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oapen-20.500.12657-493042021-11-23T14:00:54Z Chapter Where are the Things of the Internet? Precise Time of Arrival Estimation for IoT Positioning Xu, Wen Laas, Tobias Dammann, Armin Cramér-Rao lower bound, Ziv-Zakai lower bound, time (difference) of arrival, radio-based positioning, cooperative positioning bic Book Industry Communication::T Technology, engineering, agriculture::TJ Electronics & communications engineering::TJK Communications engineering / telecommunications::TJKW WAP (wireless) technology The question how a 5G communication system will look like has been addressed intensely in numerous research projects and in standardization bodies. In the massively connected world of the “Internet of Things” (IoT), it is getting more and more important to be aware of where all these “things” are located. Mobile radio-based technologies envisaged for a 5G system will play an essential role in providing high-accuracy positioning of the “things.” In this work, we will first address the fundamental Cramér-Rao lower bound (CRLB) of time of arrival (TOA) estimation in an orthogonal frequency-division multiplexing (OFDM)-based system (such as 4G and 5G) using the pilots. The achievable performance is compared with the 3GPP LTE and potential future 5G requirements. The Ziv-Zakai lower bound (ZZLB) is also considered for TOA estimation, as it is tighter than the CRLB for medium to low signal-to-noise ratios (SNRs). We show how to optimize the waveform in order to reduce the TOA estimation error. Then, we describe some practical low-complexity maximum likelihood (ML) methods for TOA estimation with enhanced first-arriving path detection. Simulation results show that such adaptive ML methods can in some cases (e.g., line of sight) achieve a performance close to the CRLB. Finally, we will briefly discuss cooperation-based positioning, which will become increasingly important for massively connected IoT. 2021-06-02T10:11:47Z 2021-06-02T10:11:47Z 2019 chapter ONIX_20210602_10.5772/intechopen.78063_418 https://library.oapen.org/handle/20.500.12657/49304 eng application/pdf n/a 62865.pdf InTechOpen 10.5772/intechopen.78063 10.5772/intechopen.78063 09f6769d-48ed-467d-b150-4cf2680656a1 H2020-ICT-2016-2 761510 open access
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The question how a 5G communication system will look like has been addressed intensely in numerous research projects and in standardization bodies. In the massively connected world of the “Internet of Things” (IoT), it is getting more and more important to be aware of where all these “things” are located. Mobile radio-based technologies envisaged for a 5G system will play an essential role in providing high-accuracy positioning of the “things.” In this work, we will first address the fundamental Cramér-Rao lower bound (CRLB) of time of arrival (TOA) estimation in an orthogonal frequency-division multiplexing (OFDM)-based system (such as 4G and 5G) using the pilots. The achievable performance is compared with the 3GPP LTE and potential future 5G requirements. The Ziv-Zakai lower bound (ZZLB) is also considered for TOA estimation, as it is tighter than the CRLB for medium to low signal-to-noise ratios (SNRs). We show how to optimize the waveform in order to reduce the TOA estimation error. Then, we describe some practical low-complexity maximum likelihood (ML) methods for TOA estimation with enhanced first-arriving path detection. Simulation results show that such adaptive ML methods can in some cases (e.g., line of sight) achieve a performance close to the CRLB. Finally, we will briefly discuss cooperation-based positioning, which will become increasingly important for massively connected IoT.
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