| NSF Org: |
CNS Division Of Computer and Network Systems |
| Recipient: |
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| Initial Amendment Date: | September 16, 2015 |
| Latest Amendment Date: | September 16, 2015 |
| Award Number: | 1547239 |
| Award Instrument: | Standard Grant |
| Program Manager: |
Alexander Sprintson
CNS Division Of Computer and Network Systems CSE Directorate for Computer and Information Science and Engineering |
| Start Date: | January 1, 2016 |
| End Date: | December 31, 2018 (Estimated) |
| Total Intended Award Amount: | $200,000.00 |
| Total Awarded Amount to Date: | $200,000.00 |
| Funds Obligated to Date: |
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| 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: |
Austin TX US 78712-1532 |
| 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): | EARS |
| Primary Program Source: |
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| 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
As new spectrum for data communication becomes available, it is increasingly important to develop cognitive network technologies that can opportunistically use spectrum whenever available and speak different wireless protocols on demand. Full duplex wireless is an exciting new technology that allows a node to send and receive simultaneously on the same spectrum. Despite significant progress, existing work on full duplex wireless focuses on narrowband production wireless systems, such as Wi-Fi and ZigBee. This project aims to develop novel systems and algorithms to embrace full duplex for cognitive networks and support different wireless technologies. The research will be integrated into undergraduate and graduate curriculum, and disseminated broadly to researchers, practitioners policy makers, high school students, parents, and teachers.
The project develops techniques that (i) go beyond narrowband and use novel cancellation mechanisms to enable transmit-while-sensing on a wider band spectrum, (ii) support cross technologies that transmit Wi-Fi while receiving LTE and vice versa, and (iii) translate physical layer advances to end-to-end performance benefits by re-visiting upper-layer protocol design. These three thrusts will enable a holistic full duplex cognitive radio platform.
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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.
This project aims to optimize spectrum efficiency by developing cognitive radio technologies including distributed channel allocation, smart rate adaptation, and interference management for long-range communication. We not only develop physical layer approaches but also revisit upper-layer protocol designs in order to translate physical layer advances to end-to-end performance benefits.
Highlights of the major research outcomes include:
(1) Developing a distributed channel allocation without coordination that has provable optimality guarantees and does not need message exchanges or channel scanning.
(2) Understanding the fundamental problem how wireless channel state information (CSI) relates to link performance, developing two complementary methods for computing frame delivery rate to capture the bursty errors under the WiFi interleaver, and designing a new interleaver to reduce the burstiness of errors and improve the frame delivery rate.
(3) Designing a smart retransmission scheme where the receiver combines information received from multiple failed transmissions associated with the same frame with the following two distinguishing features: (i) it can simultaneously support partial retransmission and combines bits with low confidence, and (ii) it has the first combining-aware rate adaptation scheme, which selects the data rates for all transmissions associated with the same frame to maximize overall throughput.
(4) Optimizing rate adaptation and retransmission for Multi-User MIMO: To effectively harness the ideal gain of MU-MIMO, we develop Concurrent Packet Recovery (CPR), a recovery protocol customized for MU-MIMO. It has two distinctive features: (i) It judiciously selects the minimum number of streams to be retransmitted to support successful decoding; (ii) during retransmission, it utilizes the full degrees of freedom by allowing new streams to be sent in parallel. Our evaluation via testbed experiments and trace-driven simulations shows that can efficiently recover both normal losses and collisions.
(5) Developing CellFi, an alternative architecture based on LTE. Unlike LTE, CellFi overcomes co-existence problems by designing an LTE-compatible spectrum database component, mandatory for TV white space networking, and introducing an interference management component for distributed coordination. CellFi interference management is compatible with existing LTE mechanisms, requires no explicit communication between base stations, and is more efficient than CSMA for long links.
Broader impacts of this project include substantial interactions with industry centered on the impact and insights from our research. We engaged the community through participation in various forms, including invited talks at conferences, universities, companies. During the duration project has partially supported and engaged roughly 3 graduate students, otwo of who has successfully defended his Ph.D. dissertation and joined in industry.
Last Modified: 04/01/2019
Modified by: Lili Qiu
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