Research


PAPERS
 
[1] Zhe Chen, C. Zhang, F. Lin, J. Yu, X. Li, Y. Song, R. Ranganathan, N. Guo, and R. C. Qiu, "Towards a large-scale cognitive radio network: Testbed, intensive computing, frequency agility, and security," (invited paper) to appear in Proceedings of IEEE International Conference on Computing, Networking and Communications (ICNC 2012), Maui, HI, January 2012. (PDF)

[2] Zhe Chen and R. C. Qiu, “Cooperative spectrum sensing using Q-learning with experimental validation,” in Proceedings of IEEE SoutheastCon, Nashville, TN, March 2011. (IEEE Xplore, PDF, PPT)

[3] Zhe Chen and R. C. Qiu, “Q-Learning Based Bidding Algorithm for Spectrum Auction in Cognitive Radio,” in Proceedings of IEEE SoutheastCon, Nashville, TN, March 2011. (IEEE Xplore, PDF, PPT)

[4] Zhe Chen, N. Guo, and R. C. Qiu, “Building a cognitive radio network testbed,” in Proceedings of IEEE SoutheastCon, Nashville, TN, March 2011. (IEEE Xplore, PDF, PPT)

[5] Zhe Chen, N. Guo, Z. Hu, and R. C. Qiu, “Channel state prediction in cognitive radio, part I: Response delays in practical hardware platforms,” in Proceedings of IEEE SoutheastCon, Nashville, TN, March 2011. (IEEE Xplore, PDF, PPT)

[6] Zhe Chen, N. Guo, Z. Hu, and R. C. Qiu, “Channel state prediction in cognitive radio, part II: Single-user prediction,” in Proceedings of IEEE SoutheastCon, Nashville, TN, March 2011. (IEEE Xplore, PDF, PPT)

[7] Zhe Chen, N. Guo, Z. Hu, and R. C. Qiu, "Experimental validation of channel state prediction considering delays in practical cognitive radio," IEEE Transactions on Vehicular Technology, vol. 60, no. 4, pp. 1314-1325, May, 2011. (IEEE Xplore, PDF)

[8] Zhe Chen, N. Guo, and R. C. Qiu, "Demonstration of real-time spectrum sensing for cognitive radio," (short paper), IEEE Communications Letters, vol. 14, no. 10, pp. 915-917, October, 2010. (IEEE Xplore, PDF)

[9] Zhe Chen, N. Guo, and R. C. Qiu, "Demonstration of real-time spectrum sensing for cognitive radio," (full paper), in Proceedings of IEEE Military Communications Conference (MILCOM 2010), San Jose, CA, November 2010. (IEEE Xplore, PDF, PPT)

[10] Zhe Chen and R. C. Qiu, "Prediction of channel state for cognitive radio using higher-order hidden Markov model," in Proceedings of IEEE SoutheastCon, Charlotte, NC, March 2010. (IEEE Xplore, PDF, PPT)
 
[11] Zhe Chen, Z. Hu, and R. C. Qiu, "Quickest spectrum detection using hidden Markov model for cognitive radio," in Proceedings of IEEE Military Communications Conference (MILCOM'09), Boston, MA, October 2009. (IEEE XplorePDF, PPT)

[12] Zhe Chen and R. C. Qiu, "Measurement denoising using kernel adaptive filters in the Smart Grid," submitted to IEEE Transactions on Smart Grid.

[13] R. C. Qiu, Zhe Chen, N. Guo, Y. Song, P. Zhang, H. Li and L. Lai, "Towards a real-time cognitive radio network testbed: Architecture, hardware platform, and application to smart grid," (invited paper) in Proceedings of Fifth IEEE Workshop on Networking Technologies for Software-Defined Radio and White Space, Boston, MA, June 2010. (IEEE Xplore, PDF)
 
[14] R. C. Qiu, Z. Hu, Zhe Chen, N. Guo, R. Ranganathan, S. Hou and G. Zheng, “Cognitive radio network for the Smart Grid: Experimental system architecture, control algorithms, security, and Microgrid testbed,” (invited paper) to appear in IEEE Transactions on Smart Grid, 2011. (TNTech)

[15] S. Hou, R. C. Qiu, Zhe Chen, and Z. Hu, "SVM and dimensionality reduction in cognitive radio with experimental validation," submitted to EURASIP Journal on Advances in Signal Processing.

