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nROAR: Near Real-Time Opportunistic Spectrum Access and Management in Cloud-Based Database-Driven Cognitive Radio Networks

机译:nROAR:基于云的数据库驱动的认知无线电网络中的近实时机会频谱访问和管理

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摘要

Cognitive radio network with spectrum sensing to find idle channels and access them opportunistically is regarded as an emerging technology to deal with spectrum scarcity caused by exclusive licensing to primary systems. Simulation-based studies loose practical relevance due to assumptions and usage of simple models for defining transmission regions, multi-path propagation, and traffic intensity. In this paper, we present an experimental study for near real-time spectrum sensing and opportunistic spectrum access in database-driven cognitive radio networks (nROAR) using national instrument USRP devices in wide-band regime. We present numerical results for evaluating spectrum sensing using adaptive threshold-based joint energy and bandwidth detection. Furthermore, we evaluate the dynamic spectrum access using database-driven quorum-based rendezvous for opportunistic access for admitted unlicensed secondary users in diverse wireless bands. The proposed nROAR architecture addresses challenges related to providing spectrum access which require fast processing of a large number of spectrum-sensing measurements across diverse wireless bands, geography, and time.
机译:具有频谱感测功能的认知无线电网络可以找到空闲信道并进行机会性访问,这被认为是一种新兴技术,可以解决由于对主系统的独家许可而导致的频谱短缺问题。基于仿真的研究由于假设和使用简单模型来定义传输区域,多径传播和交通强度而失去了实际意义。在本文中,我们针对宽带驱动中使用国家仪器USRP设备的数据库驱动的认知无线电网络(nROAR)中的近实时频谱感测和机会频谱访问进行了一项实验研究。我们提出了使用基于自适应阈值的联合能量和带宽检测评估频谱感知的数值结果。此外,我们使用数据库驱动的基于仲裁的集合点来评估动态频谱访问,以在各种无线频带中为允许的未经许可的二级用户提供机会性访问。拟议的nROAR体系结构解决了与提供频谱访问相关的挑战,这些挑战要求在不同的无线频段,地理位置和时间上快速处理大量频谱感应测量。

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