This module delves into Fourier series, including measures, Fourier series, and Fourier transforms. Students will learn how these mathematical concepts are applied in analyzing and designing communication systems.
This module provides an introduction to digital communication, emphasizing a layered view that helps understand the complex interactions in communication systems. Students will learn about various layers, including physical, data link, and network layers, and how they contribute to effective communication.
This module focuses on discrete source encoding, an essential technique for efficient data transmission. Students will explore various encoding methods and how they can reduce data size while preserving the integrity of the transmitted information.
This module discusses memory-less sources, prefix-free codes, and the concept of entropy. Students will learn how these concepts are crucial for understanding data compression and the fundamental limits of information transmission.
This module covers entropy and the Asymptotic Equipartition Property (AEP), which are foundational concepts in information theory. Students will learn how these concepts relate to data encoding and the efficiency of communication systems.
This module explores Markov sources and the Lempel-Ziv universal codes, providing insight into how these concepts can be applied to data compression and efficient encoding strategies in communication systems.
This module introduces quantization, a crucial process in digital communication that converts continuous signals into discrete data. Students will learn about various quantization techniques and their applications in data transmission.
This module addresses high-rate quantizers and waveform encoding, discussing how these techniques are applied in modern communication systems to achieve efficient data representation and transmission.
This module delves into Fourier series, including measures, Fourier series, and Fourier transforms. Students will learn how these mathematical concepts are applied in analyzing and designing communication systems.
This module focuses on discrete-time Fourier transforms and the sampling theorem. Students will learn the critical relationship between continuous and discrete signals and the implications for communication system design.
This module covers degrees of freedom, orthonormal expansions, and aliasing. Students will learn how these concepts relate to the capacity of communication channels and effective data transmission.
This module discusses signal space, the projection theorem, and modulation techniques. Students will gain insights into how these concepts are foundational for designing efficient communication systems.
This module introduces Nyquist theory, covering pulse amplitude modulation (PAM), quadrature amplitude modulation (QAM), and frequency translation. Students will learn how these modulation techniques are implemented in real-world communication systems.
This module focuses on random processes, providing students with an understanding of how random variables and processes are used to model communication systems and analyze their performance.
This module discusses jointly Gaussian random vectors and processes, focusing on white Gaussian noise (WGN). Students will learn how these concepts are essential for understanding noise in communication systems.
This module covers linear functionals and filtering of random processes, discussing how these concepts apply to signal processing and communication systems. Students will learn about filtering techniques and their importance in data transmission.
This module serves as a review and introduction to detection methods, emphasizing their significance in communication systems. Students will explore various detection techniques and their applications in real-world scenarios.
This module examines detection techniques for random vectors and processes, providing insights into how these methods can be applied to improve communication system performance under various conditions.
This module introduces the theorem of irrelevance, M-ary detection, and coding, discussing how these concepts are crucial in optimizing communication systems for efficient data transmission.
This module focuses on baseband detection and complex Gaussian processes, exploring their applications in communication systems. Students will learn how these concepts are utilized to enhance detection performance.
This module introduces wireless communication, discussing its principles and challenges. Students will gain insights into the unique aspects of wireless systems compared to traditional wired communication.
This module focuses on Doppler spread, time spread, coherence time, and coherence frequency. Students will learn how these concepts impact wireless communication system design and performance.
This module covers discrete-time baseband models for wireless channels, providing students with the tools to analyze and simulate wireless communication systems effectively.
This module examines detection for flat Rayleigh fading and incoherent channels, discussing techniques such as rake receivers. Students will learn how these methods improve communication in challenging environments.
This module presents a case study on Code Division Multiple Access (CDMA), illustrating how this technique enables multiple users to share the same communication medium effectively.