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Detecting Primary Signals Using Time and Space Model

机译:使用时空模型检测主要信号

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The advantage of using cognitive radio technology is its ability to adapt and behave to the needs of the application. The adaptability to the application leads cognitive radios with the potential for creating next generation cognitive wireless network. In dynamic spectrum allocation problem, the cognitive radio technology is used to detect the presence of primary user signal so that spectrum will be efficiently utilized by cognitive users (secondary users). To detect the presence of primary user, cognitive radio requires the data related to history of primary signal including time, signal strength (signal will be detected above certain threshold) through detection techniques (energy detectors, matched filter, feature detection, etc.), and finally analyze this data to detect the signal without failure. In this research, a stochastic model is used to detect the primary signal at a given time and space (primary signal decodable area or domain). The proposed time-space model uses Drake's equation to improve the detection of primary signal.
机译:使用认知无线电技术的优势是其能够适应应用程序并满足应用程序需求的能力。对应用程序的适应性使认知无线电具有创建下一代认知无线网络的潜力。在动态频谱分配问题中,认知无线电技术用于检测主要用户信号的存在,以便认知用户(次要用户)可以有效利用频谱。为了检测主要用户的存在,认知无线电需要与主要信号的历史记录相关的数据,包括时间,信号强度(信号将在一定阈值以上检测到),这要通过检测技术(能量检测器,匹配滤波器,特征检测等)进行,最后分析这些数据以检测信号是否正常。在这项研究中,使用随机模型检测给定时间和空间(原始信号可解码区域或域)上的原始信号。所提出的时空模型使用Drake方程来改善对原始信号的检测。

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