Primary channel statistics have recently gained increasing attention due to its remarkable role in the performance improvement of Dynamic Spectrum Access (DSA)/Cognitive Radio (CR) systems. These statistics can be calculated from the outcomes of spectrum sensing, which is the well-known method used to identify the available instantaneous opportunities in the spectrum. Computing statistical information from spectrum sensing, however, may sometimes be unreliable due to the fact that spectrum sensing is imperfect in the real world and errors are likely to occur in the sensing decisions. In this context, this work provides a detailed analysis of a broad range of primary channel statistics under Imperfect Spectrum Sensing (ISS) and finds a set of closed-form expressions for the calculated statistics under ISS as a function of the original primary channel statistics, probability of error, and the employed sensing period. In addition, the obtained mathematical expressions are employed to find and propose novel estimators for the primary channel statistics, which outperform the existing estimators in the literature and can provide accurate estimations of the original statistics even under high probability of error of spectrum sensing. The correctness of the obtained analytical expressions and the accuracy of the proposed estimators are corroborated with both simulation and experimental results.

中文翻译：

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基于不完美频谱感知的认知无线电主信道活动统计估计

由于其在动态频谱接入 (DSA)/认知无线电 (CR) 系统的性能改进中的显着作用，主信道统计最近越来越受到关注。这些统计数据可以从频谱感知的结果中计算出来，这是用于识别频谱中可用瞬时机会的众所周知的方法。然而，由于频谱感测在现实世界中并不完善并且感测决策中可能发生错误，因此从频谱感测计算统计信息有时可能不可靠。在这种情况下，这项工作提供了对不完美频谱感知 (ISS) 下广泛的主要信道统计数据的详细分析，并为 ISS 下的计算统计数据找到了一组封闭形式的表达式，作为原始主要信道统计数据、错误概率、和使用的感应周期。此外，利用获得的数学表达式来寻找和提出新的主信道统计估计量，其性能优于文献中现有的估计量，即使在频谱感知错误概率较高的情况下也能提供对原始统计量的准确估计。得到的解析表达式的正确性和所提出的估计量的准确性得到了模拟和实验结果的证实。和使用的感应周期。此外，利用获得的数学表达式来寻找和提出新的主信道统计估计量，其性能优于文献中现有的估计量，即使在频谱感知错误概率很高的情况下也能提供对原始统计量的准确估计。得到的解析表达式的正确性和所提出的估计量的准确性得到了模拟和实验结果的证实。和使用的感应周期。此外，利用获得的数学表达式来寻找和提出新的主信道统计估计量，其性能优于文献中现有的估计量，即使在频谱感知错误概率较高的情况下也能提供对原始统计量的准确估计。得到的解析表达式的正确性和所提出的估计量的准确性得到了模拟和实验结果的证实。