Sanjay Dhar Roy,
Sumit Kundu
Publication year - 2013
Publication title -
journal of computational engineering
Language(s) - English
Resource type - Journals
eISSN - 2356-7260
pISSN - 2314-6443
DOI - 10.1155/2013/270612
Subject(s) - cognitive radio , nakagami distribution , rician fading , weighting , fading , computer science , fusion rules , channel (broadcasting) , additive white gaussian noise , electronic engineering , statistic , algorithm , wireless , statistics , telecommunications , mathematics , engineering , artificial intelligence , physics , acoustics , image (mathematics) , image fusion
Cognitive radio (CR) is a promising technology for efficient utilization of underutilized spectrum since it is able to detect the occupancy of primary users (PUs) in the different parts of the spectrum. As the sensing channel uncertainties limit the reliability of the spectrum sensing decision, cooperation among multiple CR users is often used to improve the spectrum sensing decision. In this paper, the performance of single CR user based spectrum sensing and cooperative CR user based spectrum sensing (CSS) has been assessed in several channels such as AWGN, log-normal, Hoyt (or Nakagami-q), Rayleigh, Rician (or Nakagami-n), Nakagami-m, and Weibull channels. The performance of two spectrum sensing schemes based on assigning weights to CR users such as (a) weighting according to sensing channel preference and (b) weighting according to the value of decision statistic is evaluated. The performance comparison between two weighting schemes under several fading channels has been made. The performance of proposed CSS has been illustrated through complementary receiver operating characteristics (CROC) for different fading channels. The effects of weighting factors (k and Rf) on overall missed detection performance are shown. The performance of CSS with OR-logic fusion as a special case is also presented for comparison purpose.

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