NeTS: Small: Spectrum Sensing and Resource Allocation for Cognitive Radio Networks

NeTS：小型：认知无线电网络的频谱感知和资源分配

• 批准号: 1421869
• 负责人: Brian Mark
• 金额: $ 47.24万
• 依托单位: George Mason University
• 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
• 起止时间: 2014-10-01 至 2018-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1421869&HistoricalAwards=false
• 关键词: NeTS; Small; Spectrum; Sensing; Resource

Radio spectrum has become an increasingly expensive and scarce resource due to the exponential growth of the wireless industry and the rapid proliferation of wireless devices over the past couple of decades. Ironically, studies of spectrum usage have shown that much of the available spectrum is highly underutilized, due to the current policy of static allocation, which partitions the spectrum into various licensed bands. The main goal of this project is to develop a cost-effective solution to the spectrum scarcity issue based on emerging cognitive radio technology, which has the potential to allow unlicensed users to reclaim unused spectrum in the licensed bands. A cognitive radio is capable of detecting unused or idle spectrum and dynamically tuning its transmission and reception activities to the so-called spectrum holes. A group of unlicensed users equipped with cognitive radios can form a network and communicate with each other via such spectrum holes. This research focuses on developing efficient and accurate methods for cognitive radios to identify spectrum holes and allocate this spectrum to enable communications among unlicensed users without causing harmful interference to the licensed users of a spectrum band. A major challenge of this work lies in how to perform spectrum sensing and resource allocation in a cognitive radio network to maximize its capacity while managing the additional interference and overhead incurred by the cognitive radios. If the project is successful, the research results should have a significant impact on increasing the capacity and performance of future wireless networks. The research is expected to advance the field of cognitive radio and contribute towards its adoption in commercial applications. The results of this research will be applicable to future infrastructured wireless networks, as well as wireless communications in emergency scenarios such as disaster relief. An experimental platform will be developed to prototype and evaluate the effectiveness of the proposed dynamic spectrum access approach in practical wireless environments. Students, including some from underrepresented groups, will gain practical experience from working with the cognitive radio testbed. New course materials will be developed to teach the basics of cognitive radio technology to students at the graduate level. The technical approach of this research centers on a joint consideration of spectrum sensing and resource allocation, taking into account the three main dimensions of spectrum holes, i.e., time, space, and frequency. A multidimensional characterization of spectrum holes will be developed, which incorporates a bivariate Markov chain to model temporal dynamics, power control in the context of spatial spectrum sensing, and frequency-domain search for spectrum holes in the wideband regime. A model of a cognitive radio network based on simplicial homology will be developed to allocate spectrum resources among cognitive radio nodes, as well as the communication and computational resources required for spectrum sensing, to optimize performance from a networking perspective. Interference modeling and management for the cognitive radio network will be addressed in conjunction with resource allocation. The project will study tradeoffs among communications and computational resources within the proposed framework for dynamic spectrum access. An important component of the project is the development of a cognitive radio network testbed based on an open software radio platform, which will be used to prototype and evaluate the performance of the proposed algorithms and protocols in realistic wireless scenarios.

由于无线行业的指数增长以及过去几十年来无线设备的快速增长，无线电频谱已成为越来越昂贵和稀缺的资源。 具有讽刺意味的是，频谱使用的研究表明，由于当前的静态分配策略，将频谱分配为各种许可频段，因此许多可用光谱都高度不足。 该项目的主要目的是基于新兴的认知无线电技术开发一种具有成本效益的解决方案，该解决方案有可能允许未经许可的用户在许可乐队中收回未使用的光谱。 认知无线电能够检测未使用或闲置的光谱，并动态调整其传播和接收活动到所谓的光谱孔。 一组配备认知无线电的无执照的用户可以形成网络并通过此类频谱孔相互通信。 这项研究着重于为认知无线电开发有效，准确的方法，以识别频谱孔并分配此频谱，以使无执照的用户之间的通信，而不会对光谱频段的许可用户有害干扰。 这项工作的主要挑战在于如何在认知无线网络中执行频谱传感和资源分配，以最大程度地提高其能力，同时管理认知无线电产生的其他干扰和间接费用。 如果项目成功，研究结果将对提高未来无线网络的能力和性能产生重大影响。 这项研究有望推进认知无线电领域，并有助于其在商业应用中的采用。 这项研究的结果将适用于未来的基础架构无线网络，以及在诸如救灾等紧急情况下的无线通信。 将开发一个实验平台来原型和评估实用无线环境中提出的动态频谱访问方法的有效性。 包括来自代表性不足的团体的一些学生，将获得与认知无线电测试台合作的实践经验。 将开发新的课程材料，以向研究生一级的学生讲授认知无线电技术的基础知识。 考虑到光谱孔的三个主要维度，即时间，空间和频率，这项研究的技术方法集中在频谱传感和资源分配的联合考虑。 将开发出光谱孔的多维表征，该表征结合了双变量马尔可夫链，以建模时间动力学，在空间光谱传感的背景下进行功率控制以及频率域中的频率域搜索宽带状态中的光谱孔。 将开发基于简单同源性的认知无线网络的模型，以在认知无线电节点之间分配光谱资源，以及光谱传感所需的通信和计算资源，以从网络角度优化性能。 认知无线网络的干扰建模和管理将与资源分配结合解决。 该项目将在拟议的动态频谱访问框架内研究通信和计算资源之间的权衡。 该项目的一个重要组成部分是基于开放软件无线电平台的认知无线网络测试台的开发，该平台将用于原型和评估所提出的算法和协议在现实无线方案中的性能。

项目成果

Gaussian random field approximation for exclusion zones in cognitive radio networks

认知无线电网络中禁区的高斯随机场近似

• DOI: 10.1109/pimrc.2017.8292398
• 发表时间: 2017
• 期刊: Indoor and Mobile Radio Communications (PIMRC
• 作者: Wang, Zheng;Mark, Brian L.
• 通讯作者: Mark, Brian L.

A Recursive Algorithm for Wideband Temporal Spectrum Sensing

• DOI: 10.1109/tcomm.2017.2749578
• 发表时间: 2018
• 期刊: IEEE Transactions on Communications
• 影响因子: 8.3
• 作者: J. Bruno;B. L. Mark