Construction of Polar Codes with Reinforcement Learning

2020-09-19 · Yun Liao, Seyyed Ali Hashemi, John Cioffi, Andrea Goldsmith

This paper formulates the polar-code construction problem for the successive-cancellation list (SCL) decoder as a maze-traversing game, which can be solved by reinforcement learning techniques. The proposed method provides a novel technique for polar-code construction that no longer depends on sorting and selecting bit-channels by reliability. Instead, this technique decides whether the input bits should be frozen in a purely sequential manner. The equivalence of optimizing the polar-code construction for the SCL decoder under this technique and maximizing the expected reward of traversing a maze is drawn. Simulation results show that the standard polar-code constructions that are designed for the successive-cancellation decoder are no longer optimal for the SCL decoder with respect to the frame error rate. In contrast, the simulations show that, with a reasonable amount of training, the game-based construction method finds code constructions that have lower frame-error rate for various code lengths and decoders compared to standard constructions.

📄 PDF Abstract BibTeX arXiv:2009.09277

Code (0)

등록된 구현이 없습니다.

Tasks

Decoder reinforcement-learning Reinforcement Learning Reinforcement Learning (RL)

A Modified Q-Learning Algorithm for Rate-Profiling of Polarization Adjusted Convolutional (PAC) Codes

2021-10-04 · Samir Kumar Mishra, Digvijay Katyal, Sarvesha Anegundi Ganapathi

In this paper, we propose a reinforcement learning based algorithm for rate-profile construction of Arikan's Polarization Assisted Convolutional (PAC) codes. This method can be used for any blocklength, rate, list size u…

Q-Learning reinforcement-learning Reinforcement Learning Reinforcement Learning (RL)

Scalable Polar Code Construction for Successive Cancellation List Decoding: A Graph Neural Network-Based Approach

2022-07-03 · Yun Liao, Seyyed Ali Hashemi, Hengjie Yang, John M. Cioffi

While constructing polar codes for successive-cancellation decoding can be implemented efficiently by sorting the bit-channels, finding optimal polar codes for cyclic-redundancy-check-aided successive-cancellation list (…

Graph Neural Network

Nested Construction of Polar Codes via Transformers

2024-01-30 · Sravan Kumar Ankireddy, S Ashwin Hebbar, Heping Wan, Joonyoung Cho 외

Tailoring polar code construction for decoding algorithms beyond successive cancellation has remained a topic of significant interest in the field. However, despite the inherent nested structure of polar codes, the use o…

Reinforcement Learning for Nested Polar Code Construction

2019-04-16 · Lingchen Huang, Huazi Zhang, Rong Li, Yiqun Ge 외

In this paper, we model nested polar code construction as a Markov decision process (MDP), and tackle it with advanced reinforcement learning (RL) techniques. First, an MDP environment with state, action, and reward is d…

reinforcement-learning Reinforcement Learning Reinforcement Learning (RL)

Convolutional Polar Codes on Channels with Memory using Tensor Networks

2019-06-15 · Conference 2019 6 · Benjamin Bourassa，Maxime Tremblay，David Poulin

Arikan’s recursive code construction is designed to polarize a collection of memoryless channels into a set of good and a set of bad channels, and it can be efficiently decoded using successive cancellation [1]. It was…

Decoder Tensor Networks