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AEU - International Journal of Electronics and Communications

Deep learning-enabled polar code decoders for 5G networks and beyond

M. Meenalakshmi, Saurabh Chaturvedi, Vivek K. Dwivedi

Published Mar 6, 2024• 16 citations
Publisher
DOI
10.1016/j.aeue.2024.155220

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In the 5G communication systems, a hybrid approach to support polar codes for control plane and LDPC codes for data plane has been identified as the channel coding solution for enhanced mobile broadband (eMBB) scenario. One of the major challenges to implement this approach is to design powerful decoders at the terminal side. Inspired from a useful machine learning based polar decoder, we proposed a deep learning based unified polar-LDPC by concatenating an indicator section. Through numerical experiments, we show that the proposed deep neural network (DNN) based decoding architecture can achieve the similar decoding performance compared with the traditional BP-based decoding algorithm. Meanwhile, the proposed unified approach shares the same network architecture and parameters with isolated approaches, which saves significant implementation resources consequently.
In 5G mobile communication standard, polar codes have been used as coding on control channels. Although the polar code has good performance, the performance of its short code is still facing huge challenges. Moreover, the size limitation of using the deep learning model as the decoder of the polar code has always been the focus of researchers seeking a breakthrough. In this paper, the convolutional neural network (CNN) model in deep learning is cascaded with a successive cancellation (SC) decoder to achieve the decoding of polar codes under additive correlated Gaussian noise (ACGN) channels, thereby improving the decoding performance of short polar codes under ACGN and alleviating the code length limitation of a single deep learning model as a decoder. The cascaded decoding structure is represented as a CNN-SC decoder, which can effectively estimate colored noise. The simulation shows that the CNN-SC decoder improves the performance of polar codes under ACGN channels significantly.