Improved Deep Learning in OFDM Systems With Imperfect Timing Synchronization.

VTC Spring（2020）

引用 4|浏览2

暂无评分

摘要

The paper proposes a deep neural network (DNN) based receiver to outperform the state-of-the-art w/o timing synchronization error in orthogonal frequency-division multiplexing (OFDM) systems. Moreover, the closed-form of a traditional minimum mean square error (MMSE) receiver is derived in the presence of inter-symbol-interference. The derived receiver is used to benchmark the performance of the proposed DNN.

查看译文

关键词

inter-symbol-interference,DNN,OFDM systems,imperfect timing synchronization,deep neural network based receiver,orthogonal frequency-division multiplexing systems,traditional minimum mean square error receiver

AI 理解论文

溯源树

样例

生成溯源树，研究论文发展脉络

Chat Paper

正在生成论文摘要