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As the amplitude of the AWGN is increased, the signal-to-noise ratio decreases. This results in increased uncertainty Δt. [1] When affected by AWGN, the average number of either positive-going or negative-going zero crossings per second at the output of a narrow bandpass filter when the input is a sine wave is
Here an AWGN channel is assumed. In digital communication or data transmission, / (energy per bit to noise power spectral density ratio) is a normalized signal-to-noise ratio (SNR) measure, also known as the "SNR per bit".
Rayleigh fading is a statistical model for the effect of a propagation environment on a radio signal, such as that used by wireless devices.. Rayleigh fading models assume that the magnitude of a signal that has passed through such a transmission medium (also called a communication channel) will vary randomly, or fade, according to a Rayleigh distribution — the radial component of the sum of ...
In signal processing theory, Gaussian noise, named after Carl Friedrich Gauss, is a kind of signal noise that has a probability density function (pdf) equal to that of the normal distribution (which is also known as the Gaussian distribution).
In telecommunications, maximum-ratio combining (MRC) is a method of diversity combining in which: . the signals from each channel are added together,; the gain of each channel is made proportional to the rms signal level and inversely proportional to the mean square noise level in that channel.
A n-dimensional complex random vector = (, …,) is a complex standard normal random vector or complex standard Gaussian random vector if its components are independent and all of them are standard complex normal random variables as defined above.
In fact, it was shown that LDPC codes can reach within 0.0045 dB of the Shannon limit (for binary additive white Gaussian noise (AWGN) channels, with very long block lengths). [ 1 ] Mathematical statement
Detection of a Gaussian random signal in Additive white Gaussian noise (AWGN) [ edit ] When the signal we want to detect from the noisy channel is also random, for example, a white Gaussian process X ( t ), we can still implement K–L expansion to get independent sequence of observation.