Arikan Meets Shannon - Polar Codes With Near-Optimal Convergence to Channel Capacity
Offered By: Association for Computing Machinery (ACM) via YouTube
Course Description
Overview
Explore the groundbreaking concept of polar codes and their near-optimal convergence to channel capacity in this 26-minute conference talk. Delve into binary-input discrete symmetric memoryless channels, channel coding with linear codes, and Shannon capacity. Examine entropy polarization, recursive applications, and scaling exponents for polar codes. Investigate strong local polarization for BEC and BMS channels, focusing on single kernel analysis. Conclude with insights into bit-decoding of random linear codes, gaining a comprehensive understanding of this innovative approach to information theory and coding.
Syllabus
Intro
Binary-input Discrete Symmetric Memoryless Channel
Examples of BMS channels
Channel coding with linear codes
Shannon capacity
Channel entropy & capacity
Entropy Polarization
Recursive application
Scaling exponents for polar codes
Strong local polarization for BEC
Strong local polarization for BMS channel
3: single kernel
Bit-decoding of random linear codes
Taught by
Association for Computing Machinery (ACM)
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