Concept
MIMO
Related lectures (79)
Information Theory: Source Coding
Covers source coding, typical sequences, stationarity, and efficient encoding in information theory.
Coding Theorem: Proof and Properties
Covers the proof and properties of the coding theorem, focusing on maximizing the properties of lx and the achievable rate.
Channel Coding: Theory & Coding
Covers the formation theory and coding, focusing on channel capacity and concave functions.
Random Coding: Achievability and Proof Variants
Explores random coding achievability and proof variants in information theory, emphasizing achievable rates and architectural principles.
Information Theory: Entropy and Capacity
Covers concepts of entropy, Gaussian distributions, and channel capacity with constraints.
Binary Coding: Channel Decoding
Explores binary channel decoding and vector spaces in coding theory.
Communication Channels: Gaussian Noise and Capacity
Explores the capacity of communication channels with Gaussian noise and noise impact.
Communication Channels: Encoding and Decoding
Explores encoding and decoding techniques in communication systems, focusing on fundamental limits and mutual information computations.
Error Correction Codes: Theory and Applications
Covers error correction codes theory and applications, emphasizing the importance of minimizing distance for reliable communication.
Convolutional Codes: Decoding and Eye Diagrams
Covers the decoding process of convolutional codes and the analysis of eye diagrams.