EARS: Collaborative Research: Intelligence Measure of Cognitive Radio Networks

Project Duration: 1/2015-12/2018. NSF Collaborative Project Numbers: CNS-1443885 (Binghamton University), CNS-1464487 (George Mason University)

Project Objectives:

Multi-year heavy investment in spectrum sharing research has generated a large amount of spectrum measurement data and many spectrum sharing techniques. Most of the techniques are based on cognitive radio networks (CRNs) because cognitive capabilities are necessary for optimizing spectrum efficiency and guaranteeing safe coexistence in the presence of the spectrum uncertainty. Such cognitive capabilities collectively define the intelligence of CRNs. Although cognition and intelligence are vital for CRNs, their quantitative study is largely an open area.

This project proposes a multi-disciplinary framework to quantitatively study the cognitive capabilities and the intelligence of CRNs. It develops both a theoretical approach and an empirical approach to construct a CRN intelligence model from the Cattell-Horn-Carroll human intelligence model. It develops a CRN testing battery to measure the intelligence as a CRN IQ (intelligence quotient) based on psychometrics. The intelligence model and the CRN IQ are then used to develop new IQ-based routing algorithms and to enhance CRN's immunity to Denial-of-Service attacks. This project adopts a big data approach to exploit existing spectrum measurement data and CRN research results.

Project Participants:

  1. Prof. Xiaohua(Edward) Li, PI, Dept. of ECE, Binghamton University
  2. Prof. Yu Chen, co-PI, Dept. of ECE, Binghamton University
  3. Prof. Kai Zeng, PI, Dept. of ECE, George Mason University
  4. Prof. Kenneth J. Kurtz, collaborator, Dept. of Psychology, Binghamton University
  5. Graduate and undergraduate students:

Project Activities:

Publications:

  1. Monireh Dabaghchian, Amir Alipour-Fanid, Kai Zeng, Qingsi Wang, and Peter Auer , “Online Learning with Randomized Feedback Graphs for Optimal PUE Attacks in Cognitive Radio Networks”,  IEEE/ACM Transactions on Networking, Vol. 26, No. 5, pp. 2268-2281, Oct. 2018.
  2. Wenbo Xu, Jing Xu, Jiachen Li, Wei Liu, Shimin Gong, and Kai Zeng, “Robust Spectrum Monitoring in Cognitive Radio Networks With Uncertain Traffic Information,” IEEE Access, Vol. 6, pp. 34696 – 34706, Jun. 2018.
  3. Liang Zhao, Amir Alipour-Fanid, Martin Slawski, and Kai Zeng, "Prediction-time Efficient Classification Using Feature Computational Dependencies", 24th SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2018), London, UK, August 19 - 23, 2018.
  4. J. Zheng, Y. Wang, X. Zhang, and X. Li, "'Classification of severely occluded image sequences via convolutional recurrent neural networks," EEE GlobalSIP'2018 (2018 6th IEEE Global Conference on Signal and Information Processing), Anaheim, CA, USA, Nov. 26-29, 2018.
  5. Y. Chen, Q. Dong, X. Li, and K. Zeng, "'Position paper: A theoretical framework for general cognition evaluation of cognitive radios," 4th IEEE International Smart Cities Conference (ISC2), Sept. 16-19, 2018.
  6. Q. Dong, Y. Chen, X. Li, and K. Zeng, "'Explore recurrent neural network for PUE attack detection in practical CRN models," 4th IEEE International Smart Cities Conference (ISC2), Sept. 16-19, 2018
  7. J. Zheng, T.-Y. Lee, C. Feng, X. Li, and Z. Zhang, "Robust attentional pooling via feature selection," the 24th International Conference on Pattern Recognition (ICPR), Beijing, China, Aug. 20-24, 2018.
  8. Q. Dong, Y. Chen, X. Li, and K. Zeng, "An adaptive primary user emulation attack detection mechanism for cognitive radio networks," 2018 14th EAI International Conference on Security and Privacy in Communication Networks (SecureComm), Singapore, Aug. 8-10, 2018.
  9. M. Zhang, X. Li, and J. Peng, "Using joint generalized eigenvectors of a set of covariance matrix pencils for deflationary blind source extraction," IEEE Transactions on Signal Processing, vol. 66, no. 11, pp. 2892-2904, June 1, 2018. (source code)
  10. M. Ghorbaniparvar, N. Zhou, X. Li, D. Trudnowski, and R. Xie, "A forecasting-residual spectrum analysis method for distinguishing forced and natural oscillations," IEEE Transactions on Smart Grid, vol. 10, no. 1, pp. 493-502, Jan. 2019.
  11. X. Li, Y. Zhang, and W. Cadeau, "Hybrid massive MIMO for secure transmissions against stealthy eavesdroppers," IEEE Communications Letters, vol. 22, no. 1, pp. 81-84, Jan. 2018.
  12. Q. Dong, Z. Yang, Y. Chen, X. Li, and K. Zeng, "Exploration of singular spectrum analysis for online anomaly detection in CRNs," EAI Endorsed Transactions on Security and Safety, vol. 4, no. 12, pp. 1-13, Dec. 2017.
  13. Q. Dong, Z. Yang, Y. Chen, X. Li, and K. Zeng, "Anomaly detection in cognitive radio networks exploiting singular spectrum analysis," the 7th edition of International Conference on Mathematical Methods, Models and Architectures for Computer Networks (MMM-ACNS 2017), Warsaw, PL, Aug. 28-30, 2017. (Best Paper Awar)

