A Low-Complexity Recurrent Neural Network Based Joint Equalization and Decoding Method for Trellis Coded Modulation Link in Data Center
2020 OPTO-ELECTRONICS AND COMMUNICATIONS CONFERENCE (OECC 2020)(2020)
摘要
RNN-based joint equalization and decoding methods are proposed for data center with TCM signals. Numerical results show compared with traditional DSP algorithms, our method improves power sensitivity by 2.2dB@BER=3.8×10
-3
with 96% reduced complexity.
更多查看译文
关键词
trellis coded modulation (TCM), recurrent neural network (RNN), data center
AI 理解论文
溯源树
样例
![](https://originalfileserver.aminer.cn/sys/aminer/pubs/mrt_preview.jpeg)
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要