Indoor Large-Scale MIMO-Based RSSI Localization with Low-Complexity RFID Infrastructure

Sensors
Mohammed El-AbsiThomas Kaiser

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 consideri...Continue Reading

References

Jun 16, 2018·EURASIP Journal on Advances in Signal Processing·Nenad VukmirovićMiljko Erić

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Methods Mentioned

BETA
chip

Software Mentioned

Ray
CST
CST Microwave Studio )
LANDMARC
- Tracer
Wireless InSite ( WI

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