Signal Processing for Communication Systems
Convert Eb/N0 to Es/N0 and SNR for AWGN BER simulations: definitions, complex baseband noise variance, oversampling notes, Python/Matlab code, and the pitfalls that shift Monte Carlo curves by 3 dB.
Practical steps and runnable examples to migrate signal‑processing code from Matlab to Python, with tips for testing, performance, and reproducibility.
Line code is the signaling scheme used to represent data on a communication line. There are several possible mapping schemes available for this purpose. Lets understand and demonstrate line code and PSD (power spectral density) in Matlab & Python. Line codes – requirements When transmitting binary data over long distances encoding the binary data using … Read more
Fading & Diversity — 6 lessons (same on every page in this path) 1. Rayleigh BER → 2. Clarke’s model (you are here) → 3. Young’s model → 4. SIMO models → 5. Selection combining → 6. MRC Tools: BER vs Eb/N0 · 3GPP TDL · CDL / Doppler Optional branch from Fading & Diversity. … Read more
Simulate BPSK bit-error rate in Python and Matlab, compare Monte Carlo curves to the Q-function formula, and open the same points on the BER calculator.
The phase transition properties of the different variants of QPSK schemes and MSK, are easily investigated using constellation diagram. Let’s demonstrate how to plot the signal space constellations, for the various modulations used in the transmitter. Typically, in practical applications, the baseband modulated waveforms are passed through a pulse shaping filter for combating the phenomenon … Read more
Key focus: Learn how to generate color noise using auto regressive (AR) model. Apply Yule Walker equations for generating power law noises: pink noise, Brownian noise. Auto-Regressive (AR) model An uncorrelated Gaussian random sequence \(x[n]\) can be transformed into a correlated Gaussian random sequence \(y[n]\) using an AR time-series model. If a time series random … Read more
The aim of this article is to demonstrate the application of spectral factorization method in generating colored noise having Jakes power spectral density. Before continuing, I urge the reader to go through this post: Introduction to generating correlated Gaussian sequences. In spectral factorization method, a filter is designed using the desired frequency domain characteristics (like … Read more
Gaussian Minimum Shift Keying basics: MSK as CPM, Gaussian filter BT, smoother phase, and spectral compactness vs plain MSK.
Introduction An exponential random variable (RV) is a continuous random variable that has applications in modeling a Poisson process. Poisson processes find extensive applications in tele-traffic modeling and queuing theory. They are used to model random points in time or space, such as the times when call requests arriving at an exchange, the times when … Read more