Lecture

Convolutional Codes: Encoding and Decoding

Graph Chat

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.

Description

This lecture covers the encoding and decoding process of convolutional codes, focusing on selecting from the corners of the hypercube to create constellation prints. Emre Telatar explains the method step by step, highlighting the significance of selecting specific corners for efficient encoding.

Official source

Ontological neighbourhood

Information engineering

Information theory: Coding theory

Related concepts (32)

Convolutional code

In telecommunication, a convolutional code is a type of error-correcting code that generates parity symbols via the sliding application of a boolean polynomial function to a data stream. The sliding application represents the 'convolution' of the encoder over the data, which gives rise to the term 'convolutional coding'. The sliding nature of the convolutional codes facilitates trellis decoding using a time-invariant trellis. Time invariant trellis decoding allows convolutional codes to be maximum-likelihood soft-decision decoded with reasonable complexity.

Space–time block code

Space–time block coding is a technique used in wireless communications to transmit multiple copies of a data stream across a number of antennas and to exploit the various received versions of the data to improve the reliability of data transfer. The fact that the transmitted signal must traverse a potentially difficult environment with scattering, reflection, refraction and so on and may then be further corrupted by thermal noise in the receiver means that some of the received copies of the data may be closer to the original signal than others.

Turbo code

In information theory, turbo codes (originally in French Turbocodes) are a class of high-performance forward error correction (FEC) codes developed around 1990–91, but first published in 1993. They were the first practical codes to closely approach the maximum channel capacity or Shannon limit, a theoretical maximum for the code rate at which reliable communication is still possible given a specific noise level. Turbo codes are used in 3G/4G mobile communications (e.g.

2G is a short notation for second-generation cellular network, a group of technology standards employed for cellular networks. 2G was commercially launched on the GSM standard in Finland by Radiolinja (now part of Elisa Oyj) in 1991. After 2G was launched, the previous mobile wireless network systems were retroactively dubbed 1G. While radio signals on 1G networks are analog, radio signals on 2G networks are digital, though both systems use digital signaling to connect cellular radio towers to the rest of the mobile network system.

Error correction code

In computing, telecommunication, information theory, and coding theory, forward error correction (FEC) or channel coding is a technique used for controlling errors in data transmission over unreliable or noisy communication channels. The central idea is that the sender encodes the message in a redundant way, most often by using an error correction code or error correcting code (ECC). The redundancy allows the receiver not only to detect errors that may occur anywhere in the message, but often to correct a limited number of errors.

Related lectures (64)

Convolutional Codes: Mapping Symbols and Paths

Covers Convolutional Codes, focusing on mapping symbols and paths.

Error Correction Codes: Decoding and Communication

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

Convolutional Codes: Decoding and Performance Analysis

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

Quantum Correction Codes 4

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

Channel Coding: Convolutional Codes

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

Related concepts (32)

Convolutional code

Space–time block code

Turbo code

Error correction code