Signal Processing
Bridging the analog and digital worlds — from sampling and conversion to filtering and modulation, signal processing underpins every modern communication system.
Signal Processing Pipeline
About Part V
Signal processing is the set of techniques used to acquire, transform, and transmit information encoded in physical signals. In the analog domain, signals vary continuously; in the digital domain, they are represented as discrete numbers. Converting between the two — sampling, quantizing, reconstructing — is governed by the Nyquist–Shannon sampling theorem:
\[ f_s \;\geq\; 2\,f_{max} \]
Once in the digital domain, signals can be filtered with extraordinary precision using finite impulse response (FIR) or infinite impulse response (IIR) filters. They can be modulated onto carriers for wireless transmission — AM, FM in the analog world; QAM-64 or OFDM in the digital. The three chapters of Part V cover each stage of this pipeline.
Quantization introduces noise: an N-bit ADC achieves \(\text{SNR} \approx 6.02N + 1.76\) dB of dynamic range. A 16-bit audio ADC delivers ~98 dB SNR — far exceeding the 60 dB range of human hearing.
Key Equations
Chapters
Ch 13: Sampling, ADC & DAC
Nyquist–Shannon theorem, aliasing, quantization noise, flash/SAR/sigma-delta converters, R-2R DAC, and SNR vs bit depth.
Ch 14: Analog & Digital Filters
Transfer functions, Butterworth, Chebyshev and Bessel designs, FIR vs IIR digital filters, windowed sinc, and bilinear transform.
Ch 15: Modulation & Demodulation
AM (DSB-SC, DSB-LC, SSB), FM, PM, superheterodyne receivers, digital modulation (ASK, FSK, PSK, QAM), and BER curves.