| NSF Org: |
CNS Division Of Computer and Network Systems |
| Recipient: |
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| Initial Amendment Date: | June 27, 2012 |
| Latest Amendment Date: | September 8, 2014 |
| Award Number: | 1161868 |
| Award Instrument: | Continuing Grant |
| Program Manager: |
Thyagarajan Nandagopal
CNS Division Of Computer and Network Systems CSE Directorate for Computer and Information Science and Engineering |
| Start Date: | September 1, 2012 |
| End Date: | August 31, 2017 (Estimated) |
| Total Intended Award Amount: | $376,000.00 |
| Total Awarded Amount to Date: | $376,000.00 |
| Funds Obligated to Date: |
FY 2014 = $188,000.00 |
| History of Investigator: |
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| Recipient Sponsored Research Office: |
110 INNER CAMPUS DR AUSTIN TX US 78712-1139 (512)471-6424 |
| Sponsor Congressional District: |
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| Primary Place of Performance: |
P. O Box 7726 Austin TX US 78713-7726 |
| Primary Place of
Performance Congressional District: |
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| Unique Entity Identifier (UEI): |
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| Parent UEI: |
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| NSF Program(s): |
Special Projects - CNS, Networking Technology and Syst |
| Primary Program Source: |
01001415DB NSF RESEARCH & RELATED ACTIVIT |
| Program Reference Code(s): |
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| Program Element Code(s): |
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| Award Agency Code: | 4900 |
| Fund Agency Code: | 4900 |
| Assistance Listing Number(s): | 47.070 |
ABSTRACT
Femto-aided cellular networks appear to be one the best solutions to achieve multi-fold capacity needed for future wireless networks. However, Femto-aided cellular systems have an information architecture that is very different from current planned and centrally managed cellular architecture. In this project, both the design of information architecture to acquire network state information and the optimal use of the resulting NSI will be addressed. The project is organized into three symbiotic research thrusts on network-aware physical-layer (PHY) coding schemes, network protocols and algorithms leveraging advanced PHYs, and their architectural prototypes. The first thrust utilizes recent innovations in deterministic models of wireless networks and develops novel physical-layer cooperative encoding and decoding schemes that operate with delayed, inconsistent, and erroneous NSI. The second thrust builds on the new physical-layer coding schemes to design network-scheduling algorithms to address performance issues. Finally, the third thrust utilizes the WARP programmable radios and studies implementation challenges of the protocols. The project goals of foundational design for Femto-aided cellular networks will have significant impact on industry practice. The PIs will facilitate technology transfer through their established industry affiliate program. A broad range of education and outreach activities will also complement the research agenda, including integration of research findings into the courses, promoting underrepresented and undergraduate populations, and engaging with the middle/high school community to raise the level of interest in engineering and mathematics.
PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH
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PROJECT OUTCOMES REPORT
Disclaimer
This Project Outcomes Report for the General Public is displayed verbatim as submitted by the Principal Investigator (PI) for this award. Any opinions, findings, and conclusions or recommendations expressed in this Report are those of the PI and do not necessarily reflect the views of the National Science Foundation; NSF has not approved or endorsed its content.
As physical layer technologies and network architectures advance, there is a need to develop network resource allocation algorithms that take advantage of these capabilities. This project has developed novel ideas, algorithms and analysis in this domain.
a. Device-to-device communications: We study device-to-device (D2D) enabled hierarchical cellular networks consisting of a macro base station (BS), a dense network of access nodes (ANs, e.g. femto stations) and mobile users, where spectrum is shared between cellular traffic and D2D traffic. Further, (the receivers of) mobile users dynamically time-share between the cellular and D2D networks. We have developed algorithms for channel allocation and mobile-user receiver mode selection (choosing which network to participate in) with the objectives of minimizing delay for cellular traffic, and capacity maximization for D2D traffic. Our proposed solution takes advantage of the unique features offered by large and densified cellular networks such as multi-point connectivity, channel diversity, spatial reuse and load distribution.
b. Understanding network resource allocation over short timescales: Emerging cellular network architectures result in smaller cell sizes, and thus, increased user mobility between cells. Thus, understanding the transient / short time-scale behavior of network algorithms become increasingly important. In this project, we have developed a new line of study to understand transient behavior of queues, where we explicitly characterize the loss in performance when compared to a genie-aided system that has complete knowledge of channel and arrival statistics. This work provides insights into the time-scale over which traditional (steady-state) performance analysis is meaningful.
c. New technical results on large-deviations for sampled systems: Large deviation results are useful for giving guarantees for rare events. In the wireless context, they are useful for providing bounds on maximum queue-length or delay that is experienced by a packet in a queue. Sampled systems arise in the setting when information is not fully available -- we can think of the information being sampled from the underlying full-channel-state. Our technical results are thus useful in providing guarantees in wireless systems with partial channel information.
d. There have been several graduate students who have been trained in both wireless network design and analysis, as well as stochastic modeling of network systems. The research led to several publications in the premier venues in this field. Finally, the results have been discussed with industry participants and business leaders to help direct future technology strategy.
Last Modified: 11/29/2017
Modified by: Sanjay Shakkottai
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