Journals

1. K. Davaslioglu, S. Boztas, M. C. Ertem, Y. E. Sagduyu, and E. Ayanoglu, “Self-Supervised RF Signal Representation Learning for NextG Signal Classification with Deep Learning,” IEEE Wireless Communications Letters, vol. 12, no. 1, pp. 65-69, Jan. 2023.  

2. B. Kim, Y. E. Sagduyu, K. Davaslioglu, T. Erpek, and S. Ulukus, “Adversarial Machine Learning for NextG Covert Communications Using Multiple Antennas,” Entropy 24, no. 8, 1047, pp. 1-15, July 2022. 

3. E. Ayanoglu, K. Davaslioglu, Y. E. Sagduyu, “Machine Learning in NextG Networks via Generative Adversarial Networks,” in IEEE Transactions on Cognitive Communications and Networking, vol. 8, no. 2, pp. 480-501, June 2022.

4. B. Kim, Y. E. Sagduyu, K. Davaslioglu, T. Erpek, and S. Ulukus, "Channel-Aware Adversarial Attacks Against Deep Learning-Based Wireless Signal Classifiers," IEEE Transactions on Wireless Communications, vol. 21, no. 6, pp. 3868-3880, June 2022.

5. Y. Shi, K. Davaslioglu, and Y. E. Sagduyu, “Generative Adversarial Network in the Air: Deep Adversarial Learning for Wireless Signal Spoofing,” in IEEE Transactions on Cognitive Communications and Networking, vol. 7, no. 1, pp. 294-303, March 2021.

6. K. Davaslioglu, S. Soltani, T. Erpek, and Y. E. Sagduyu, “DeepWiFi: Cognitive WiFi with Deep Learning,” in IEEE Transactions on Mobile Computing, vol. 20, no. 2, Feb. 2021.

7. R. Theagarajan, B. Bhanu, T. Erpek, Y.-K. Hue, R. Schwieterman, K. Davaslioglu, Y. Shi, and Y. E. Sagduyu, “Integrating deep learning-based data driven and model-based approaches for inverse synthetic aperture radar target recognition,” in Optical Engineering Journal, Apr. 2020.

8. K. Davaslioglu, B. Pokorny, Y. E. Sagduyu, H. Molintas, S. Soltani, R. Grossman, and C. Bowers, “Collective Allostatic Load Measures for Teams,” in Structural Health Monitoring, Nov. 2019. https://doi.org/10.1177/1475921719884864.

9. C. C. Coskun, K. Davaslioglu, E. Ayanoglu, “Three-Stage Resource Allocation Algorithm for Energy-Efficient Heterogeneous Networks,” in IEEE Transactions on Vehicular Technology, vol. 66, no. 8, pp. 6942 – 6957, 2017.

10. K. Davaslioglu, C. C. Coskun, and E. Ayanoglu, “Energy-Efficient Resource Allocation for Fractional Frequency Reuse in Heterogeneous Networks,” in IEEE Transactions on Wireless Communications, vol. 14, no. 10, pp. 5484-5497, October 2015. [https://arxiv.org/abs/1410.1593]

11. K. Davaslioglu and E. Ayanoglu, “Quantifying Potential Energy Efficiency Gain in Green Cellular Wireless Networks,” in IEEE Communications Surveys and Tutorials, vol. 16., no. 4, pp. 2065-2091, Fourth Quarter, 2014.

12. K. Davaslioglu and E. Ayanoglu, “Efficiency and Fairness Trade-Offs in SC-FDMA Schedulers,” in IEEE Transactions on Wireless Communications, vol. 13, no. 6, pp. 2991-3002, June 2014.

13. K. Davaslioglu, E. Cagiral, M. Koca, “Free Space Optical Ultra-Wideband Communications over Atmospheric Turbulence Channels,” in Optics Express, Vol. 18, No. 16, pp. 16618-16627, August 2010.

