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CIF: Small: Fundamentals of Energy-Efficiency in Delay-SensitiveWireless Communications

CIF: Small: Fundamentals of Energy-Efficiency in Delay-SensitiveWireless Communications
CIF:小:延迟敏感无线通信中的能源效率基础
批准号:
1422241
负责人:
Lingjia Liu
金额:
$12.27万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2014
资助国家:
美国
项目状态:
已结题
起止时间:
2014-08-01 至 2016-07-31

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中文摘要
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英文摘要
This project aims to improve the understanding of delay-sensitive communications over modern wireless systems and networks where the physical layer transmission is based on transport blocks. Information theory, communication theory, and queuing theory will be integrated to provide a framework to analyze wireless system performance by jointly considering decoding error probability and delay-violation probability. To be specific, a transport block-based channel dispersion will be developed to understand the interplay among channel coding over finite transport blocks, channel knowledge feedback, modulation, and probability of decoding error for modern wireless systems. Performance of hybrid automatic repeat request (HARQ) systems will also be analyzed under this framework. The outcome of this project is expected to provide design guidance for modern and future wireless systems and networks that supports delay-sensitive traffic. Wireless devices are an integral part of society and are currently used by over 95% of the global population. Research that leads to improving their performance under delay-sensitive traffic offers the potential to improve how these devices serve the needs of their users. In addition to global technological impact, this project has an educational plan that will immerse students from various backgrounds in the exciting field of mobile wireless communications.
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Collaborative Research: SWIFT: Intelligent Dynamic Spectrum Access (IDEA): An Efficient Learning Approach to Enhancing Spectrum Utilization and Coexistence
RINGS: Learning-Enabled Ground and Air Integrated Networks (GAINs)
Collaborative Research: MLWiNS: Deep Neural Networks Meet Physical LayerCommunications -- Learning with Knowledge of Structure
SpecEES: Collaborative Research: Enabling Spectrum and Energy-Efficient Dynamic Spectrum Access Wireless Networks using Neuromorphic Computing
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