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Novel Direction-of-Arrival-Based Localization in Massive DECT-2020 5G NR Networks

Research output: Contribution to journalArticleScientificpeer-review

6 Citations (Scopus)
16 Downloads (Pure)

Abstract

This research investigates an affordable, energy- efficient Direction-of-Arrival (DOA)-based localization solution for Digital Enhanced Cordless Telecommunications (DECT) 2020 New Radio (NR), a new standard lacking a native position- ing feature. This standard enables Massive Internet of Things (IoT) networks, a vast 5G network interconnecting an unparal- leled number of low-cost and battery-operated smart sensors. However, integrating DOA localization into such networks is challenging due to cost constraints and power limitations. We propose a potentially cost-effective solution using a single Radio- Frequency (RF) chain for uniform L-shaped antenna arrays. Each antenna takes turns sampling the Orthogonal Frequency Division Multiplexing (OFDM) signal via an RF switch, enabled by time-dividing the OFDM signal into sample and switch slots. Further, we introduce a novel DOA method optimized for single Line-of-Sight (LOS) OFDM signals and array sequential sam- pling. This method leverages the dual shift-invariant properties of L-shaped antenna arrays and the array frequency response to estimate azimuth and elevation angles. Experiments in an indoor environment reveal that at a Signal-to-Noise Ratio (SNR) of 15 dB, over 50% of data achieve sub-degree angular accuracy, increasing to 75% at 20 dB. Thus, over 50% of position estimations fall below the sub-meter error level at 15 dB SNR, rising to nearly 75% at 25 dB SNR. Our findings also indicate that halving the slot rate by proportionately reducing active subcarriers does not compromise accuracy. Experiments on the nRF52480 system-on-chip show the new DOA method is both fast and energy-efficient, taking only 0.76 – 2.26 ms and consuming 5.08 – 15.1 nWh.
Original languageEnglish
Pages (from-to)2690-2712
JournalIEEE Internet of Things Journal
Volume12
Issue number3
Early online date2024
DOIs
Publication statusPublished - 2025
Publication typeA1 Journal article-refereed

Keywords

  • DoA
  • 5G
  • Indoor
  • Positioning
  • massive IoT
  • OFDM
  • DECT
  • 5G-NR

Publication forum classification

  • Publication forum level 2

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