DeepDeMod: BPSK Demodulation Using Deep Learning Over Software-Defined Radio

DeepDeMod: BPSK Demodulation Using Deep Learning Over Software-Defined Radio

In wireless communication, signal demodulation under non-ideal conditions is one of the important research topic. In this paper, a novel non-coherent binary phase shift keying demodulator based on deep neural network, namely DeepDeMod, is proposed. The proposed scheme makes use of neural network to...

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Bibliographic Details
Main Authors: Arhum Ahmad, Satyam Agarwal, Sam Darshi, Sumit Chakravarty
Format: Article
Language:English
Published: IEEE 2022-01-01
Series:IEEE Access
Subjects:
Binary phase shift keying (BPSK)
deep neural network (DNN)
demodulation
software-defined radio (SDR)
transfer learning
universal software radio peripheral (USRP)
Online Access:https://ieeexplore.ieee.org/document/9936610/

Internet

https://ieeexplore.ieee.org/document/9936610/

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