Lectures related to Binary Coding: Channel Decoding

Channel Coding: Convolutional Codes

Explores channel coding with a focus on convolutional codes, emphasizing error detection, correction, and decoding processes.

Channel Coding and BICM (LLRs)

Explores channel coding, BICM, and LLRs in wireless communication systems, emphasizing the importance of error detection and correction.

Lecture: Shannon

Covers the basics of information theory, focusing on Shannon's setting and channel transmission.

Error Correction Codes: Theory and Applications

Covers error correction codes theory and applications, emphasizing the importance of minimizing distance for reliable communication.

Error Correction Codes: Hamming Code

Explores the Hamming Code for error correction, emphasizing its ability to correct single-bit errors.

Minimum Distance Decoding

Explains Minimum Distance (MD) decoding on erasure channels with illustrative examples.

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.

Polynomials: Operations and Properties

Explores polynomial operations, properties, and subspaces in vector spaces.

Vector Spaces: Properties and Operations

Covers the properties and operations of vector spaces, including addition and scalar multiplication.

Soft-Output MIMO Detection for BICM

Covers Soft-Output MIMO Detection for BICM, LLRs computation, BICM system model, and challenges of channel assumptions.

Information Theory: Source Coding, Cryptography, Channel Coding

Covers source coding, cryptography, and channel coding in communication systems, exploring entropy, codes, error channels, and future related courses.

Linear Algebra: Matrices and Vector Spaces

Covers matrix kernels, images, linear applications, independence, and bases in vector spaces.

Matrix Operations: Determinants and Vector Spaces

Covers strategies for matrix operations and the concept of vector spaces.

Linear Algebra: Abstract Concepts

Introduces abstract concepts in linear algebra, focusing on operations with vectors and matrices.

Error-Correcting Codes

Explores error-correcting codes, decoding processes, constraints satisfaction, randomness in code selection, and error compensation methods.

Matrix Operations and Vector Spaces

Covers elementary matrix operations and vector spaces, including properties and conditions for invertibility.

Convolutional Codes: Decoding and Eye Diagrams

Covers the decoding process of convolutional codes and the analysis of eye diagrams.

Error Correction Codes: Basics

Introduces erasure and error channels, Hamming distance, and error correction codes.

Linear Algebra Basics

Covers fundamental concepts in linear algebra, including linear equations, matrix operations, determinants, and vector spaces.

Error Correction Codes: Decoding and Communication

Explores error correction codes, decoding algorithms, and their role in communication systems.