This paper proposes a spectrum sensing algorithm from one-bit measurements in a cognitive radio sensor network. A likelihood ratio test (LRT) for the one-bit spectrum sensing problem is derived. Different from the one-bit spectrum sensing research work in the literature, the signal is assumed to be a discrete random correlated Gaussian process, where the correlation is only available within immediate successive samples of the received signal. The employed model facilitates the design of a powerful detection criteria with measurable analytical performance. One-bit spectrum sensing criterion is derived for one sensor which is then generalized to multiple sensors. Performance of the detector is analyzed by obtaining closed-form formulas for the probability of false alarm and the probability of detection. The proposed one-bit LRT detector exhibits comparable performance to that of non-one-bit detectors (i.e., quadratic and energy detectors) with the lower computational complexity. Simulation results corroborate the theoretical findings and confirm the efficacy of the proposed detector in the context of highly correlated signals.

中文翻译：

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认知无线电传感器网络中的一位频谱感知

本文提出了一种基于认知无线电传感器网络中的一位测量值的频谱感知算法。导出了一位频谱感知问题的似然比测试 (LRT)。与文献中的一位频谱感知研究工作不同，假设信号是离散随机相关的高斯过程，其中相关性仅在接收信号的直接连续样本内可用。所采用的模型有助于设计具有可测量分析性能的强大检测标准。为一个传感器导出一位频谱感知准则，然后将其推广到多个传感器。通过得到虚警概率和检测概率的闭式公式来分析检测器的性能。所提出的一位 LRT 检测器表现出与非一位检测器（即二次和能量检测器）相当的性能，并且具有较低的计算复杂度。仿真结果证实了理论发现，并证实了所提出的检测器在高度相关信号的背景下的功效。