Channel Coding: Convolutional Codes

Related lectures (24)

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Explores binary channel decoding and vector spaces in coding theory.

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

Explores cosets, syndromes, and error probability in linear codes.

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

Covers error correction in quantum computing using Hamming codes and syndrome decoding.

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

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

Covers Convolutional Codes, focusing on mapping symbols and paths.

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

Discusses linear codes' dimension and Hamming weight with examples and theorems.