Lectures related to Convolutional Codes: Mapping Symbols and Paths

Explains the encoding and decoding process of convolutional codes using constellation prints.

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

Covers the decoding and performance analysis of convolutional codes in communication systems.

Explores the basics and applications of convolutional codes in communication systems.

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

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

Delves into the analysis and applications of convolutional codes, highlighting the significance of correct implementation for optimal results.

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

Covers Convolutional Codes, Viterbi Algorithm, state and branch metric computations, and survivor path length limitations.

Covers the introduction of Convolutional Coder, explaining its structure and operation.

Covers the art of designing convolutional codes to improve communication rate.

Explores binary channel decoding and vector spaces in coding theory.

Covers the proof and properties of the coding theorem, focusing on maximizing the properties of lx and the achievable rate.

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

Explores error correction codes, focusing on structure, properties, and the Singleton bound.

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

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

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

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

Explains quantum correction codes using two classic codes to correct errors, focusing on goal flips and headlight flips.