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Maximum-Likelihood Detection for Energy-Efficient Timing Acquisition in NB-IoT

机译:NB-IoT中节能定时采集的最大似然检测

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Initial timing acquisition in narrow-band IoT (NB- IoT) devices is done by detecting a periodically transmitted known sequence. The detection has to be done at lowest possible latency, because the RF- transceiver, which dominates downlink power consumption of an NB-IoT modem, has to be turned on throughout this time. Auto-correlation detectors show low computational complexity from a signal processing point of view at the price of a higher detection latency. In contrast a maximum likelihood cross-correlation detector achieves low latency at a higher complexity as shown in this paper. We present a hardware implementation of the maximum likelihood cross-correlation detection. The detector achieves an average detection latency which is a factor of two below that of an auto- correlation method and is able to reduce the required energy per timing acquisition by up to 34%.
机译:窄带物联网(NB-IoT)设备中的初始时序获取是通过检测定期发送的已知序列来完成的。必须在尽可能低的延迟下进行检测,因为在整个这段时间内必须打开NB-IoT调制解调器的下行链路功耗占主导的RF收发器。从信号处理的角度来看,自相关检测器显示出较低的计算复杂度,但代价是检测延迟更高。相反,如本文所示,最大似然互相关检测器以较高的复杂度实现了低延迟。我们提出了最大似然互相关检测的硬件实现。该检测器获得的平均检测等待时间比自动相关方法的平均检测等待时间低两倍,并且能够将每次定时采集所需的能量减少多达34%。

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