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An Eigenvalue Decomposition-Based Method for In-Service Testing of Wireless Communications Systems

机译:基于特征值分解的无线通信系统在役测试方法

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摘要

Reliably measuring the relevant parameters (like channel power, occupied bandwidth, and carrier frequency) characterizing the signals involved in wireless communications systems turns out to be the key for their in-service testing at a physical layer. This task, however, would not succeed whenever other signals, generated by different wireless systems, interfere with the useful one both in the time and frequency domains. To overcome this limitation, the authors have recently assessed the suitability of eigenvalue decomposition-based algorithms in accurately estimating the power spectrum of a given number of signals that overlap in the time domain and occupy, fully or partially, the same frequency band. Starting from the promising outcomes of the cited algorithms and taking advantage of some nice features of information theoretical criteria, a new measurement method is designed and implemented hereinafter. Designed directly for the in-service physical layer testing of wireless communications systems, the method allows a blind separation of the power spectrum of the useful signal from those of the interfering ones. The evaluation of the desired parameters of the useful signal as well as the frequency-domain characterization of the interfering ones is thus possible, whatever the number of involved signals. The results obtained in a number of laboratory experiments under different in-channel interference conditions show the reliability and efficacy of the method also in the presence of severe in-channel interference.
机译:可靠地测量表征无线通信系统所涉及信号的相关参数(如信道功率,占用的带宽和载波频率),是对其进行物理层服务测试的关键。但是,每当由不同无线系统生成的其他信号在时域和频域中都干扰有用信号时,该任务就不会成功。为了克服此限制,作者最近评估了基于特征值分解的算法在准确估计时域内重叠且完全或部分占据相同频段的给定数量信号功率谱的适用性。从所引用算法的有希望的结果开始,并利用信息理论标准的一些出色功能,在下文中设计并实现了一种新的测量方法。该方法直接为无线通信系统的服务中物理层测试而设计,可以将有用信号的功率谱与干扰信号的功率谱进行盲分离。因此,无论所涉及信号的数量如何,都可以对有用信号的所需参数进行评估以及对干扰信号进行频域表征。在不同的信道内干扰条件下,通过许多实验室实验获得的结果表明,即使在严重的信道内干扰下,该方法的可靠性和有效性也是如此。

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