1 |
H. Roh, S. Oh, H. Song, J. Han and S. Lim, "Deep learning-based wireless signal classification in the iot environment," Computers, Materials & Continua, vol. 71, no.3, pp. 5717-5732, 2022.
DOI
|
2 |
Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio, "Generative adversarial networks.", Commun. ACM 63, 11 (November 2020)
|
3 |
Alzubaidi, L., Zhang, J., Humaidi, A.J. et al, "Review of deep learning: concepts, CNN architectures, challenges, applications, future directions.", J Big Data 8, 53 (2021).
|
4 |
X.Wu, P.C.Y. Chen and J. Liu, "LSTMnetwork:Adeep learning approach for short-termtraffic forecast,"Iet Intelligent Transport Systems, vol. 11, no. 2, pp. 68-75, 2017.
DOI
|
5 |
W. Kong, Z. Y. Dong, Y. Jia, D. J. Hill, Y. Xu et al., "Short-term residential load forecasting based on LSTM recurrent neural network," IEEE Transactions on Smart Grid, vol. 10, no. 1, pp. 841-851, 2019.
DOI
|
6 |
C. Weber, M. Peter and T. Felhauer, "Automatic modulation classification technique for radio monitoring,", Electronics Letters, vol. 51, no. 10, pp. 794-796, 2015.
DOI
|
7 |
S. Zhou, Z. Yin, Z. Wu, Y. Chen, N. Zhao et al., "A robust modulation classification method using convolutional neural networks," EURASIP Journal on Advances in Signal Processing, vol. 2019, no. 1, pp. 55, 2019.
|
8 |
X. Zhang, J. Sun and X. Zhang, "Automatic modulation classification based on novel feature extraction algorithms," IEEE Access, vol. 8, pp. 16362-16371, 2020.
DOI
|
9 |
D. Hong, Z. Zhang and X. Xu, "Automatic modulation classification using recurrent neural networks," in 2017 3rd IEEE Int. Conf. on Computer and Communications (ICCC), Chengdu, China, pp. 695-700, 2017.
|
10 |
RadioML2016.10a Dataset, https://www.deepsig.ai/datasets
|
11 |
S. H. Shah and I. Yaqoob, "A survey: Internet of Things (IOT) technologies, applications and challenges," 2016 IEEE Smart Energy Grid Engineering (SEGE), 2016, pp. 381-385
|
12 |
S. Rajendran, W. Meert, D. Giustiniano, V. Lenders and S. Pollin, "Deep Learning Models for Wireless Signal Classification With Distributed Low-Cost Spectrum Sensors," in IEEE Transactions on Cognitive Communications and Networking, vol. 4, no. 3, pp. 433-445, Sept. 2018
DOI
|
13 |
S. Lim, S. Lee, J. Yoo and C. Kim, "NBP: light-weight Narrow Band Protection for ZigBee and WiFi coexistence", EURASIP Journal on Wireless Communications and Networking 2013, 76 (2013)
|
14 |
Xiaolong Zheng, Zhichao Cao, Jiliang Wang, Yuan He, and Yunhao Liu, "ZiSense: towards interference resilient duty cycling in wireless sensor networks", In Proceedings of the 12th ACM Conference on Embedded Network Sensor Systems (SenSys '14). Association for Computing Machinery, New York, NY, USA, 119-133.
|
15 |
Shravan Rayanchu, Ashish Patro, and Suman Banerjee, "Catching whales and minnows using WiFiNet: deconstructing non-WiFi interference using WiFi hardware.", In Proceedings of the 9th USENIX conference on Networked Systems Design and Implementation (NSDI'12). USENIX Association, USA, 5.
|
16 |
S. Tridgell, D. Boland, P. H. W. Leong and P. H. W. Siddhartha, "Real-time automatic modulation classification," in Int. Conf. on Field-Programmable Technology, ICFPT 2019, Tianjin, China, pp. 299-302, 2019.
|