Signal Processing for Communication Systems
Skeptical of ‘Black Box’ AI? We prove that a 1D Convolutional Neural Network (CNN) is mathematically identical to an adaptive FIR filter. Includes Python code to train a CNN to reinvent the Matched Filter and visualize its frequency response.
Let’s see how to design a simple digital FIR filter to reject unwanted frequencies in an incoming signal. As a per-requisite, I urge you to read through this post: Introduction to digital filter design Background on transfer function The transfer function of a system provides the underlying support for ascertaining vital system response characteristics without … Read more
Key focus: Develop basic understanding of digital filter design. Learn about fundamentals of FIR and IIR filters and the design choices. Analog filters and digital filters are the two major classification of filters, depending on the type of signal signal they process. An analog filter, processes continuous-time signal analog signals. Whereas, digital filters process sampled, … Read more
Introduction to precoding Intersymbol interference (ISI) is a common problem in telecommunication systems, such as terrestrial television broadcasting, digital data communication systems, and cellular mobile communication systems. Dispersive effects in high-speed data transmission and multipath fading are the main reasons for ISI. To maximize the capacity, the transmission bandwidth must be extended to the entire … Read more
FIR vs IIR tradeoffs: linear phase, stability, order, and when each wins — with links to digital filter design articles.
Fading Lab path: Fading models → Young → Clarke SOS → BPSK BER Rayleigh → MRC Keyfocus: Fading channel models for simulation. Learn how fading channels can be modeled as FIR filters for simplified modulation & detection. Rayleigh/Rician fading. Introduction A fading channel is a wireless communication channel in which the quality of the … Read more