Publication

Polar coding: a brief tour

Emre Telatar
2010
Conference Papers

Abstract

Arikan's 'polar coding' is a technique to achieve the symmetric capacity of binary input memoryless channels. In this talk I will attempt to describe this technique, and briefly discuss its extensions to q-ary input channels, multiple access channels and rate-distortion coding. The underlying principle of polar coding allows one to view randomness from a different vantage. I will try to illustrate this with a recent result of Sasoglu: when a binary ergodic process is transformed by Arikan's 'polar transform' the resulting process, in the limit, consists only of fair coin flips or constants.

Official source

https://infoscience.epfl.ch/entities/publication/c28aaadf-cfd1-486e-80cc-c20db9c1bd91

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Emre Telatar
2010
Conference Papers

Abstract

Official source

https://infoscience.epfl.ch/entities/publication/c28aaadf-cfd1-486e-80cc-c20db9c1bd91

About this result

Related concepts (32)

Rate–distortion theory

Rate–distortion theory is a major branch of information theory which provides the theoretical foundations for lossy data compression; it addresses the problem of determining the minimal number of bits per symbol, as measured by the rate R, that should be communicated over a channel, so that the source (input signal) can be approximately reconstructed at the receiver (output signal) without exceeding an expected distortion D. Rate–distortion theory gives an analytical expression for how much compression can be achieved using lossy compression methods.

Binary symmetric channel

A binary symmetric channel (or BSCp) is a common communications channel model used in coding theory and information theory. In this model, a transmitter wishes to send a bit (a zero or a one), and the receiver will receive a bit. The bit will be "flipped" with a "crossover probability" of p, and otherwise is received correctly. This model can be applied to varied communication channels such as telephone lines or disk drive storage.

Bernoulli process

In probability and statistics, a Bernoulli process (named after Jacob Bernoulli) is a finite or infinite sequence of binary random variables, so it is a discrete-time stochastic process that takes only two values, canonically 0 and 1. The component Bernoulli variables Xi are identically distributed and independent. Prosaically, a Bernoulli process is a repeated coin flipping, possibly with an unfair coin (but with consistent unfairness). Every variable Xi in the sequence is associated with a Bernoulli trial or experiment.

Related publications (7)

Polar coding: a brief tour

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