Aims: In the context of modern times where most of the network infrastructure is technology
dependent, it becomes imperative to cumulate the perceptive regarding the contrivance of the concept of
correlational analysis in communication domain as well. Hence, a Canonical Corelational Analysis (CCA)
based Signal-to-Noise Ratio (SNR) estimation scheme for Frequency Hopped (FH) signals amidst a sumof-
sinusoids based Nakagami- m fading channel is proposed.
Objective: Spectrum Sensing (SS) is enunciated using maximum eigenvalue of the received signal’s covariance
matrix obtained by the proposed CCA approach.
Methods: The SNR of the sensed FH signals is evaluated using a conventional moment-based M2M4
Results: Consequently, on contemplating the outcomes in terms of Normalized Mean Square Error
(NMSE), it can be substantiated that the application of CCA approach is pertinent enough for reliable low
range SNR estimation up to -5dB.
Conclusion: Meanwhile, due to efficient multivariate analysis, CCA fosters statistical efficiency in terms
of modulation identification that reduces the complexity of computation.