CCF: Small: Sensing-Based Dynamic Spectrum Access Networks: Modeling, Algorithms, and Experimental Validation

CCF：小型：基于传感的动态频谱接入网络：建模、算法和实验验证

• 批准号: 1117365
• 负责人: J Nicholas Laneman
• 金额: $ 47.31万
• 依托单位: University of Notre Dame
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-09-01 至 2015-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1117365&HistoricalAwards=false
• 关键词: CCF; Small; Sensing; Based; Dynamic

The FCC released its National Broadband Plan citing the exponentially growing demand for mobile data services and the critical need to better utilize the radio spectrum. Beyond retargeting certain frequency bands, the FCC is considering a paradigm shift of dynamic spectrum access (DSA) technology and policy. DSA allows 'secondary' radios to transmit in underutilized 'white space' provided they create minimal interference to 'primary' radios. Significant white space, as much as 85%, has been observed across time, frequency, and location. However, even in the TV bands, the challenge of inconspicuous utilization of white spaces has not yet been achieved by the two leading solutions, distributed spectrum sensing and centralized emitter databases.This project focuses on a comprehensive approach to DSA based upon spectrum sensing that combines the following in a feedback loop: novel modeling of primary and secondary transmissions; design of optimal spectrum sensing algorithms and secondary access protocols based upon these models; and experimental validation within a testbed of software-defined radios. Preliminary results develop primary Markov models and optimal sequence detection algorithms for spectrum sensing that build upon the well-known Viterbi and forward-backward algorithms and expose fundamental limitations due to primary mismatch for the commonly used energy detector. The connections to trellis- and graph-based algorithms from the channel coding community should introduce a sizable new toolbox to DSA researchers. Secondary access protocols that take advantage of Markov process models for the primary users similarly exhibit improved performance tradeoffs between primary interference and secondary throughput. Collaborators in industry and regulatory bodies will be kept informed of the research results with an aim toward impacting DSA technology and policy development at national and international levels.

美国联邦通信委员会 (FCC) 发布了国家宽带计划，指出对移动数据服务的需求呈指数级增长以及更好地利用无线电频谱的迫切需要。 除了重新定位某些频段外，FCC 还在考虑动态频谱接入 (DSA) 技术和政策的范式转变。 DSA 允许“辅助”无线电在未充分利用的“空白空间”中进行传输，前提是它们对“主要”无线电产生的干扰最小。 在不同时间、频率和位置上都观察到了高达 85% 的显着空白。 然而，即使在电视频段，分布式频谱感知和集中式发射器数据库这两种领先解决方案也尚未解决不显眼利用空白空间的挑战。该项目重点关注基于频谱感知的 DSA 综合方法，该方法将以下内容结合在反馈环中：初级和次级传输的新颖建模；基于这些模型设计最佳频谱感知算法和辅助接入协议；以及软件定义无线电测试台内的实验验证。 初步结果开发了用于频谱感知的主要马尔可夫模型和最佳序列检测算法，这些算法建立在众所周知的维特比和前向-后向算法的基础上，并暴露了由于常用能量检测器的主要失配而导致的基本限制。 通道编码社区与基于网格和图形的算法的连接应该为 DSA 研究人员引入一个相当大的新工具箱。 利用主要用户的马尔可夫过程模型的辅助接入协议同样表现出主要干扰和辅助吞吐量之间改进的性能权衡。 行业和监管机构的合作者将随时了解研究结果，旨在影响国家和国际层面的 DSA 技术和政策制定。