Sreeraj Rajendran
Sreeraj Rajendran
Post-Doctoral Researcher, KU Leuven
Verified email at esat.kuleuven.be - Homepage
Title
Cited by
Cited by
Year
Deep learning models for wireless signal classification with distributed low-cost spectrum sensors
S Rajendran, W Meert, D Giustiniano, V Lenders, S Pollin
IEEE Transactions on Cognitive Communications and Networking 4 (3), 433-445, 2018
1112018
Electrosense: Open and big spectrum data
S Rajendran, R Calvo-Palomino, M Fuchs, B Van den Bergh, H Cordobés, ...
IEEE Communications Magazine 56 (1), 210-217, 2017
362017
Key technologies and system trade-offs for detection and localization of amateur drones
MM Azari, H Sallouha, A Chiumento, S Rajendran, E Vinogradov, S Pollin
IEEE Communications Magazine 56 (1), 51-57, 2018
352018
SAIFE: Unsupervised wireless spectrum anomaly detection with interpretable features
S Rajendran, W Meert, V Lenders, S Pollin
2018 IEEE International Symposium on Dynamic Spectrum Access Networks …, 2018
132018
IEEE 5G spectrum sharing challenge: A practical evaluation of learning and feedback
S Rajendran, B Van den Bergh, T Vermeulen, S Pollin
IEEE Communications Magazine 54 (11), 210-216, 2016
112016
DySPAN spectrum challenge: situational awareness and opportunistic spectrum access benchmarked
F Wunsch, F Paisana, S Rajendran, A Selim, P Alvarez, S Müller, ...
IEEE Transactions on Cognitive Communications and Networking 3 (3), 550-562, 2017
82017
Saving energy in WSNs for acoustic surveillance applications while maintaining QoS
B Thoen, G Ottoy, F Rosas, S Lauwereins, S Rajendran, L De Strycker, ...
2017 IEEE Sensors Applications Symposium (SAS), 1-6, 2017
72017
Electrosense: Crowdsourcing spectrum monitoring
B Van den Bergh, D Giustiniano, H Cordobés, M Fuchs, ...
2017 IEEE International Symposium on Dynamic Spectrum Access Networks …, 2017
52017
Unsupervised Wireless Spectrum Anomaly Detection With Interpretable Features
S Rajendran, W Meert, V Lenders, S Pollin
IEEE Transactions on Cognitive Communications and Networking 5 (3), 637-647, 2019
32019
Electrosense+: Empowering People to Decode the Radio Spectrum
R Calvo-Palomino, H Cordobés, M Engel, M Fuchs, P Jain, M Liechti, ...
arXiv preprint arXiv:1811.12265, 2018
22018
Crowdsourced wireless spectrum anomaly detection
S Rajendran, V Lenders, W Meert, S Pollin
IEEE Transactions on Cognitive Communications and Networking, 2019
12019
Localization in Ultra Narrow Band IoT Networks: Design Guidelines and Tradeoffs
H Sallouha, A Chiumento, S Rajendran, S Pollin
IEEE Internet of Things Journal 6 (6), 9375-9385, 2019
12019
Large-scale Wireless Spectrum Monitoring: Challenges and Solutions based on Machine Learning
S Rajendran, S Pollin
Spectrum Sharing: The Next Frontier in Wireless Networks, 2020
2020
Automatic Modulation Classification Using Parallel Fusion of Convolutional Neural Networks
E Perenda, S Rajendran, S Pollin
IEEE WIRELESS COMMUNICATIONS, 2019
2019
Deep Learning Solutions for Large Scale Wireless Spectrum Monitoring
S Rajendran
KU Leuven, 2019
2019
A multi-layered energy consumption model for smart wireless acoustic sensor networks
G Dekkers, F Rosas, S Lauwereins, S Rajendran, S Pollin, B Vanrumste, ...
arXiv preprint arXiv:1812.06672, 2018
2018
Electrosense-spectrum sensing with increased frequency range
F Minucci, B Van den Bergh, S Rajendran, D Giustiniano, ...
2018
Using Cheap RTL-SDRs for Measuring Electrosmog
B Reynders, R Iyare, S Rajendran, V Volskiy, GAE Vandenbosch, S Pollin
2018 IEEE Symposium on Communications and Vehicular Technology (SCVT)(SCVT'18), 2018
2018
Key Technologies and System Trade-Offs for Detection and Localization of Amateur Drones
M Mahdi Azari, H Sallouha, A Chiumento, S Rajendran, E Vinogradov, ...
arXiv preprint arXiv:1710.08478, 2017
2017
Adaptive Channel Selection and Sensing based on Reinforcement Learning
S Rajendran, S Pollin
WIC/IEEE SP Symposium on Information Theory and Signal Processing, Date …, 2015
2015
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Articles 1–20