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Stochastic Modeling and Optimization for Cognitive Radio Networks

Project Information

  • “CCSS: Collaborative Research: Stochastic Modeling and Optimization for Cognitive Radio Networks (ECCS-1128768),” PI. National Science Foundation, September 15, 2011–August 31, 2015
  • This webpage and the materials provided here are based upon work supported by the National Science Foundation under Grant No. ECCS-1128768.

Project Summary

The objective of this research is to develop network protocols and optimization techniques to efficiently utilize the spectrum white spaces for cognitive radio networks. The proposed approach is based on a novel cognitive radio network (CRN) network architecture under which effective design methodologies can be developed to take better advantage of cognitive radio technologies in harvesting and managing unutilized spectrum for better service provisioning. In this project, we will first study the proposed CRN architecture to enable collective spectrum sensing and let the secondary service provider manage the harvested spectrum for better spectral efficiency while shifting the design complexity from the user side to the system side. We will then investigate how to split traffic over harvested spectral bands to balance the risk and reward, how to optimally utilize the spectral resource by jointly designing frequency allocation and routing while supporting traffic demands, and how to maximize the throughput by joint link scheduling and routing. The proposed research outcome will lay the solid foundation for practical implementation of CRNs, which could potentially revolutionizes the way how cognitive radios should be more effectively used. The expected research outcome will significantly advance the state of the art in CRNs, opening a new avenue to designing smart living environments for public safety, disaster rescue, mobile healthcare and online social networks to improve peoples quality of life. Research findings will be disseminated through publications and talks, and in classroom teaching. This project will also actively recruit and train minority students for future workforce and mentor junior faculty.

Personnel at MSU

  • Pan Li, PI
  • Ming Li, Ph.D. Student
  • Weixian Liao, Ph.D. Student
  • Changqing Luo, Ph.D. Student
  • Sergio Salinas, Ph.D. Student
  • Arun Thapa, Ph.D. Student
  • Kaijin Zhang, Ph.D. Student

Personnel at Collaborative Institution

  • Yuguang Fang, University of Florida, PI

Publications

Journal Papers

  1. Sergio Salinas and Pan Li, “Privacy-Preserving Energy Theft Detection in Microgrids: A State Estimation Approach,” to appear in IEEE Transactions on Power Systems.
  2. Arun Thapa, Weixian Liao, Ming Li, Pan Li, and Jinyuan Sun, “SPA: A Secure and Private Auction Framework for Decentralized Online Social Networks,” to appear in IEEE Transactions on Parallel and Distributed Systems.
  3. Weixian Liao, Ming Li, Sergio Salinas, Pan Li, and Miao Pan, “Energy-Source-Aware Cost Optimization for Green Cellular Networks with Strong Stability,” to appear in IEEE Transactions on Emerging Topics in Computing.
  4. Arun Thapa, Ming Li, Sergio Salinas, and Pan Li, “Asymmetric Social Proximity Based Private Matching Protocols for Online Social Networks,” IEEE Transaction on Parallel and Distributed System, Vol. 26, No. 6, pp. 1547-1559, June 2015.
  5. Ming Li, Sergio, Salinas, Pan Li, Jinyuan Sun, and Xiaoxia Huang, “MAC-Layer Selfish Misbehavior in IEEE 802.11 Ad Hoc Networks: Detection and Defense,” IEEE Transactions on Mobile Computing, Vol. 14, No. 6, pp. 1203-1217, June 2015.
  6. Ming Li, Pan Li, Xiaoxia Huang, Yuguang Fang, and Savo Glisic, “Energy Consumption Optimization for Multihop Cognitive Cellular Networks,” IEEE Transactions on Mobile Computing, Vol. 4, No. 2, pp. 358-372, February 2015. (Feature Article of the February Issue).
  7. Ming Li, Sergio Salinas, Pan Li, Xiaoxia Huang, Yuguang Fang, and Savo Glisic, “Optimal Scheduling for Multi-radio Multi-channel Multi-hop Cognitive Cellular Networks,” IEEE Transactions on Mobile Computing, Vol. 14, No. 1, pp. 139-154, January 2015.
  8. Miao Pan, Pan Li, Yang Song, Yuguang Fang, Phone Lin, and Savo Glisic, “When Spectrum Meets Clouds: Optimal Session Based Spectrum Trading under Spectrum Uncertainty,” IEEE Journal on Selected Areas in Communications – Cognitive Radio Series, Vol. 32, No. 3, pp. 615-627, March 2014.
  9. Ming Li, Sergio Salinas, and Pan Li, “Locaward: A Security and Privacy Aware Location-Based Rewarding System,” IEEE Transactions on Parallel and Distributed Systems – Special Issue on Trust, Security, and Privacy, Vol. 25, No. 2, pp. 343-352, February 2014.
  10. Ming Li and Pan Li, “Crowdsourcing in Cyber-Physical Systems: Stochastic Optimization with Strong Stability,” IEEE Transactions on Emerging Topics in Computing – Special Issue on Cyber-Physical Systems, Vol 1, No. 2, pp. 218-231, December 2013.
  11. Sergio Salinas, Ming Li, Pan Li, and Yong Fu, “Dynamic Energy Management for the Smart Grid with Distributed Energy Resources,” IEEE Transactions on Smart Grid, Vol. 4, No. 4, pp. 2139-2151, December 2013.
  12. Sergio Salinas, Ming Li, Pan Li, “Privacy-Preserving Energy Theft Detection in Smart Grids: A P2P Computing Approach,” IEEE Journal on Selected Areas in Communications – Special Issue on Emerging Technologies in Communications, Vol. 31, No. 9, pp. 257-267, September 2013.
  13. Sergio Salinas, Ming Li, Pan Li, “Multi-Objective Optimal Energy Consumption Scheduling in Smart Grids,” IEEE Transactions on Smart Grid, Vol. 4, No. 1, pp. 341-348, March 2013.
  14. Miao Pan, Pan Li, and Yuguang Fang, “Cooperative Communication Aware Link Scheduling for Cognitive Vehicular Ad-hoc Networks,” IEEE Journal on Selected Areas in Communications – Special Issue on Broadband Wireless Communications for High Speed Vehicles, Vol. 30, No. 4, pp. 760-768, May 2012.
  15. Miao Pan, Chi Zhang, Pan Li, and Yuguang Fang, “Spectrum Harvesting and Sharing in Multi-hop CRNs under Uncertain Spectrum Supply,” IEEE Journal on Selected Areas in Communications – Special Issue on Cooperative Networking Challenges and Applications, Vol. 30, No. 2, pp. 369-378, February 2012.

