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- W3043310296 endingPage "3933" @default.
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- W3043310296 abstract "Indoor localization based on unsynchronized, low-complexity, passive radio frequency identification (RFID) using the received signal strength indicator (RSSI) has a wide potential for a variety of internet of things (IoTs) applications due to their energy-harvesting capabilities and low complexity. However, conventional RSSI-based algorithms present inaccurate ranging, especially in indoor environments, mainly because of the multipath randomness effect. In this work, we propose RSSI-based localization with low-complexity, passive RFID infrastructure utilizing the potential benefits of large-scale MIMO technology operated in the millimeter-wave band, which offers channel hardening, in order to alleviate the effect of small-scale fading. Particularly, by investigating an indoor environment equipped with extremely simple dielectric resonator (DR) tags, we propose an efficient localization algorithm that enables a smart object equipped with large-scale MIMO exploiting the RSSI measurements obtained from the reference DR tags in order to improve the localization accuracy. In this context, we also derive Cramer–Rao lower bound of the proposed technique. Numerical results evidence the effectiveness of the proposed algorithms considering various arbitrary network topologies, and results are compared with an existing algorithm, where the proposed algorithms not only produce higher localization accuracy but also achieve a greater robustness against inaccuracies in channel modeling." @default.
- W3043310296 created "2020-07-23" @default.
- W3043310296 creator A5027795205 @default.
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- W3043310296 date "2020-07-15" @default.
- W3043310296 modified "2023-09-27" @default.
- W3043310296 title "Indoor Large-Scale MIMO-Based RSSI Localization with Low-Complexity RFID Infrastructure" @default.
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- W3043310296 doi "https://doi.org/10.3390/s20143933" @default.
- W3043310296 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/7412086" @default.
- W3043310296 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/32679709" @default.
- W3043310296 hasPublicationYear "2020" @default.
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