no code implementations • journal 2021 • Meng Xia, Shichuan Chen, AND XIAONIU YANG
Owing to advances in the overall performance and anti-interception capability of radars, the designs of radar waveforms with good correlation properties have been a concern for researchers.
no code implementations • 23 Nov 2020 • Shilian Zheng, Xiaoyu Zhou, Shichuan Chen, Peihan Qi, Xiaoniu Yang
The simulation results show that under the AWGN channel, the performance of both hard demodulation and soft demodulation of DemodNet is very close to the traditional methods.
no code implementations • 28 Oct 2020 • Zhuangzhi Chen, Hui Cui, Jingyang Xiang, Kunfeng Qiu, Liang Huang, Shilian Zheng, Shichuan Chen, Qi Xuan, Xiaoniu Yang
More interestingly, our proposed models behave extremely well in small-sample learning when only a small training dataset is provided.
no code implementations • 31 Mar 2020 • Shilian Zheng, Shichuan Chen, Xiaoniu Yang
In this paper, we propose a new receiver model, namely DeepReceiver, that uses a deep neural network to replace the traditional receiver's entire information recovery process.
no code implementations • 13 Sep 2019 • Shilian Zheng, Shichuan Chen, Peihan Qi, Huaji Zhou, Xiaoniu Yang
We present spectrum sensing as a classification problem and propose a sensing method based on deep learning classification.
no code implementations • 20 Apr 2019 • Shichuan Chen, Shilian Zheng, Lifeng Yang, Xiaoniu Yang
In order to verify the performance of the deep learning-based radio signal classification on real-world radio signal data, in this paper we conduct experiments on large-scale real-world ACARS and ADS-B signal data with sample sizes of 900, 000 and 13, 000, 000, respectively, and with categories of 3, 143 and 5, 157 respectively.