Abstract
This paper addresses the use of channel state information (CSI) for Long Term Evolution (LTE) signal fingerprinting localization. In particular, the paper proposes a novel CSI-based signal fingerprinting approach, where fingerprints are descriptors of the “shape” of the channel frequency response (CFR) calculated on CSI vectors, rather than direct CSI vectors. Experiments have been carried out to prove the feasibility and the effectiveness of the proposed method and to study the impact on the localization performance of (i) the bandwidth of the available LTE signal and (ii) the availability of more LTE signals transmitted by different eNodeB (cell diversity). Comparisons with other signal fingerprinting approaches, such as the ones based on received signal strength indicator or reference signal received power, clearly show that using LTE CSI, and in particular, descriptors as fingerprints, can bring relevant performance improvement.
Highlights
The range of applications requiring ubiquitous high-accuracy localization is rapidly increasing, and it is well known that the accuracy and availability of the Global Navigation Satellite System (GNSS), which remains the most common positioning technology, drop in indoor environments and urban canyons
6.1 channel state information (CSI) vs Received Signal Strength Indicator (RSSI) vs Reference Signal Received Power (RSRP) in a narrowband scenario First of all, we wonder whether the use of CSI for Long Term Evolution (LTE) signal fingerprinting improves the performance with respect to the use of more classical approaches based on RSSI and RSRP
7 Conclusions This paper investigates the possibility to use the CSI extracted from LTE signals for signal fingerprinting indoor localization
Summary
The range of applications requiring ubiquitous (indoor and outdoor) high-accuracy localization is rapidly increasing, and it is well known that the accuracy and availability of the Global Navigation Satellite System (GNSS), which remains the most common positioning technology, drop in indoor environments and urban canyons. This aspect has motivated extensive work on alternative localization solutions [1], which are based on radio signals that are either transmitted by dedicated sensors or by opportunistic transmitters (e.g., WiFi routers or towers of a cellular system). As a matter of fact, the device can receive the signalling messages of different eNodeBs regardless the specific operator
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