Enabling Cellular Services over Unplanned Femto-cell Deployments: From Theory to Implementation

This is a collaborative research project with Prasun Sinha at Ohio State University and R. Srikant at UIUC under the support of National Science Foundation Grant CNS-1160775.

Mobile phones are becoming the dominant platform for networked applications, but cellular data rates remain orders-of-magnitude lower than those of wireless local area networks. A new concept, the femtocell, offers promise to bridge this gap in capacity. Femtocells are built by installing a small, short-range, cellular base station at the owner’s premises and connecting it to a broadband network. Having a short range and a limited number of users allows a femtocell to provide orders-of-magnitude more cellular throughput than a macrocell. As femtocells operate in the cellular wireless bands, their ad-hoc deployment without advanced planning constitutes a complete paradigm shift for the cellular industry, which has mainly relied on planned deployment of macrocells with labor-intensive manual tuning and static channel assignment.

In this project we have been developing the foundations for resource allocation in femtocell networks, and study the performance of the solutions using a prototype deployment. Specifically, we have been focusing on market-based as well as non-market-based solutions as follows:

  • Joint Resource Scheduling and Handover for Legacy Systems: For legacy systems, we have been developing distributed solutions for both downlink and uplink scheduling and handover under co-deployment of macro- and femto-cells that do not require any changes to existing hardware and standards.
  • Joint Base Station Association, Channel Assignment and Power Control: We have been developing distributed, adaptive and self-organizing solutions (unconstrained by legacy requirements for resource allocation by using a powerful tool from statistical physics, called Glauber dynamics.
  • Market-based Multi-party Resource Allocation: We are designing mechanisms to facilitate truthful auctions in practical settings involving the end-users, the femtocell owners, and the operator to accelerate deployment of femtocells and investigate how such market based solutions can co-exist with the above non-market-based schemes.

All our solutions will be implemented and evaluated on testbeds being built at the University of Michigan and OSU.

Project Participants at University of Michigan: Kang G. Shin (PI), Krishna C. Garikipati (graduate student at UM)

Publications:

  • Ruihao Zhu and Kang G. Shin, Differentially Private and Strategy-Proof Spectrum Auction with Approximate Revenue Maximization, Proceedings of the 34th IEEE International Conference on Computer Communications (INFOCOM 2015), Hong Kong, China, April, 2015. PDF pdf
  • Mohammad Ghadir Khoshkholgh, Keivan Navie, Kang G. Shin, Chun-Hung Liu, Yan Zhang, Victor Leung, and Stein Gjessing (2015). On the impact of delay constraint on the multicast outage in wireless fading environment. 2015 IEEE International Conference on Communications — Mobile and Wireless Networking Symposium} (ICC’15 (03) MWN). London.PDF pdf
  • Eugene Chai, Kang G. Shin, Sung-Ju Lee, Jeongkeun Lee, and Raul Etkin, SPIRO: Turning elephants into mice with efficient RF transport, Proceedings of the 34th IEEE International Conference on Computer Communications (INFOCOM 2015), Hong Kong, China, April, 2015. PDF pdf
  • Yu-Chih Tung, Sihui Han, Dongyao Chen, and Kang G. Shin, Vulnerability and Protection of Channel State Information in Multiuser MIMO Networks, The 21st ACM Conference on Computer and Communications Security (CCS’14), Nov. 3-7, 2014, Scottsdale, Arizona, USA. PDF pdf
  • Jihoon Yun and Kang G. Shin,Distributed coordination of co-channel femtocells via
    inter-cell signaling with arbitrary delay,
    IEEE Journal on Selected Areas of Communications, vol.33, no.6, pp.1127–1139, June 2015. PDF pdf
  • Mohammad G. Khoshkholgh, Nader Mokari, Keivan Navaie, Halim Yanikomeroglu, Victor C. M. Leung, and Kang G. Shin, Radio resource allocation in OFDM-based spectrum-sharing systems: duality gap and time averaging, IEEE Journal on Selected Areas of Communications, vol.33, no.5, pp.848–864, May 2015.PDF pdf
  • Mohammad Ghadir Khoshkholgh, Yan Zhang, Kwang-Cheng Chen, Kang G. Shin, and Stein Gjessing (2015). Connectivity of cognitive device-to-device communications in cellular networks with coverage guarantee. IEEE Journal of Selected Areas of Communications. 33 (1), 81.PDF pdf
  • Xinyu Zhang and Kang G. Shin, Cooperation without synchronization: Practical cooperative relaying in wireless networks, IEEE Transactions on Mobile Computing, vol.14, no.5, pp.937–950, May 2015.PDF pdf
  • Krishna C. Garikipati and Kang G. Shin (2013). Distributed association control in shared wireless networks. IEEE International Conference on Sensing, Communication, and Networking (SECON’13). New Orleans.
  • Linjing Zhao, Guangrui Huo, and Kang G. Shin (2013). Enhanced spectrum resource allocation for femtocells. IEEE 78-th Vehicular Technology Conference: VTC2013-Fall. Las Vegas.
  • Xinyu Zhang, Karthik Sundaresan, Amir Khojastepour, Sampath Rangarajan, and Kang G. Shin (2013). NEMOx: Scalable network MIMO for wireless networks. 19-th Annual ACM International Conference on Mobile Computing and Networking (ACM MobiCom’13). Miami, FL.
  • Jeong-Yoon Lee, Chansu Yu, Kang G. Shin, and Young-Ju Suh (2013). Maximizing Transmission Opportunities in Wireless Multihop Networks. 12. (9). IEEE Transactions on Mobile Computing, 12. 1879-1892.
  • Mohammad G. Khoshkholgh, Nader Mokari, and Kang G. Shin (2013). Ergodic sum capacity of spectrum-sharing multiple access with collision metric. 31. (11). IEEE Journal of Selected Areas of Communications, 31. 2528-2540.
  • Hyoil Kim, Jaehyuk Choi, and Kang G. Shin (2013). Hierarchical market competition in a duopoly super Wi-Fi spectrum market. 31. (11). IEEE Journal of Selected Areas of Communications, 31. 2580-2590.
  • Eugene Chai, Kang G. Shin, Jongkeun Lee, Sung-Ju Lee, and Raul Etkin (2014). Fast spectrum shaping for next-generation wireless networks. 13. (1). IEEE Transactions on Mobile Computing, 13. 20-34.