CSI-based fingerprinting for indoor localization using LTE Signals

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

LTE Signal Fingerprinting Device-Free Passive Localization in Changing Environments

This paper proposes a fingerprinting-based device Free Passive localization system based on the use of the LTE signal and it is robust to environment changes. The proposed methodology uses as fingerprints descriptors calculated on the CSI vectors rather than directly CSI vectors. The paper shows the performance of the proposed methods also assuming that the monitored environment might be different from the one characterized during the training phase as some equipment may be moved. Moreover, the paper compares the proposed method with signal fingerprinting approaches based on RSSI or direct CSI vectors. Experimental results, which consider one single LTE receiver in the monitored room, show the effectiveness of the proposed solution

End-stage renal disease is a risk factor for complex laparoscopic cholecystectomy in patients waiting for renal transplantation

INTRODUCTION: : To date, there are no studies investigating whether laparoscopic cholecystectomy (LC) is technically more complex in patients waiting for kidney transplant. The aim of this study is to create a user-friendly score to identify high-risk cases for complex LC integrating end-stage renal disease (ESRD). MATERIALS AND METHODS: We retrospectively analysed 321 patients undergoing LC during the period 2014-2016. Two groups were compared: ESRD group (n = 25) versus control group (n = 296). Concerning statistical analysis, continuous variables were compared using Kruskal-Wallis' test, dummy variables with Chi-square test or Fisher's exact test when appropriate. A multivariable logistic regression analysis was performed to identify risk factors for complex LC. A backward conditional method was used to design the final model. RESULTS: : Seventy out of 321 (21.8%) cases were considered as complex, with a higher prevalence in the ESRD group (32.0 vs. 20.9%; P = 0.2). Using a multivariable logistic regression analysis, we formulated a score based on the independent risk factors for complex LC: 4×(previous cholecystitis) +5 × (previous ESRD) +1 × (age per decade) +2 × (previous open abdominal surgery). High-risk cases (score ≥ 10) were more commonly reported in the ESRD group (72.0 vs. 24.7%; P < 0.0001). CONCLUSION: : Although several scores investigating the risk for complex LC have been proposed, none of them has focused on ESRD. This is the first series demonstrating that ESRD is an independent risk factor for technical complexity in LC. We developed a score to offer surgeons an extra tool for pre-operative evaluation of patients requiring LC