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RSSI-based localisation algorithms using spatial diversity in wireless sensor networks

机译:无线传感器网络中使用空间分集的基于RSSI的定位算法

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Many localisation algorithms in wireless sensor networks (WSNs) are based on received signal strength indication (RSSI). Although these methods present some advantages in terms of complexity and energy consumption, RSSI values especially in indoor environments, are very unstable due to fading. In this paper, we propose a comparative study of RSSI-based localisation algorithms using spatial diversity in WSNs. We consider different kinds of single/multiple antenna systems: single input single output (SISO) system, single input multiple output (SIMO) system, multiple input single output (MISO) system and multiple input multiple output (MIMO) system. We focus on the well known trilateration and multilateration localisation algorithms. Three diversity combining techniques at the receiver are used: maximal ratio combining (MRC), equal gain combining (EGC) and selection combining (SC). The obtained results show that using multiple antennas at both the transmitter and receiver sides present better performance than using multiple antennas at only one side. We also conclude that MRC diversity combining technique outperforms EGC that as well outperforms SC.
机译:无线传感器网络(WSN)中的许多定位算法都基于接收信号强度指示(RSSI)。尽管这些方法在复杂性和能耗方面都具有一些优势,但是RSSI值(尤其是在室内环境中)由于衰落而非常不稳定。在本文中,我们提出了一种在无线传感器网络中使用空间分集的基于RSSI的定位算法的比较研究。我们考虑不同种类的单/多天线系统:单输入单输出(SISO)系统,单输入多输出(SIMO)系统,多输入单输出(MISO)系统和多输入多输出(MIMO)系统。我们专注于众所周知的三边测量和多边定位算法。在接收机处使用三种分集组合技术:最大比率组合(MRC),等增益组合(EGC)和选择组合(SC)。获得的结果表明,与仅在一侧使用多个天线相比,在发送器和接收器两侧都使用多个天线表现出更好的性能。我们还得出结论,MRC分集组合技术胜过EGC,胜过SC。

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