CRII: CNS: Towards Spectrum and Energy Efficient Large-scale IoT Communications: A Cross-layer Optimization Approach
CRII:CNS:迈向频谱和节能的大规模物联网通信:跨层优化方法
基本信息
- 批准号:2153428
- 负责人:
- 金额:$ 17.5万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Standard Grant
- 财政年份:2022
- 资助国家:美国
- 起止时间:2022-05-01 至 2022-12-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
This award is funded in whole or in part under the American Rescue Plan Act of 2021 (Public Law 117-2).Although 5G has dramatically improved network capacity and spectrum efficiency (SE), the explosive growth of Internet of Things (IoT) demands for more spectrum and energy resources to support high device density and massive traffics. It is estimated that at least 5.2 GHz bandwidth is required for just eHealth Care IoT if spectrum is accessed exclusively, or 1.3 GHz even with dynamic sharing strategy. It is clear that shortage of spectrum resources is a major bottleneck for the success of IoT popularity. On the other hand, current IoT devices use standards such as Bluetooth, LoRA, Sigfox, narrow-band IoT (NB-IoT), or Zigbee, which require power-hungry active radio frequency components like oscillators and converters. Battery-driven IoT devices can hardly sustain years of life-cycle goal even with infrequent transmission and optimized low-power protocols. Thus, sustainable energy consumption is another challenge. With tens of billions of IoTs desire for connectivity by 2030, there is a pressing need to address both SE and energy efficiency (EE) challenges to accommodate for such densified IoT networks. This research seeks to improve SE and EE performance while providing guaranteed quality of service (QoS) for IoTs at large-scale, thereby providing a feasible and practical connectivity solution in massive IoT era. Outcomes from this project can bring following impacts: 1) a hybrid and cooperative communication architect for IoTs, which combines benefits from both active and passive mode; 2) integration of research and curriculum design, capstone projects to both undergraduate and graduate students; 3) cutting-edge research experiences to a primarily undergraduate institution (PUI). The core approach is to enable IoT device with a wireless-powered hybrid communication structure that can not only minimize energy footprint with energy harvesting from ambient signals, but also integrate coordinated passive and active communication to support versatile QoS needs with efficient spectrum utilization through user cooperation. This project offers a holistic solution to deliver following innovations. 1) A novel PHY transmission architect. It combines a bio-inspired symbiotic radio to coordinate excessive interference. Optimization problems for SE and EE metrics are introduced from PHY resource allocation perspective. 2) The co-designed MAC layer protocol to ensure proper user and resource coordination. Two protocols will be introduced, one for maximum performance and the other for lower complexity. 3) System validation with software and hardware implementations. Extensive experimental verification is designed to systematically validate the performance of proposed schemes and algorithms.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
该奖项是根据2021年《美国救援计划法》的全部或部分资助(公法117-2)。尽管5G大大提高了网络容量和频谱效率(SE),这是物联网(IoT)的爆炸性增长(IOT)要求提供更多频谱和能源资源以支持高设备密度和大型贩运者。据估计,如果仅访问频谱,即使具有动态共享策略,也只需要至少5.2 GHz带宽。显然,频谱资源短缺是物联网受欢迎程度成功的主要瓶颈。另一方面,当前的物联网设备使用蓝牙,洛拉,sigfox,窄带物联网(NB-iot)或Zigbee等标准,这些标准需要渴望耗电的主动射频组件(例如振荡器和转换器)。电池驱动的物联网设备即使很少传输和优化的低功率协议也无法维持生命周期的多年目标。因此,可持续的能源消耗是另一个挑战。到2030年,有数十亿的物联网渴望连通性,因此需要解决SE和能源效率(EE)挑战以适应此类致密的IoT网络的挑战。这项研究旨在提高SE和EE的性能,同时为大规模的IoT提供保证的服务质量(QoS),从而在大型物联网时代提供了可行且实用的连接解决方案。该项目的结果可以带来以下影响:1)物联网的混合和合作交流架构师,该架构结合了主动模式和被动模式的好处; 2)整合研究和课程设计,为本科生和研究生的盖石材项目项目; 3)主要是本科机构(PUI)的尖端研究经验。核心方法是使用无线供电的混合通信结构启用物联网设备,该结构不仅可以通过从环境信号中收集能量来最大程度地减少能量足迹,而且还可以通过用户合作来整合了协调的被动和主动通信,以支持多功能QoS需求,并通过用户合作进行有效的频谱利用。该项目提供了一个整体解决方案,可以交付创新。 1)新颖的PHY传输建筑师。它结合了生物启发的共生无线电,以协调过度干扰。从PHY资源分配的角度引入了SE和EE指标的优化问题。 2)共同设计的MAC层协议,以确保适当的用户和资源协调。将引入两个协议,一个协议以最高性能,另一个用于较低的复杂性。 3)使用软件和硬件实现的系统验证。广泛的实验验证旨在系统地验证拟议方案和算法的性能。该奖项反映了NSF的法定任务,并使用基金会的知识分子优点和更广泛的影响审查标准,被认为值得通过评估。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Haijian Sun其他文献
Research on the medication rules of post-surgical thyroid cancer treatment by Professor Xu Zhiyin (based on multi-dimensional data mining).