  14.  M. Dabaghchian, S. Liu, A. Alipour-Fanid, K. Zeng, X. Li, Y. Chen, “Who is Smarter? Intelligence Measure of Learning-based Cognitive Radios,” submitted to IEEE Transactions on Cognitive Communications and Networking.

  15. Q. Dong, Y. Chen, X. Li, and K. Zeng, “An Adaptive PUE Attacker Detection Mechanism for CRNs Leveraging Unclonable PU Transmission Features,” submitted to the IEEE Conference on Communications and Network Security (CNS), Beijing, China, May 30-June 1, 2018.

  16. Y. Pan, Y. Hou, M. Li, R. Gerdes, K. Zeng, M. Towfiq, and B. Cetiner, "Message Integrity Protection over Wireless Channel: Countering Signal Cancellation via Channel Randomization", to appear in IEEE Transactions on Dependable and Secure Computing, 2017.
  17. R. Jin, Xianru Du, K. Zeng, L. Huang, L. Xiao, and J. Xu, "Delay Analysis of Physical Layer Key Generation in Dynamic Roadside-to-Vehicle Networks", IEEE Transactions on Vehicular Technology, vol. 66, no. 3, pp. 2526-2535, March 2017
  18. Eric Wang, William Xu, Suhas Sastry, Songsong Liu, and Kai Zeng, "Hardware module-based message authentication in intra-vehicle networks", The ACM/IEEE 8th International Conference on Cyber-Physical Systems (ICCPS’17), Pittsburgh, Pennsylvania, April 18 - 20, 2017. PDF
  19. Yantian Hou, Ming Li, and Kai Zeng, "Throughput optimization in multi-hop wireless networks with reconfigurable antennas", International Conference on Computing, Networking and Communications (ICNC'17), Silicon Valley, USA, Jan. 26 - 29, 2017. PDF
  20. Amir Alipour-Fanid, Monireh Dabaghchian, Hengrun Zhang, and Kai Zeng, "String stability analysis of cooperative adaptive cruise control under jamming attacks", IEEE 18th International Symposium on High Assurance Systems Engineering (HASE), Singapore, Jan. 12 - 14, 2017. PDF
  21. J. Zheng, C. Xu, Z. Zhang, and X. Li, "Electric load forecasting in smart grid using long-short-term-memory based recursive neural networks," The 51th Annual Conference on Information Sciences and Systems (CISS'2017), Johns Hopkins University, Mar. 22-24, 2017.
  22. X. Li, J. Zheng, and M. Zhang, "Compressive sensing based spectrum sharing and coexistence for machine-to-machine communications," Proceesings of the 42nd IEEE Internatonal Conference on Acoustics, Speech and Signal Processing (ICASSP'2017), New Orleans, Mar. 5-9, 2017.
  23. J. Zheng, W. Yang, and X. Li, "Training data reduction in deep neural networks with partial mutual information based feature selection and correlation matching based active learning," Proceesings of the 42nd IEEE Internatonal Conference on Acoustics, Speech and Signal Processing (ICASSP'2017), New Orleans, Mar. 5-9, 2017.
  24. X. Li, Y. Zhang, and W. Cadeau, "Hybrid massive MIMO for secure transmissions against stealthy eavesdroppers," IEEE Communications Letters, 2017
  25. M. Ghorbaniparvar, N. Zhou, X. Li, D. Trudnowski, and R. Xie, "A forecasting-residual spectrum analysis method for distinguishing forced and natural oscillations," IEEE Transactions on Smart Grid, 2017
  26. X. Li and J. Zheng, "Active learning for regression with correlation matching and labeling error suppression," IEEE Signal Processing Letters, vol. 23, no. 8, pp. 1081-1085, Aug. 2016.