Book Chapters

1. Y. Shi, Y. E. Sagduyu, K. Davaslioglu, and R. Levy, “Vulnerability Detection and Analysis in Adversarial Deep Learning,” in Guide to Vulnerability Analysis for Computer Networks and Systems - An Artificial Intelligence Approach. Computer Communications and Networks. Springer, Cham. , Nov. 2018.  Available online at: https://link.springer.com/chapter/10.1007/978-3-319-92624-7_9.

Conferences

1. Z. El Jamous, K. Davaslioglu, and Y. E. Sagduyu, “Deep Reinforcement Learning for Power Control in Next-Generation WiFi Network Systems,” IEEE Military Communications Conference (MILCOM), Nov.-Dec. 2022. 

2. K. Davaslioglu, T. Erpek, Y. E. Sagduyu, N. Abuzainab, and D. Hartman, “Deep Learning with Interference Training for Adaptive Radar Beamforming,” IEEE International Symposium on Phased Array Systems and Technology, Oct. 2022.

3. K. Davaslioglu, T. Erpek, and Y. E. Sagduyu, “Autoencoder Communications with Optimized Interference Suppression for NextG RAN,” IEEE Future Networks World Forum (FNWF), 2022.

4. B. Kim, Y. E. Sagduyu, T. Erpek, K. Davaslioglu, and S. Ulukus, “Channel Effects on Surrogate Models of Adversarial Attacks against Wireless Signal Classifies,” IEEE International Conference on Communications (ICC), 2021. Also available at arXiv preprint arXiv:2012.02160.

5. B. Kim, Y. E. Sagduyu, T. Erpek, K. Davaslioglu, S. Ulukus, “Adversarial Attacks with Multiple Antennas Against Deep Learning-Based Modulation Classifiers,” IEEE GLOBECOM Open Workshop on Machine Learning in Communications, 2020. Also available at arxiv preprint arXiv:2007.16204.

6. B. Kim, Y. E. Sagduyu, K. Davaslioglu, T. Erpek, and S. Ulukus, “How to Make 5G Communications "Invisible": Adversarial Machine Learning for Wireless  Privacy,” 54th Asilomar Conference on Signals, Systems and Computers, 2020. 

7. Y. Shi, K. Davaslioglu, and Y. E. Sagduyu, “Over-the-Air Membership Inference Attacks as Privacy Threats for Deep Learning-based Wireless Signal Classifiers,” ACM Conference on Security and Privacy in Wireless and Mobile Networks (WiSec) Workshop on Wireless Security and Machine Learning (WiseML), 2020.

8. B. Kim, Y. E. Sagduyu, K. Davaslioglu, T. Erpek, and S. Ulukus, “Over-the-Air Adversarial Attacks on Deep Learning Based Modulation Classifier over Wireless Channels,” Conference on Information Sciences and Systems (CISS), 2020. Also available at arXiv preprint arXiv:2002.022400.

9. K. Davaslioglu and Y. E. Sagduyu, “Trojan Attacks on Wireless Signal Classification with Adversarial Machine Learning,” IEEE Workshop on Data-Driven Dynamic Spectrum Sharing of IEEE International Symposium on Dynamic Spectrum Access Networks (DySPAN), Nov. 2019. [https://arxiv.org/abs/1910.10766]

10. Y. Shi, K. Davaslioglu, Y. E. Sagduyu, W. C. Headley, M. Fowler, and G. Green, “Deep Learning for Signal Classification in Unknown and Dynamic Spectrum Environments,” IEEE International Symposium on Dynamic Spectrum Access Networks (DySPAN), Nov. 2019. [https://arxiv.org/abs/1909.11800]

11. N. Abuzainab, T. Erpek, K. Davaslioglu, Y. E. Sagduyu, Y. Shi, S. Mackey, M. Patel, F. Panettieri, M. Qureshi, V. Isler, and A. Yener, “QoS and Jamming-Aware Wireless Networking Using Deep Reinforcement Learning,” IEEE Military Communications Conference (MILCOM), Nov. 2019. [https://arxiv.org/abs/1910.05766]

