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

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:
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
项目状态:
已结题
起止时间:
2011-09-01 至 2015-08-31

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中文摘要
翻译
FCC发布了其国家宽带计划,理由是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正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”无线电在未得到充分利用的“空白空间”中传输,前提是它们对“主要”无线电造成的干扰最小。在不同的时间、频率和位置都观察到了大量的空白,高达85%。然而,即使在电视频段,分布式频谱感知和集中式发射源数据库这两种主要的解决方案还没有解决空白空间利用不明显的挑战。本项目专注于一种基于频谱感知的综合DSA方法,该方法在反馈环路中结合了以下内容:一次和二次传输的新颖建模;基于这些模型的最优频谱感知算法和二次接入协议的设计;以及在软件定义的无线电试验台上的实验验证。初步结果发展了频谱感知的主要马尔可夫模型和最优序列检测算法,它们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造成的基本限制。从信道编码社区到基于网格和基于图形的算法的连接应该会为DSA研究人员带来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次要接入协议类似地在主要干扰和次要吞吐量之间表现出改进的性能折衷。行业和监管机构的合作者将被告知研究结果,目的是影响国家和国际层面的DSA技术和政策发展。
英文摘要
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.
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