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Using multiple power spectrum measurements to sense signals with partial spectral overlap

机译:使用多个功率谱测量来检测具有部分光谱重叠的信号

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In this work, we study the wideband sensing problem of detecting intermittently transmitting signals that may have partial spectral overlap. We aim to estimate the frequency bands occupied by transmitters using standards with overlapping frequency bands, such as IEEE 802.11, and those without guard bands, such as LTE-Advanced. Multiple power spectrum measurements are used to distinguish the distinct bands. An extreme ray based non-negative matrix factorization algorithm is proposed to identify measurements where a single transmitter is active. Distinct bands are identified in the presence of frequency-selective fading by using a combinatorial search. In addition, we propose a novel algorithm to automatically estimate the noise power spectrum by identifying measurements that do not have significant signal energy. Its ability to learn colored noise and LO leakage in the signal is demonstrated through USRP measurements. The dependence of the proposed algorithm's performance on the medium access control protocol used by the primary users is discussed. MATLAB simulations are used to verify that the proposed algorithm detects the occupied bands more accurately than existing methods. Over the air USRP measurements in the 2.4 GHz ISM band are used to detect the occupied WiFi channels in a university environment.
机译:在这项工作中,我们研究的检测可以具有局部的光谱重叠间断地发送信号宽带感测的问题。我们的目标是估计由使用标准与重叠的频带,诸如IEEE 802.11发射机所占据的频带,而那些没有保护带,如高级LTE。多个功率谱测量用于区分不同的条带。极端射线基于非负矩阵分解算法,以确定测量值,其中单个发射机是活动的。不同的条带是通过使用组合的搜索结果在频率选择性衰落的存在来鉴定。此外,我们提出了一种算法,以通过识别不具有显著信号能量测量自动估计噪声功率谱。它的学习能力有色噪声和信号LO泄漏是通过测量USRP证明。所提出的算法对由所述主要用户所使用的媒体访问控制协议的性能的依赖性进行了讨论。 MATLAB仿真用来验证所提出的算法比现有方法更准确地检测被占领带。在2.4 GHz ISM频段的空中USRP测量被用来检测在大学环境被占领WiFi信道。

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