12. S. Soltani, R. Hasan, Y. E. Sagduyu, K. Davaslioglu, H. Deng, and T. Erpek, “Real-Time and Embedded Deep Learning on FPGA for RF Signal Classification,” IEEE Military Communications Conference (MILCOM), Nov. 2019. [https://arxiv.org/pdf/1910.05765.pdf]

13. Y. Shi, K. Davaslioglu, and Y. E. Sagduyu, “Generative Adversarial Network for Wireless Signal Spoofing,” ACM Conference on Security and Privacy in Wireless and Mobile Networks (WiSec) Workshop on Wireless Security and Machine Learning (WiseML), May 2019. [https://arxiv.org/pdf/1905.01008.pdf]

14. K. Davaslioglu, B. Pokorny, Y. E. Sagduyu, H. Molintas, S. Soltani, R. Grossman, and C. Bowers, “Measuring the Collective Allostatic Load,” IEEE Conference on Cognitive and Computational Aspects of Situation Management (CogSIMA), April 2019.

15. Y. Shi, Y. E. Sagduyu, K. Davaslioglu, and J. Li, “Active Deep Learning Attacks under Strict Rate Limitations for Online API Calls,” IEEE Symposium on Technologies for Homeland Security, Oct. 2018. (BEST PAPER AWARD) [https://arxiv.org/abs/1811.01811]

16. Y. Shi, Y. E. Sagduyu, K. Davaslioglu, and J. Li, “Generative Adversarial Networks for Black-Box API Attacks with Limited Training Data,” IEEE International Symposium on Signal Processing and Information Technology (ISSPIT), Dec. 2018. [https://arxiv.org/abs/1901.09113]

17. T. Erpek, Y. E. Sagduyu, Y. Shi, M. Costa, K. Davaslioglu, H. Han, D. Fayette, E. Bentley, and C. Banner, “Routing, Network Coding, and TCP Support for Wideband HF communications,” IEEE Military Communications Conference (MILCOM), Nov. 2018.

18. Y. Shi, Y. E Sagduyu, T. Erpek, K. Davaslioglu, Z. Lu, and J. Li, “Adversarial Deep Learning for Cognitive Radio Security: Jamming Attack and Defense Strategies,” IEEE International Conference on Communications (ICC), Kansas City, MO, May 2018.

19. K. Davaslioglu and Y. E. Sagduyu, “Generative Adversarial Learning for Spectrum Sensing,” IEEE International Conference on Communications (ICC), Kansas City, MO, May 2018.  [https://arxiv.org/abs/1804.00709]

20. N. Sulieman, E. Balevi, K. Davaslioglu, and R.D. Gitlin, “Diversity and Network Coded 5G Fronthaul Wireless Networks for Ultra-Low Latency Communication,” IEEE PIMRC 2017, Montreal, QC, Canada, October 2017.  

21. Asim Mazin, K. Davaslioglu, and R. D. Gitlin, “Secure Key Management for 5G Physical Layer Security,” IEEE WAMICON 2017, Cocoa Beach, FL, USA, April 2017.

22. D. Wickramasuriya, C. Perumalla, K. Davaslioglu, and R. D. Gitlin, “Base Station Prediction and Proactive Mobility Management in Virtual Cells using Recurrent Neural Networks,” IEEE WAMICON 2017, Cocoa Beach, FL, USA, April 2017.

23. N. Sulieman, K. Davaslioglu, and R.D. Gitlin, “Link Failure Recovery via Diversity Coding in 5G Fronthaul Wireless Networks,” IEEE WAMICON 2017, Cocoa Beach, FL, USA, April 2017.

24. N. Sulieman, K. Davaslioglu, and R.D. Gitlin, “Diversity Coded 5G Fronthaul Wireless Networks,” IEEE Wireless Telecommunications Symposium (WTS), Chicago, IL, April, 2017.

