Search Results for author: S Ashwin Hebbar

Found 4 papers, 2 papers with code

DeepPolar: Inventing Nonlinear Large-Kernel Polar Codes via Deep Learning

no code implementations14 Feb 2024 S Ashwin Hebbar, Sravan Kumar Ankireddy, Hyeji Kim, Sewoong Oh, Pramod Viswanath

Polar codes, developed on the foundation of Arikan's polarization kernel, represent a breakthrough in coding theory and have emerged as the state-of-the-art error-correction-code in short-to-medium block length regimes.

Nested Construction of Polar Codes via Transformers

no code implementations30 Jan 2024 Sravan Kumar Ankireddy, S Ashwin Hebbar, Heping Wan, Joonyoung Cho, Charlie Zhang

Tailoring polar code construction for decoding algorithms beyond successive cancellation has remained a topic of significant interest in the field.

CRISP: Curriculum based Sequential Neural Decoders for Polar Code Family

1 code implementation1 Oct 2022 S Ashwin Hebbar, Viraj Nadkarni, Ashok Vardhan Makkuva, Suma Bhat, Sewoong Oh, Pramod Viswanath

We design a principled curriculum, guided by information-theoretic insights, to train CRISP and show that it outperforms the successive-cancellation (SC) decoder and attains near-optimal reliability performance on the Polar(32, 16) and Polar(64, 22) codes.

TinyTurbo: Efficient Turbo Decoders on Edge

1 code implementation30 Sep 2022 S Ashwin Hebbar, Rajesh K Mishra, Sravan Kumar Ankireddy, Ashok V Makkuva, Hyeji Kim, Pramod Viswanath

In this paper, we introduce a neural-augmented decoder for Turbo codes called TINYTURBO .

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