DLSTM-Based Successive Cancellation Flipping Decoder for Short Polar Codes

Polar code has been adopted as the control channel coding scheme for the fifth generation (5G), and the performance of short polar codes is receiving intensive attention. The successive cancellation flipping (SC flipping) algorithm suffers a significant performance loss in short block lengths. To address this issue, we propose a double long short-term memory (DLSTM) neural network to locate the first error bit. To enhance the prediction accuracy of the DLSTM network, all frozen bits are clipped in the output layer. Then, Gaussian approximation is applied to measure the channel reliability and rank the flipping set to choose the least reliable position for multi-bit flipping. To be robust under different codewords, padding and masking strategies aid the network architecture to be compatible with multiple block lengths. Numerical results indicate that the error-correction performance of the proposed algorithm is competitive with that of the CA-SCL algorithm. It has better performance than the machine learning-based multi-bit flipping SC (ML-MSCF) decoder and the dynamic SC flipping (DSCF) decoder for short polar codes.

[1]  An-Yeu Wu,et al.  Low-Complexity LSTM-Assisted Bit-Flipping Algorithm For Successive Cancellation List Polar Decoder , 2019, ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

[2]  Rong Li,et al.  Learning to Flip Successive Cancellation Decoding of Polar Codes with LSTM Networks , 2019, 2019 IEEE 30th Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC).

[3]  Yanxia Sun,et al.  A Deep Long Short-Term Memory based classifier for Wireless Intrusion Detection System , 2020, ICT Express.

[4]  Kai Niu,et al.  Multi-Bit-Flipping Decoding of Polar Codes Based on Medium-Level Bit-Channels Sets , 2019, 2019 IEEE Wireless Communications and Networking Conference (WCNC).

[5]  Warren J. Gross,et al.  Neural Successive Cancellation Decoding of Polar Codes , 2018, 2018 IEEE 19th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC).

[6]  Alexios Balatsoukas-Stimming,et al.  A low-complexity improved successive cancellation decoder for polar codes , 2014, 2014 48th Asilomar Conference on Signals, Systems and Computers.

[7]  Guanghui Wen,et al.  DLSTM: Distributed Long Short-Term Memory Neural Networks for the Internet of Things , 2022, IEEE Transactions on Network Science and Engineering.

[8]  David Declercq,et al.  Dynamic-SCFlip Decoding of Polar Codes , 2017, IEEE Transactions on Communications.

[9]  Erdal Arikan,et al.  Channel Polarization: A Method for Constructing Capacity-Achieving Codes for Symmetric Binary-Input Memoryless Channels , 2008, IEEE Transactions on Information Theory.

[10]  Alexander Vardy,et al.  How to Construct Polar Codes , 2011, IEEE Transactions on Information Theory.

[11]  Kai Chen,et al.  CRC-Aided Decoding of Polar Codes , 2012, IEEE Communications Letters.

[12]  David Declercq,et al.  An Improved SCFlip Decoder for Polar Codes , 2016, 2016 IEEE Global Communications Conference (GLOBECOM).

[13]  Furkan Ercan,et al.  Neural Dynamic Successive Cancellation Flip Decoding of Polar Codes , 2019, 2019 IEEE International Workshop on Signal Processing Systems (SiPS).

[14]  Feng Liu,et al.  Convolutional Neural Network-Based Polar Decoding , 2019, 2019 2nd World Symposium on Communication Engineering (WSCE).

[15]  Jürgen Schmidhuber,et al.  Long Short-Term Memory , 1997, Neural Computation.

[16]  Shaohua Wu,et al.  A Machine Learning Based Multi-flips Successive Cancellation Decoding Scheme of Polar Codes , 2020, 2020 IEEE 91st Vehicular Technology Conference (VTC2020-Spring).

[17]  Erdal Arikan,et al.  Channel polarization: A method for constructing capacity-achieving codes , 2008, 2008 IEEE International Symposium on Information Theory.

[18]  Lin Gui,et al.  A Novel Decoding Scheme for Polar Code Using Convolutional Neural Network , 2019, 2019 IEEE International Symposium on Broadband Multimedia Systems and Broadcasting (BMSB).

[19]  Liang Zhang,et al.  Progressive Bit-Flipping Decoding of Polar Codes over Layered Critical Sets , 2017, GLOBECOM 2017 - 2017 IEEE Global Communications Conference.

[20]  Jimmy Ba,et al.  Adam: A Method for Stochastic Optimization , 2014, ICLR.

[21]  Swapnil Bhole,et al.  ATRNN: Using Seq2Seq Approach for Decoding Polar Codes , 2020, 2020 International Conference on COMmunication Systems & NETworkS (COMSNETS).

[22]  Martin Reisslein,et al.  Hardware-Accelerated Platforms and Infrastructures for Network Functions: A Survey of Enabling Technologies and Research Studies , 2020, IEEE Access.