25. Y. Liu, K. Davaslioglu, and R.D. Gitlin, “Energy Efficiency Optimization of Channel Access Probabilities in IEEE 802.15.6 UWB WBANs,” IEEE Wireless Communications and Networking Conference (WCNC), San Francisco, CA, April 2017. [https://arxiv.org/abs/1610.02092 ]

26. Y. Liu, K. Davaslioglu, and R.D. Gitlin, “Energy Efficiency and Resource Allocation of IEEE 802.15. 6 IR-UWB WBANs: Current State-of-the-Art and Future Directions,” IEEE Information Theory and Applications Workshop, San Diego, CA, February 2017. 

27. K. Davaslioglu, Y. Liu, and R.D. Gitlin, “CLOEE – Cross-Layer Optimization for Energy Efficiency of IEEE 802.15.6 IR-UWB WBANs,” IEEE Globecom, Washington, D.C., December 2016. [https://arxiv.org/abs/1609.05256 ]

28. K. Davaslioglu and R. D. Gitlin, “5G Green Networking- Enabling Technologies, Potentials, and Challenges,” IEEE Wireless and Microwave Technology Conference (WAMICON), Clearwater, FL, April 2016.

29. K. Davaslioglu, C. C. Coskun, and E. Ayanoglu, “New Algorithms for Maximizing Cellular Wireless Network Energy Efficiency,” IEEE Information Theory and Applications Workshop, San Diego, CA, February 2016. 

30. K. Davaslioglu, C. C. Coskun, and E. Ayanoglu, “An Energy-Efficient Resource Allocation Algorithm with QoS Constraints for Heterogeneous Networks,” IEEE Globecom, San Deigo, CA, December 2015.

31. K. Davaslioglu and E. Ayanoglu, “Interference-based Cell Selection in Heterogeneous Networks,” Information Theory and Applications Workshop, San Diego, CA, February, 2013.  [arXiv:1302.7048]

32. K. Davaslioglu and E. Ayanoglu, “Common Rate Maximization in Two-Layer Networks,” IEEE Globecom, Anaheim, CA, November 2012, pp. 1096 – 1101. [arXiv:1302.7046].

33. K. Davaslioglu and E. Ayanoglu, “Power Control in Multi-Layer Cellular Networks,” March 2012. [arXiv:1203:6131]

34. K. Davaslioglu, E. Cagiral, M. Koca, “Free Space Optical Ultra-Wideband Communications over Atmospheric Turbulence Channels,” IEEE International Conference on Ultra-Wideband (ICUWB), vol. 1, pp. 1-4, September 2010.

Patents

1. Z. El-Jamous, Y. E. Sagduyu, K. Davaslioglu, “Systems and methods for deep reinforcement learning for optimal power control in wireless networks,” United States Patent 2024/0089863, March 14, 2024.

Preprints

2. K. Davaslioglu, T. Erpek, Yalin E. Sagduyu, “End-to-End Autoencoder Communications with Optimized Interference Suppression,” arXiv preprints, arXiv:2201.01388, 2021.

Demo Papers

1. S. Soltani, R. Hasan, Y. E. Sagduyu, K. Davaslioglu, H. Deng, and T. Erpek, “Real-Time Experimentation of Deep Learning-based RF Signal Classifier on FPGA,” IEEE International Symposium on Dynamic Spectrum Access Networks (DySPAN), 2019.

Dissertations 

1. K. Davaslioglu, Energy Efficiency and Load Balancing in Next-Generation Wireless Cellular Networks, Ph.D. Dissertation, Electr. and Comput. Eng. Dept., University of California, Irvine, 2015.

2. K. Davaslioglu, Impulse Radio Ultra-Wideband Communication over Free-Space Optical Links, M.S. thesis, Elect. Eng. Dept., Bogazici University, Istanbul, Turkey, 2010. [arXiv:1303.5683]