Fundamentals of Communication Theory: Analog to Digital

Fundamentals of Communication Theory: Analog to Digital by Unnikrishna Pillai, Anuj Patel
English | 2026 | True PDF | 175 pages | 20.3 Mb

This unique textbook – made up of classroom slides and relevant context from the authors’ course at NYU – provides a clear, step-by-step journey from the fundamentals of signal analysis to the sophisticated modulation and detection strategies that power today’s communication systems. Beginning with intuitive treatments of Fourier Series, Fourier Transforms, and Nyquist’s Sampling Theorem, the book builds the mathematical intuition students need to move confidently into analog and digital modulation techniques-covering AM (DSB, SSB, VSB), FM, PM, and their behavior in noisy environments.

The narrative then turns to modern digital topics such as sampling, quantization, coding, and probabilistic detection for binary and multi-signaling schemes, showing how error probabilities can be driven arbitrarily low with thoughtful waveform design. Rich in worked examples and practical insights, the text equips undergraduates with both the theoretical grounding and hands on perspective required to understand, analyze, and design real world communication links. The book is designed for a semester undergraduate course in Fundamentals of Communication Theory, and the slides are intended to be used and are available digitally.

Building upon amplitude modulation, a detailed study of Angle Modulation is carried out in this chapter covering both Frequency Modulation (FM) and Phase Modulation (PM). The chapter begins by examining the fundamental principles of frequency and phase modulation, comparing peak versus average transmitted power levels, and analyzing the efficiency of different modulation techniques. Key practical aspects are introduced, such as Carson’s Rule for estimating FM/PM bandwidth, Armstrong’s method for generating wideband FM from narrowband FM, and receiver architectures designed to handle noise in real-world systems. A significant portion of the discussion focuses on noise analysis, contrasting the performance of AM and FM/PM systems. Concepts such as signal-to-noise ratio (SNR), noise modeling, and filtering techniques are systematically introduced, showing how FM and PM provide better protection against noise compared to AM. Both the advantages and disadvantages of FM/PM are highlighted, giving a balanced view of their role in communication systems.

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