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Single sensor radio scene analysis for packet based radio signals using 2nd and 4th order statistics

机译:使用二阶和四阶统计信息对基于分组的无线电信号进行单传感器无线电场景分析

摘要

We consider a problem of radio frequency (RF) signal analysis where one sensing node observes a frequency band possibly used by multiple packet based radio transmitters. Analysis of the received signal includes two steps. In the first step we use a spectrogram to perform temporal segmentation of the received nonstationary signal. This task may be formulated as a clustering problem. In the second step we compute a certain 2-D slice of the fourth order spectrum for each of the segments found in the first step. These fourth order spectrum slices are arraigned in a three-way array. One aspect of the second step is to use uniqueness properties of the low rank decomposition of the three-way array to recover spectra and associated activity sequences of individual components in the received signal. We derive a numerical algorithm for the low rank decomposition, which computes estimates of the spectra and activity sequences by optimizing certain weighted least squares criterion under application specific constraints. Certain embodiments are illustrated with simulation examples involving signals used in 802.11a/b/g and Bluetooth networks. The disclosed methods and related systems can be used as spectrum analysis tools, providing crucial information needed for achieving efficient utilization of radio spectrum and elimination of mutual interference between the coexisting systems.
机译:我们考虑了一个射频(RF)信号分析问题,其中一个传感节点观察到可能由多个基于分组的无线电发射机使用的频带。接收信号的分析包括两个步骤。第一步,我们使用频谱图对接收到的非平稳信号进行时间分割。该任务可以表述为聚类问题。在第二步中,我们为第一步中发现的每个片段计算四阶光谱的某个二维切片。这些四阶频谱切片以三向阵列的形式进行精调。第二步的一个方面是使用三向阵列的低秩分解的唯一性属性来恢复接收信号中各个成分的光谱和相关的活动序列。我们推导了用于低秩分解的数值算法,该算法通过在特定于应用程序的约束下优化某些加权最小二乘准则来计算光谱和活性序列的估计值。某些实施例用涉及在802.11a / b / g和蓝牙网络中使用的信号的仿真示例进行说明。所公开的方法和相关系统可以用作频谱分析工具,提供实现无线电频谱的有效利用和消除共存系统之间的相互干扰所需的关键信息。

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