Collaborative Research: RUI: Exploiting Upper Layer Spectrum Sensing and Directionality to Access the Hidden Available Spectrum

合作研究：RUI：利用上层频谱感知和方向性来访问隐藏的可用频谱

• 批准号: 2025307
• 负责人: Xingya Liu
• 金额: $ 18万
• 依托单位: Lamar University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-08-15 至 2024-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2025307&HistoricalAwards=false
• 关键词: Collaborative; Research; RUI; Exploiting; Upper

Cognitive radio has recently emerged as a promising technology to overcome the imbalance between the increase in spectrum access demand and the inefficiency in spectrum usage by allowing dynamic spectrum access. However, existing cognitive radio network research work is based on a number of conventional spectrum sensing and access mechanisms that suffer several drawbacks and are unable to exploit additional available spectrum opportunities. These conventional spectrum sensing mechanisms cannot differentiate primary user and secondary user signals effectively. They also cannot distinguish a primary user transmitter and receiver. In addition, conventional omnidirectional antenna-based spectrum access schemes cannot exploit the spatial spectrum availability to optimize the secondary user spectrum access capability. These drawbacks lead to spectrum resource waste and cannot be solved by physical-layer spectrum sensing and access techniques alone. Therefore, upper layer networking techniques are incorporated to solve these challenging problems. This research is potentially transformative as it will help generate innovative techniques to numerous applications of the cognitive radio technology, e.g., public safety networks, emergency networks, and health monitoring. It will also have significant impacts on research in emerging technologies with dynamic spectrum access, such as vehicular networks, mobile health, and opportunistic interconnections of heterogeneous wireless networks. The proposed designs can be applied to Internet-of-Things (IoT) with IoT devices efficiently accessing the wide spectrum. This project also integrates research findings into related graduate/undergraduate courses and diversity support.This project will have a significant impact on enhancing radio spectrum access. It aims at systematically investigating a novel spectrum sensing and access framework to discover and access additional available spectrum hidden from conventional spectrum sensing and access techniques in cognitive radio networks. In particular, this project consists of three major research tasks to achieve the goals of enhancing radio spectrum access: 1) network layer spectrum sensing scheduling to differentiate primary user and secondary user signals; 2) data link layer spectrum sensing to distinguish between a primary user transmitter and receiver; and (3) directional antenna-based spectrum access to proactively utilize the spatial spectrum opportunities, exploit the temporal and spatial channel availability, and obtain the optimal directional antenna sector angle.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.

认知无线电是近年来出现的一种新兴技术，它通过动态频谱接入来克服频谱接入需求增长与频谱使用效率低下之间的不平衡。然而，现有的认知无线电网络的研究工作是基于一些传统的频谱感测和接入机制，遭受几个缺点，无法利用额外的可用频谱的机会。这些传统的频谱感测机制不能有效地区分主用户和次用户信号。它们也无法区分主用户发射器和接收器。此外，传统的基于全向天线的频谱接入方案不能利用空间频谱可用性来优化次级用户频谱接入能力。这些缺点导致频谱资源浪费，并且不能单独通过物理层频谱感知和接入技术来解决。因此，上层网络技术被纳入解决这些具有挑战性的问题。这项研究具有潜在的变革性，因为它将有助于为认知无线电技术的众多应用产生创新技术，例如，公共安全网络、应急网络和健康监测。它还将对具有动态频谱接入的新兴技术的研究产生重大影响，例如车载网络、移动的健康以及异构无线网络的机会互连。所提出的设计可以应用于物联网（IoT），其中IoT设备有效地访问宽频谱。该项目还将研究成果融入相关的研究生/本科生课程和多样性支持中，这将对提高无线电频谱利用率产生重大影响。它旨在系统地研究一种新的频谱感知和接入框架，以发现和访问隐藏在传统的频谱感知和接入技术在认知无线电网络的额外可用频谱。具体而言，本项目主要包括三个方面的研究任务，以实现增强无线电频谱接入的目标：1）网络层频谱感知调度，以区分主用户和次用户信号; 2）数据链路层频谱感知，以区分主用户发射机和接收机;以及（3）基于定向天线的频谱接入以主动地利用空间频谱机会，利用时间和空间信道可用性，该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

Acknowledgment Mechanisms for Reliable File Transfer Over Highly Asymmetric Deep-Space Channels

• DOI: 10.1109/maes.2022.3192508
• 发表时间: 2022-09
• 期刊: IEEE Aerospace and Electronic Systems Magazine
• 影响因子: 3.6
• 作者: Lei Yang;Ruhai Wang;Jie Liang;Yu Zhou;Kanglian Zhao;Xingya Liu

A Joint Design of Deployment and Routing for Lifetime Maximization in Pipeline Sensor Networks

管道传感器网络生命周期最大化的部署和路由联合设计

• DOI: 10.1109/isncc55209.2022.9851806
• 发表时间: 2022
• 期刊: Computers and Communications (ISNCC
• 作者: Saritac, Ugur;Liu, Xingya;Newaz, Sabila;Wang, Ruhai;Imran, Hasan
• 通讯作者: Imran, Hasan