Conference Papers

  1. Ming Li, Pan Li, Linke Guo, and Xiaoxia Huang, “PPER: Privacy-Preserving Economic-Robust Spectrum Auction in Wireless Networks,” IEEE International Conference on Computer Communications (INFOCOM’15), Hong Kong, China, April 26-May 1, 2015. (Acceptance ratio = 316/1640 = 19%)
  2. Sergio Salinas, Changqing Luo, Xuhui Chen, and Pan Li, “Efficient Secure Outsourcing of Large-scale Linear Systems of Equations,” IEEE International Conference on Computer Communications (INFOCOM’15), Hong Kong, China, April 26-May 1, 2015. (Acceptance ratio = 316/1640 = 19%)
  3. Sergio Salinas, Changqing Luo, Weixian Liao, Pan Li, “State Estimation for Energy Theft Detection in Microgrids,” the 9th International Conference on Communications and Networking in China (ChinaCom’14), Maoming, China, August 14-16, 2014. (Best Paper Award)
  4. Weixian Liao, Ming Li, Sergio Salinas, Pan Li, and Miao Pan, “Optimal Energy Cost for Strongly Stable Multi-hop Green Cellular Networks,” IEEE International Conference on Distributed Computing Systems (ICDCS’14), Madrid, Spain, June 30-July 3, 2014. (Acceptance ratio: 66/500 = 13%)
  5. Ming Li, Pan Li, Miao Pan, and Jinyuan Sun, “Economic-Robust Transmission Opportunity Auction in Multi-hop Wireless Networks,” IEEE International Conference on Computer Communications (INFOCOM’13), Turin, Italy, April 14-19, 2013. (Acceptance ratio = 280/1613 = 17%)
  6. Ming Li, Sergio Salinas, Arun Thapa, and Pan Li, “n-CD: A Geometric Approach to Preserving Location Privacy in Location-Based Services,” IEEE International Conference on Computer Communications (INFOCOM’13), Turin, Italy, April 14-19, 2013. (Acceptance ratio = 280/1613 = 17%)
  7. Sergio Salinas, Ming Li, Pan Li, “Privacy-Preserving Energy Theft Detection in Smart Grids,” IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks (SECON’12), Seoul, Korea, June 18-21, 2012.
  8. Miao Pan, Pan Li, Yang Song, Yuguang Fang, and Phone Lin, “Spectrum Clouds: A Session Based Spectrum Trading System for Multi-hop Cognitive Radio Networks,” IEEE International Conference on Computer Communications (INFOCOM’12), Orlando, Florida, March 25-30, 2012. (Acceptance ratio = 278/1547 = 18%)

Outreach and Education Activities for Broader Impact

Our major results have been disseminated through presentations and publications in meetings, conferences, and journals. A substantial quantity of the materials of this project have also been made publicly available online here.

Besides, the research in this project is one of the main topics in the split-level courses ECE 4813/6813: Communication Theory and ECE 4823/6823: Digital Communications, and the graduate courses ECE 8823: Wireless Networks, ECE 8990: Wireless Communications, ECE 8990: Smart Grids, ECE 8990: Advanced Topics in Cloud Computing, and ECE 8990: Advanced Topics in Cognitive Radio Networks at MSU. The graduate courses are also offered to long-distance students. The research outcomes and network design methodologies developed in this project have been channelized into the classroom.

In addition, three of the Ph.D. students who worked on this project, i.e., Ming Li, Arun Thapa, and Sergio Salinas, have graduated. Ming joined the Department of Computer Science and Engineering at University of Nevada, Reno, Arun joined the Department of Electrical Engineering at Tuskegee University, and Sergio joined the Department of Electrical Engineering and Computer Science at Wichita State University respectively, as a tenure-track Assistant Professor. Continuing collaborations with them has extended the impact of this project to universities in Nevada, Alabama, and Wichita as well.

 

ccss11.txt · Last modified: 2015/11/29 11:32 by lipanleo