许志银教授甲状腺癌术后治疗用药规律研究(基于多维数据挖掘)
- DOI:
10.1016/j.asjsur.2022.02.014 - 发表时间:
2022 - 期刊:
- 影响因子:3.5
- 作者:
Haijian Sun;Liu Li;Yong Zhu;Hong Zhu - 通讯作者:
Hong Zhu
WiSegRT: Dataset for Site-Specific Indoor Radio Propagation Modeling with 3D Segmentation and Differentiable Ray-Tracing: (Invited Paper)
WiSegRT:使用 3D 分割和可微光线追踪进行特定地点室内无线电传播建模的数据集:(特邀论文)
- DOI:
- 发表时间:
2023 - 期刊:
- 影响因子:0
- 作者:
Lihao Zhang;Haijian Sun;Jin Sun;Rose Qingyang Hu - 通讯作者:
Rose Qingyang Hu
Robust Beamforming Design in a NOMA Cognitive Radio Network Relying on SWIPT
基于 SWIPT 的 NOMA 认知无线电网络中的鲁棒波束成形设计
- DOI:
10.1109/jsac.2018.2872375 - 发表时间:
2018-07 - 期刊:
- 影响因子:16.4
- 作者:
Haijian Sun;Fuhui Zhou;Rose Qingyang Hu;Lajos Hanzo - 通讯作者:
Lajos Hanzo
Anti-rheumatic arthritis efficacy of <em>Pueraria montana</em> extract against type-II collagen-induced rheumatoid arthritis rat model an <em>in vitro</em> and <em>in vivo</em> assessment
- DOI:
10.1016/j.jep.2024.119175 - 发表时间:
2025-01-31 - 期刊:
- 影响因子:
- 作者:
Fangming Wang;Minli Liu;Qian Tang;Haijian Sun;Guangxia Yang;Jian Sun - 通讯作者:
Jian Sun
End-user viewpoint control of live video from a medical camera array
来自医疗摄像机阵列的实时视频的最终用户视点控制
- DOI:
10.1109/icdsc.2011.6042917 - 发表时间:
2011 - 期刊:
- 影响因子:0
- 作者:
Jeffrey R. Blum;Haijian Sun;Adriana Olmos;J. Cooperstock - 通讯作者:
J. Cooperstock
Haijian Sun的其他文献
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{{ truncateString('Haijian Sun', 18)}}的其他基金
ERI: Toward mmWave Vehicular Communication: A Multisensor Multimodal Deep Data Fusion Approach
ERI:迈向毫米波车辆通信:多传感器多模态深度数据融合方法
- 批准号:
2138680 - 财政年份:2022
- 资助金额:
$ 17.5万 - 项目类别:
Standard Grant
CRII: CNS: Towards Spectrum and Energy Efficient Large-scale IoT Communications: A Cross-layer Optimization Approach
CRII:CNS:迈向频谱和节能的大规模物联网通信:跨层优化方法
- 批准号:
2236449 - 财政年份:2022
- 资助金额:
$ 17.5万 - 项目类别:
Standard Grant
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