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  • 袁治中,王旭东,吴 楠.高可靠性信道反馈自编码器系统设计[J].电讯技术,2022,(1): - .    [点击复制]
  • YUAN Zhizhong,WANG Xudong,WU Nan.Design of a high reliability autoencoder system with feedback channel[J].,2022,(1): - .   [点击复制]
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高可靠性信道反馈自编码器系统设计
袁治中,王旭东,吴楠
0
(大连海事大学 信息科学技术学院,辽宁 大连 116026)
摘要:
为了充分利用信道反馈编码系统中反馈信息,提出了一种针对带有反馈信道的高可靠性自编码器系统设计方案。该方案通过在发送端引入反馈解码器模块,将编码与反馈信息的提取分成两部分进行,利用端到端的学习方式使发送端和接收端寻找到适合信道的编码和解码算法。针对反馈解码器模块,给出了基于卷积神经网络和双向门控循环单元的两种实现方案。此外,提出了一种节约反馈发送功率的部分反馈方案,通过抽样间隔灵活控制反馈发送功率,同时利用反馈解码器对反馈信息进行恢复和提取。仿真实验表明,在不同码速和不同反馈信道信噪比的情况下,提出的两种信道反馈编码方案的系统误码性能均优于已有文献给出的方案,并且在反馈信道环境较差时,提出的部分反馈方案在节省反馈发送功率的同时仍有0.1 dB的误码性能提升。
关键词:  信道反馈编码  自编码器  反馈解码器  部分反馈  卷积神经网络
DOI:
基金项目:国家自然科学基金资助项目(61371091)
Design of a high reliability autoencoder system with feedback channel
YUAN Zhizhong,WANG Xudong,WU Nan
(College of Information Science and Technology,Dalian Maritime University,Dalian 116026,China)
Abstract:
In order to fully use feedback information in the channel feedback coding system,a design scheme for a highly reliable autoencoder system with feedback channel is proposed.The scheme introduces a feedback decoder module in the transmitter,divides coding and feedback information extraction into two parts,and finds the appropriate channel encoding and decoding algorithms through end-to-end training.Two kinds of feedback decoder based on convolutional neural network(CNN) and bi-directional gated recurrent unit(Bi-GRU) are presented.In addition,a partial feedback scheme is proposed to save the power of feedback transmission.The power of feedback transmission is controlled flexibly by sampling interval,and the feedback information is recovered and extracted by the feedback decoder.Simulation experiments show that under the conditions of different code rates and different feedback channel signal-to-noise ratios,the system error performance of the two proposed channel feedback coding schemes is better than that of the existing literature.And when the feedback channel environment is poor,the partial feedback schemes can save feedback transmission power while still improving the error performance of 0.1 dB.
Key words:  channel feedback coding  autoencoder  feedback decoder  partial feedback  convolutional neural network
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