Maximum-Likelihood Detection for Energy-Efficient Timing Acquisition in NB-IoT
Autor: | Samuel Willi, Harald Kroll, Matthias Korb, Qiuting Huang, Benjamin Weber |
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Jazyk: | angličtina |
Rok vydání: | 2016 |
Předmět: |
Networking and Internet Architecture (cs.NI)
FOS: Computer and information sciences Signal processing Computer science Detector Real-time computing 020206 networking & telecommunications 02 engineering and technology Computer Science - Networking and Internet Architecture Telecommunications link 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Transceiver Energy (signal processing) Efficient energy use |
Zdroj: | WCNC Workshops |
Popis: | 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%. 5 pages, 6 figures, submitted to M2M Communications and the Internet of Things workshop at WCNC 2017 |
Databáze: | OpenAIRE |
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