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Signal-to-noise ratio (SNR) is a dimensionless measure that quantifies the ratio of the power of a desired signal to the power of background noise in a communication or measurement system. Expressed in decibels (dB), SNR is calculated as ten times the base-10 logarithm of the signal power divided by the noise power, or equivalently as twenty times the logarithm of the amplitude ratio when signal and noise are measured across the same impedance [1]. A positive SNR indicates that the signal power exceeds the noise power, while a negative SNR indicates that noise dominates [2]. SNR serves as a fundamental metric for assessing system fidelity, receiver sensitivity, and the reliability of data transmission across analog and digital communication channels [3]. In digital communications, SNR is directly related to bit error rate through modulation-specific relationships, where higher SNR values correspond to lower error probabilities [4]. The measure is applied across electrical engineering, acoustics, imaging, and spectroscopy, although the precise definition of signal and noise power may vary by domain [5].
References
- Sklar, B. Digital Communications: Fundamentals and Applications, 2nd ed.; Prentice Hall: Upper Saddle River, NJ, USA, 2001.
- Proakis, J.G.; Manolakis, D.G. Digital Signal Processing: Principles, Algorithms, and Applications, 4th ed.; Pearson: Upper Saddle River, NJ, USA, 2007.
- Couch, L.W. Digital and Analog Communication Systems, 8th ed.; Pearson: Upper Saddle River, NJ, USA, 2013.
- Goldsmith, A. Wireless Communications; Cambridge University Press: Cambridge, UK, 2005.
- Oppenheim, A.V.; Schafer, R.W. Discrete-Time Signal Processing, 3rd ed.; Pearson: Upper Saddle River, NJ, USA, 2010.
