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Equal Gain Combining Based Sub-optimum Posterior Noncoherent Fusion Rule for Wireless Sensor Networks

机译:无线传感器网络基于等增益组合的次优后验非相干融合规​​则

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The maximum a-posteriori (MAP) noncoherent fusion rule has been introduced for the best noncoherent detection performance, however, which is prohibitively complex for widely practical applications. In this contribution, a novel noncoherent detector named equal gain combining aided sub-optimum MAP (EGC-SMAP) is employed for the fusion detection in wireless sensor networks (WSNs). Explicate, our proposed EGC-SMAP fusion rule starts the detecting via EGC principle which shrinks the searching range. Then, the final decision is made by MAP fusion rule within the searching range. The novel EGC-SMAP fusion rule has two major advantages compared with the previous work. (1) It allows noncoherent detection, hence, the phase information of carrier is no longer required. As such, it is particularly suitable for WSNs applications with severe resource constraints. (2) This EGC-SMAP fusion rule can be viewed as a combination of EGC and MAP fusion rules, which is capable of achieving various required detection performance as well as computation complexity via justifying the searching range.
机译:为了获得最佳的非相干检测性能,已经引入了最大的后验(MAP)非相干融合规​​则,但是,对于广泛的实际应用而言,这是极其复杂的。在此贡献中,一种名为等增益组合辅助次优MAP(EGC-SMAP)的新型非相干检测器被用于无线传感器网络(WSN)中的融合检测。明确地说,我们提出的EGC-SMAP融合规则通过EGC原理开始检测,从而缩小了搜索范围。然后,根据搜索范围内的MAP融合规则做出最终决定。与以前的工作相比,新颖的EGC-SMAP融合规则具有两个主要优点。 (1)允许非相干检测,因此,不再需要载波的相位信息。因此,它特别适用于资源紧张的WSN应用。 (2)该EGC-SMAP融合规则可以看作是EGC和MAP融合规则的组合,能够通过证明搜索范围的合理性来实现各种所需的检测性能以及计算复杂性。

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