5G NR CA-Polar Maximum Likelihood Decoding by GRAND

07/01/2019
by   Ken Duffy, et al.
0

CA-Polar codes have been selected for all control channel communications in 5G NR, but accurate, computationally feasible decoders are still subject to development. Here we report the performance of a recently proposed class of optimally precise Maximum Likelihood (ML) decoders, GRAND, that can be used with any block-code. As published theoretical results indicate that GRAND is computationally efficient for short-length, high-rate codes and 5G CA-Polar codes are in that class, here we consider GRAND's utility for decoding them. Simulation results indicate that decoding of 5G CA-Polar codes by GRAND, and a simple soft detection variant, is a practical possibility.

READ FULL TEXT
research
01/09/2020

Soft Maximum Likelihood Decoding using GRAND

Maximum Likelihood (ML) decoding of forward error correction codes is kn...
research
06/28/2021

Efficient Maximum Likelihood Decoding of Polar Codes Over the Binary Erasure Channel

A new algorithm for efficient exact maximum likelihood decoding of polar...
research
11/09/2022

Neural network concatenation for Polar Codes

When a neural network (NN) is used to decode a polar code, its training ...
research
10/08/2019

Approaching the Finite Blocklength Capacity within 0.025dB by Short Polar Codes and CRC-Aided Hybrid Decoding

In this letter, we explore the performance limits of short polar codes a...
research
05/02/2023

Rate-Compatible Polar Codes for Automorphism Ensemble Decoding

Recently, automorphism ensemble decoding (AED) has drawn research intere...
research
07/15/2021

On Hard and Soft Decision Decoding of BCH Codes

Cyclic codes have the advantage that it is only necessary to store one p...
research
03/20/2023

Dynamic Frozen-Function Design for Reed-Muller Codes With Automorphism-Based Decoding

In this letter, we propose to add dynamic frozen bits to underlying pola...

Please sign up or login with your details

Forgot password? Click here to reset