We have been using a wireless signal model in our simulations without going into the details of noise calibration for simulation. In this article we discuss this. Lets assume the received signal is given as
where r(t) is the received signal s(t) is the transmitted signal and n(t) is the Additive White Gaussian Noise (AWGN). Channel fading is ignored at the moment. Signal to noise ratio for simulation of digital communication systems is given as
Where Eb is the energy per bit and No is the noise Power Spectral Density (PSD). We also know that for the case of Additive White Gaussian Noise the noise power is given as [Tranter]
If the energy per bit and the sampling frequency is set to 1 the above equation reduces to
The simulation software can thus calculate the noise standard deviation (or variance) for each value of Eb/No in the simulation cycle. The following piece of MATLAB code generates AWGN with the required power and adds it to the transmitted signal.
s=sign(rand-0.5); % Generate a symbol sigma=1/sqrt(2*EbNo); % Calculate noise standard deviation n=sigma*randn; % Generate AWGN with the required std dev r=s+n; % Add noise to the signal
How can we assume that energy per bit and sampling frequency is equal to one and are we breaking some discrete time signal processing rule here. This will be discussed in a later post.
Author: Yasir Ahmed (aka John)
More than 20 years of experience in various organizations in Pakistan, USA and Europe. Worked as Research Assistant within Mobile and Portable Radio Group (MPRG) of Virginia Tech and was one of the first researchers to propose Space Time Block Codes for eight transmit antennas. The collaboration with MPRG continued even after graduating with an MSEE degree and has resulted in 12 research publications and a book on Wireless Communications. Worked for Qualcomm USA as an Engineer with the key role of performance and conformance testing of UMTS modems. Qualcomm is the inventor of CDMA technology and owns patents critical to the 5G and 4G standards.