Design polar codes with large kernels based on reciprocal channel approximation

Le Chen; Zhiliang Huang; Youyan Zhang; Shuihong Zhou

doi:10.1117/12.3017355

15 December 2023 Design polar codes with large kernels based on reciprocal channel approximation

Le Chen, Zhiliang Huang, Youyan Zhang, Shuihong Zhou

Proceedings Volume 12971, Third International Conference on Optics and Communication Technology (ICOCT 2023); 129710R (2023) https://doi.org/10.1117/12.3017355
Event: Third International Conference on Optics and Communication Technology (ICOCT 2023), 2023, Changchun, China

Abstract

In this paper, the reciprocal channel approximation (RCA) method is used to design polar codes with large kernels. Firstly, based on the given large kernels, we obtain the encoder graph. Secondly, the bit-channel SNR parameters are successively updated according to the encoder graph by the RCA. Finally, the frozen bits are selected by the SNR of the last bit-channels. The RCA method can avoid the distortion caused by the kernel matrix being too large. Furthermore, in the calculation process, the closed-form expression of the channel capacity is used to avoid excessive use of transcendental functions, which can greatly reduce the calculation cost. The experimental results show that for the G₃^⊗5 and G₅^⊗3 with lengths of 243 and 125, and bit rates of 1/2, when the channel SNR is more than 3dB and 2.5dB, respectively, polar codes with large kernels designed by our scheme have better frame error rate than the Gaussian approximation (GA) method.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Le Chen, Zhiliang Huang, Youyan Zhang, and Shuihong Zhou "Design polar codes with large kernels based on reciprocal channel approximation", Proc. SPIE 12971, Third International Conference on Optics and Communication Technology (ICOCT 2023), 129710R (15 December 2023); https://doi.org/10.1117/12.3017355

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available