Neural Successive Cancellation Polar Decoder With Tanh-Based Modified LLR Over FSO Turbulence Channel
The neural successive cancellation (NSC) decoder with tanh-based modified log-likelihood ratio (LLR) is proposed for reducing the decoding latency of polar codes over free space optical (FSO) turbulence channel. The conventional successive cancellation (SC) decoder is partitioned into multiple sub-b...
Saved in:
| Main Authors: | , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2020-01-01
|
| Series: | IEEE Photonics Journal |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/9222501/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849417448763162624 |
|---|---|
| author | Jiafei Fang Meihua Bi Shilin Xiao Hang Yang Zhiyu Chen Zhiyang Liu Weisheng Hu |
| author_facet | Jiafei Fang Meihua Bi Shilin Xiao Hang Yang Zhiyu Chen Zhiyang Liu Weisheng Hu |
| author_sort | Jiafei Fang |
| collection | DOAJ |
| description | The neural successive cancellation (NSC) decoder with tanh-based modified log-likelihood ratio (LLR) is proposed for reducing the decoding latency of polar codes over free space optical (FSO) turbulence channel. The conventional successive cancellation (SC) decoder is partitioned into multiple sub-blocks, which are replaced by multiple sub neural network (NN) decoders with tanh-based modified LLR. The recursive characteristic of the polar sequences reliability ranking given in 5G standard enables the sub-NN decoder to be uniquely determined by code length and the number of information bits. Confirmed by the simulation, the bit error rate (BER) performance of NSC decoder with tanh-based modified LLR is close to the conventional SC decoder over turbulence channel for the practical-length polar codes. Regarding turbulence-stability, the NSC decoder trained in moderate and strong turbulence conditions have stable performance in a wide range of turbulence conditions. Moreover, in comparison of decoding latency, the NSC decoder with tanh-based modified LLR takes less than 25% time steps of SC decoder in the same code length. |
| format | Article |
| id | doaj-art-de9f3deb6a5f4e23ae13c8aa289d4ba9 |
| institution | Kabale University |
| issn | 1943-0655 |
| language | English |
| publishDate | 2020-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Photonics Journal |
| spelling | doaj-art-de9f3deb6a5f4e23ae13c8aa289d4ba92025-08-20T03:32:50ZengIEEEIEEE Photonics Journal1943-06552020-01-0112611010.1109/JPHOT.2020.30306189222501Neural Successive Cancellation Polar Decoder With Tanh-Based Modified LLR Over FSO Turbulence ChannelJiafei Fang0https://orcid.org/0000-0003-3128-554XMeihua Bi1https://orcid.org/0000-0001-8177-1808Shilin Xiao2https://orcid.org/0000-0003-0887-782XHang Yang3Zhiyu Chen4Zhiyang Liu5Weisheng Hu6https://orcid.org/0000-0002-6168-2688The State Key Laboratory of Advanced Optical Communication System and Networks, Shanghai Jiao Tong University, Shanghai, ChinaThe State Key Laboratory of Advanced Optical Communication System and Networks, Shanghai Jiao Tong University, Shanghai, ChinaThe State Key Laboratory of Advanced Optical Communication System and Networks, Shanghai Jiao Tong University, Shanghai, ChinaThe State Key Laboratory of Advanced Optical Communication System and Networks, Shanghai Jiao Tong University, Shanghai, ChinaThe State Key Laboratory of Advanced Optical Communication System and Networks, Shanghai Jiao Tong University, Shanghai, ChinaThe State Key Laboratory of Advanced Optical Communication System and Networks, Shanghai Jiao Tong University, Shanghai, ChinaThe State Key Laboratory of Advanced Optical Communication System and Networks, Shanghai Jiao Tong University, Shanghai, ChinaThe neural successive cancellation (NSC) decoder with tanh-based modified log-likelihood ratio (LLR) is proposed for reducing the decoding latency of polar codes over free space optical (FSO) turbulence channel. The conventional successive cancellation (SC) decoder is partitioned into multiple sub-blocks, which are replaced by multiple sub neural network (NN) decoders with tanh-based modified LLR. The recursive characteristic of the polar sequences reliability ranking given in 5G standard enables the sub-NN decoder to be uniquely determined by code length and the number of information bits. Confirmed by the simulation, the bit error rate (BER) performance of NSC decoder with tanh-based modified LLR is close to the conventional SC decoder over turbulence channel for the practical-length polar codes. Regarding turbulence-stability, the NSC decoder trained in moderate and strong turbulence conditions have stable performance in a wide range of turbulence conditions. Moreover, in comparison of decoding latency, the NSC decoder with tanh-based modified LLR takes less than 25% time steps of SC decoder in the same code length.https://ieeexplore.ieee.org/document/9222501/FSOPolar CodesDeep Learning |
| spellingShingle | Jiafei Fang Meihua Bi Shilin Xiao Hang Yang Zhiyu Chen Zhiyang Liu Weisheng Hu Neural Successive Cancellation Polar Decoder With Tanh-Based Modified LLR Over FSO Turbulence Channel IEEE Photonics Journal FSO Polar Codes Deep Learning |
| title | Neural Successive Cancellation Polar Decoder With Tanh-Based Modified LLR Over FSO Turbulence Channel |
| title_full | Neural Successive Cancellation Polar Decoder With Tanh-Based Modified LLR Over FSO Turbulence Channel |
| title_fullStr | Neural Successive Cancellation Polar Decoder With Tanh-Based Modified LLR Over FSO Turbulence Channel |
| title_full_unstemmed | Neural Successive Cancellation Polar Decoder With Tanh-Based Modified LLR Over FSO Turbulence Channel |
| title_short | Neural Successive Cancellation Polar Decoder With Tanh-Based Modified LLR Over FSO Turbulence Channel |
| title_sort | neural successive cancellation polar decoder with tanh based modified llr over fso turbulence channel |
| topic | FSO Polar Codes Deep Learning |
| url | https://ieeexplore.ieee.org/document/9222501/ |
| work_keys_str_mv | AT jiafeifang neuralsuccessivecancellationpolardecoderwithtanhbasedmodifiedllroverfsoturbulencechannel AT meihuabi neuralsuccessivecancellationpolardecoderwithtanhbasedmodifiedllroverfsoturbulencechannel AT shilinxiao neuralsuccessivecancellationpolardecoderwithtanhbasedmodifiedllroverfsoturbulencechannel AT hangyang neuralsuccessivecancellationpolardecoderwithtanhbasedmodifiedllroverfsoturbulencechannel AT zhiyuchen neuralsuccessivecancellationpolardecoderwithtanhbasedmodifiedllroverfsoturbulencechannel AT zhiyangliu neuralsuccessivecancellationpolardecoderwithtanhbasedmodifiedllroverfsoturbulencechannel AT weishenghu neuralsuccessivecancellationpolardecoderwithtanhbasedmodifiedllroverfsoturbulencechannel |