Convolutional Codes: Mapping Symbols and Paths

Related lectures (27)

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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.