  27. X. Li, J. Zheng, and M. Zhang, "Compressive sensing based spectrum sharing and coexistence for machine-to-machine communications," to appear in ICASSP'2017 (42nd IEEE International Conference on Acoustics, Speech and Signal Processing), New Orleans, Mar. 5-9, 2017.
  28. J. Zheng, W. Yang, and X. Li, "Training data reduction in deep neural networks with partial mutual information based feature selection and correlation matching based active learning," to appear in ICASSP'2017 (42nd IEEE International Conference on Acoustics, Speech and Signal Processing), New Orleans, Mar. 5-9, 2017.
  29. J. Zheng and X. Li, "Active regression with compressive-sensing based outlier mitigation for both small and large outliers," IEEE GlobalSIP'2016 (2016 IEEE Global Conference on Signal and Information Processing), Washington, D.C., Dec. 7-9, 2016.
  30. M. Zhang and X. Li, "Deflationary blind source extraction using an exact solution subspace searching scheme," IEEE GlobalSIP'2016, Washington, D.C., Dec. 7-9, 2016.
  31. M. Ghorbaniparvar, N. Zhou, and X. Li, "Coherence function estimation with a derivative constraint for power grid oscillation detection," IEEE GlobalSIP'2016, Washington, D.C., Dec. 7-9, 2016.
  32. M. Dabaghchian, S. Liu, A. Alipour-Fanid, K. Zeng, X. Li, and Y. Chen, "Intelligence measure of cognitive radios with learning capabilities," IEEE GLOBECOM'2016, Washington, D.C., Dec. 4-8, 2016.
  33. X. Li, M. Ghorbaniparvar, and N. Zhou, "Population dynamic human behavioral models for smart grid demand side management," Proceedings of the 48th North American Power Symposium (NAPS), Denver, CO, Sept. 18-20, 2016.
  34. X. Li, Y. Chen, and K. Zeng, "Integration of machine learning and human learning for training optimization in robust linear regression," Proceedings of the IEEE International Conference on Acoustic, Speech and Signal Processing (ICASSP'2016), Shanghai, China, Mar. 21-25, 2016.
  35. X. Li and J. Zheng, "Joint machine learning and human learning design with sequential active learning and outlier detection for linear regression problems," The 50th Annual Conference on Information Sciences and Systems (CISS'2016), Princeton University, Mar. 16-18, 2016.
  36. R. Wu, B. Liu, Y. Chen, E. Blasch, H. Ling, and G. Chen, "A container-based elastic cloud architecture for pseudo real-time exploitation of wide area motion imagery (WAMI) stream," Special Issue: Dynamic Data Driven Application Systems (DDDAS) Concepts in Signal Processing, Journal of Signal Processing Systems, in review, 2016.
  37. J. Xua, Q. Wang, K. Zeng, M. Liu, and W. Liu, "Sniffer channel assignment with imperfect monitoring for cognitive radio networks," IEEE Trans. Wireless Communications, 2016.
  38. Z. Yang, N. Zhou, A. Polunchenko, and Y Chen, "Singular spectrum analysis based quick online detection of disturbance start time in power grid,"  IEEE GlobalCom'2015, Dec. 2015
  39. Q. Dong, Z. Yang, Y. Chen, A. Polunchenko, X. Li, and K. Zeng, “Primary User Emulation Attacks Detection for CRNs using Singular Spectrum Analysis,” submitted to IEEE WCNC, March 2017.
  40. Q. Dong, Y. Chen, X. Li, and K. Zeng, “A Survey on Simulators for Cognitive Radio Networks,” submitted to IEEE Communications Surveys and Tutorial, under review.