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arXiv 1807.06112eess.SPcs.ITmath.IT
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F复合衰落信道下基于熵和能量检测的频谱感知

Entropy and Energy Detection-based Spectrum Sensing over F Composite Fading Channels

Seong Ki Yoo, Simon L. Cotton, Paschalis C. Sofotasios, Sami Muhaidat, Osamah S. Badarneh, George K. Karagiannidis

摘要:

在本文中,我们研究了基于能量检测的频谱感知在F复合衰落信道的性能。为此,首先推导出平均检测概率的解析表达式。然后,这个表达式扩展到占协作频谱感知,平方律选择分集接收和噪声功率的不确定性。分析了不同平均信噪比、噪声功率不确定性、时间带宽积、多径衰落、阴影、分集分支数和协作用户数条件下的接收机工作特性。研究表明,能量检测性能对多径衰落的严重程度和阴影量很敏感,因此即使这些物理现象中的任何一个的微小变化也会显着影响检测概率。作为评价检测性能的一个品质因数,ROC曲线下的面积(AUC)推导并评估不同的多径衰落和阴影条件。香农熵和交叉熵的封闭形式的表达式也制定和评估不同的平均信噪比,多径衰落和阴影条件。然后检查香农熵和ROC/AUC之间的关系,其中发现编码信号所需的平均比特数变小(即,低香农熵)。通过比较Rayleigh衰落和Nakagami-m衰落的交叉熵,强调了复合衰落与传统小尺度衰落的区别。通过与一些模拟结果的仔细比较,提供了一个验证的分析结果。

英文摘要:

In this paper, we investigate the performance of energy detection-based spectrum sensing over F composite fading channels. To this end, an analytical expression for the average detection probability is firstly derived. This expression is then extended to account for collaborative spectrum sensing, square-law selection diversity reception and noise power uncertainty. The corresponding receiver operating characteristics (ROC) are analyzed for different conditions of the average signal-to-noise ratio (SNR), noise power uncertainty, time-bandwidth product, multipath fading, shadowing, number of diversity branches and number of collaborating users. It is shown that the energy detection performance is sensitive to the severity of the multipath fading and amount of shadowing, whereby even small variations in either of these physical phenomena can significantly impact the detection probability. As a figure of merit to evaluate the detection performance, the area under the ROC curve (AUC) is derived and evaluated for different multipath fading and shadowing conditions. Closed-form expressions for the Shannon entropy and cross entropy are also formulated and assessed for different average SNR, multipath fading and shadowing conditions. Then the relationship between the Shannon entropy and ROC/AUC is examined where it is found that the average number of bits required for encoding a signal becomes small (i.e., low Shannon entropy) when the detection probability is high or when the AUC is large. The difference between composite and traditional small-scale fading is emphasized by comparing the cross entropy for Rayleigh and Nakagami-m fading. A validation of the analytical results is provided through a careful comparison with the results of some simulations.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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