It's not a place, it's a yearning.
It's not a race, it's a journey.

Cognitive Mesh: Making Cellular Networks More Flexible

Project Information

  • “EARS: Collaborative Research: Cognitive Mesh: Making Cellular Networks More Flexible (CNS-1343220),” PI. National Science Foundation, January 1, 2014-December 31, 2017.
  • This webpage and the materials provided here are based upon work supported by the National Science Foundation under Grant No. CNS-1343220.

Project Summary

The exploding growth and popularity of wireless devices such as smartphones have resulted in the surge of various applications, such as anywhere anytime online social networking, mobile gaming, and mobile video services, which have exacerbated the congestion over cellular spectrum. On the other hand, many licensed spectrum blocks are left unused. Although cognitive radio (CR) technology has emerged to enable unlicensed users to opportunistically access the unused licensed spectrum, most previous works commonly assume that each user is equipped with a CR which can operate across a wide spectrum range. This may be possible in theory, but may not be practical for light-weight radios such as cell phones. How to effectively take advantage of the CR technology to build more flexible networks so that the non-CR capable devices can gain benefit from the opportunistic access to the unused spectrum is therefore in dire need. This proposal is to address this important issue. In particular, this proposal focuses on fundamental challenges associated with the development of a novel cognitive mesh assisted cellular network (CMCN). We plan to lay the algorithmic foundation, develop systematic design, and experimentally evaluate our design geared towards spectrum and energy efficiency in cellular networks. The developed technologies in this project will advance the state of the art in future cellular technologies, enrich the scientific knowledge of network theory and design, and thus can be used to find novel solutions to supporting more diversified applications, such as smart environments like smart cities and smart grids, mobile health systems, mobile social networks, and public safety systems, which will then create more business opportunities for job creation and economic growth.

Personnel

  • Pan Li, PI
  • Xuhui Chen, Ph.D. Student
  • Ming Li, Ph.D. Student (Graduated in August, 2014)
  • Weixian Liao, Ph.D. Student
  • Robert Luo, Ph.D. Student
  • Sergio Salinas, Ph.D. Student (Graduated in August, 2015)
  • Arun, Thapa, Ph.D. Student (Graduated in August, 2014)

Publications

Journal Papers

  1. 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.
  2. C. Luo, L.T. Yang, P. Li, and X. Xia, “A holistic energy optimization framework for cloud‐assisted mobile computing,” IEEE Wireless Communications, Vol. 22, No. 3, pp. 118–123, June 2015.
  3. 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.
  4. 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.
  5. 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).
  6. 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.
  7. 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.
  8. Yue Tong, Jinyuan Sun, Sherman S. M. Chow, and Pan Li, “Cloud-assisted Mobile-access of Health Data with Privacy and Auditability,” IEEE Journal of Biomedical and Health Informatics, Vol. 18, No. 2, pp. 419-429, March 2014.

Conference Papers

  1. Linke Guo, Yuguang Fang, Ming Li, and Pan Li, “Verifiable Privacy-preserving Monitoring for Cloud-assisted mHealth Systems,” IEEE International Conference on Computer Communications (INFOCOM’15), Hong Kong, China, April 26-May 1, 2015. (Acceptance ratio = 316/1640 = 19%)
  2. 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%)
  3. 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%)
  4. 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)
  5. 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%)

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: Advanced Topics in Wireless Networks and ECE 8990: Wireless Communications at MSU. Both 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.

Besides, the research in this project is one of the main topics in the split‐level course ECE 4823/6823: Digital Communications, and the graduate course ECE 8823: Wireless Networks at MSU. The second graduate course is also offered to long‐distance students. Furthermore, PI Li has developed several new graduate courses including ECE 8990: Advanced Topics in Big Data, and ECE 8990: Advanced Topics in Cognitive Radio Networks. These courses focused on fundamental challenges and hot topics in big data and cognitive radio networks, respectively, and were highly received by both EE and CS graduate students. The research outcomes and network design methodologies developed in this project have been channelized into the classroom.

In addition, two of the Ph.D. students who worked on this project, i.e., Ming Li and Arun Thapa, graduated in Summer 2014. Ming joined the Department of Computer Science and Engineering at University of Nevada, Reno, and Arun joined the Department of Electrical Engineering at Tuskegee University, respectively, as tenure‐track Assistant Professors. Another Ph.D. student, Sergio Salinas, graduated in Summer 2015, and joined the Department of Electrical Engineering and Computer Science at Wichita State University as a tenure‐track Assistant Professor. Continuing collaborations with them has extended the impact of this project to universities in Nevada, Alabama, and Kentucky as well.

 

ears.txt · Last modified: 2015/10/09 12:34 by lipanleo