[16] R. Ranganathan, R. C. Qiu, Z. Hu, S. Hou, M. P. Revilla, G. Zheng, Zhe Chen and N. Guo, "Cognitive radio for Smart Grid: Theory, algorithms, and security", (invited paper) International Journal of Digital Multimedia Broadcasting, vol. 2011, Article ID 502087, 14 pages, 2011. doi:10.1155/2011/502087. (Open Access)

[17] R. C. Qiu, N. Guo, H. Li, Z. Wu, V. Chakravarthy, Y. Song, Z. Hu, P. Zhang, Zhe Chen, "A unified multi-functional dynamic spectrum access framework: tutorial, theory and multi-GHz wideband testbed," Sensors, vol. 9, no. 8, pp. 6530-6603, August 2009. (Open Access)
 
[18] L. Fan and Zhe Chen, "An effective algorithm based on cluster analysis for CFA image processing," in Proceedings of IEEE International Conference on Neural Networks and Signal Processing (ICNNSP'08), Zhenjiang, China, June 2008. (IEEE Xplore)
 
[19] Zhe Chen and G. Chen, "An adaptive weighting approach for image color and magnitude interpolation," in Proceedings of IEEE International Conference on Consumer Electronics (ICCE'07), Las Vegas, NV, January 2007. (IEEE Xplore, PDF)
 
[20] Zhe Chen and F. Zhang, "A study of the bootload modes of TMS320VC5416 DSP," Journal of Hangzhou Institute of Electronic Engineering, vol. 22, no. 6, pp. 65-68, December 2002. (WanfangData, PDF in Chinese)
 
[21] Zhe Chen and F. Zhang, "A study of the open multimedia application platform (OMAP)," Journal of Hangzhou Institute of Electronic Engineering, vol. 22, no. 3, pp. 41-44, June 2002.(WanfangData, PDF in Chinese)


 
PUBLISHED PATENTS
 
[1, 2] Zhe Chen and G. Chen, “Adaptive classification scheme for CFA image interpolation,” China Patent: application number 200510116542.6, United States Patent: application number: 11/582,128. (Google Patent)



BOOK CHAPTERS

[1] R. Ranganathan, R. C. Qiu, Z. Hu, S. Hou, Zhe Chen, M. Pazos-Revilla, and N. Guo, “Cognitive radio network for Smart Grid,” in “Security and Privacy in Smart Grids,” to be published by CRC Press.
 

 
DISSERTATION AND THESIS
 
[1] Zhe Chen, "Cognitive radio network: Architecture, algorithms, and testbed," Ph.D. dissertation, 2011.

[2] Zhe Chen, "Study and implementation of speech recognition system for mobile communication terminals," Master's thesis, 2003. (WanfangData, PDF in Chinese)
 
 
 
PART OF PRESENTATIONS

[1] Reading group, Feb. 2011. (PDF)
 
[2] Reading group, Oct. 2010. (PDF)

[3] What’s going on in the field of Cognitive Radio (CR) and CR Network testbed, Sept. 2009. (PDF)

[4] Ultra-wideband (UWB) Impulse Radio Communication System Design and Prototyping, Dec. 2008. (PDF)
 
[5] MIMO Channel Capacitypy of Static Channels, Dec. 2008. (PDF)
 
[6] 3-Level Cache Implementation Using SimpleScalar, Dec. 2008. (PDF)
 
[7] Cache Part III - An Example, Nov. 2008. (PDF)
 
[8] An Introduction to Solving POMDPs, Nov. 2008. (PDF)
 
[9] The emerging video coding standard - AVS, Mar. 2007. (PDF)
 
 
 
TECHNICAL REPORTS
 
[1] Primary comparison between AVS1.0 and H.264/AVC.
 
[2] Proposed implementation architecture of motion compensation for both H.264 and AVS1.0 decoding.
 
[3] Proposed implementation architecture of loop filter for both H.264 and AVS1.0 decoding.
 
[4] Proposed implementations of VLC decoder and IQ-IT module for H.264/AVC and AVS1.0.
 
[5] Motion compensation of AVS-M and H.264 baseline.
 
[6] Loop filter of AVS-M and H.264 baseline.
 
[7] AVS-M decoding on Nomadik.
 
[8] MPE-FEC codec for DVB-H.
 
[9] Image demosizing algorithm.
 
 
 
SORTED RESOURCES
 
        1. Isolated-word speech recognition system
        2. CFA image interpolation and image demosizing algorithm
        3. About C/C++ coding style
 

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