arXiv subjects

Luca De Nardis

Publications and source records attributed to Luca De Nardis.

10 recordsLinked to original sources

arXiv2026

Improving Outdoor Multi-cell Fingerprinting-based Positioning via Mobile Data Augmentation

Accurate outdoor positioning in cellular networks is hindered by sparse, heterogeneous measurement collections and the high cost of exhaustive site surveys. This paper introduces a lightweight, modular mobile data augmentation framework designed to enhance multi-cell fingerprinting-based positioning using operator-collected minimization of drive test (MDT) records. The proposed approach decouples spatial and radio-feature synthesis: kernel density estimation (KDE) models the empirical spatial distribution to generate geographically coherent synthetic locations, while a k-nearest-neighbor (KNN)-based block produces augmented per-cell radio fingerprints. The architecture is intentionally training-free, interpretable, and suitable for distributed or on-premise operator deployments, supporting privacy-aware workflows. We both validate each augmentation module independently and assess its end-to-end impact on fingerprinting-based positioning using a real-world MDT dataset provided by an Italian mobile network operator across diverse urban and peri-urban scenarios. Results show that the proposed KDE-KNN augmentation consistently improves positioning performance with respect to state-of-the-art approaches, reducing the median positioning error by up to 30% in the most sparsely sampled or structurally complex regions. We also observe region-dependent saturation effects, which emerge most rapidly in scenarios with high user density where the information gain from additional synthetic samples quickly diminishes. Overall, the framework offers a practical, low-complexity path to enhance operator positioning services using existing mobile data traces.

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arXiv2025

Research Directions and Modeling Guidelines for Industrial Internet of Things Applications

The Industrial Internet of Things (IIoT) paradigm has emerged as a transformative force, revolutionizing industrial processes by integrating advanced wireless technologies into traditional procedures to enhance their efficiency. The importance of this paradigm shift has produced a massive, yet heterogeneous, proliferation of scientific contributions. However, these works lack a standardized and cohesive characterization of the IIoT framework coming from different entities, like the 3rd Generation Partnership Project (3GPP) or the 5G Alliance for Connected Industries and Automation (5G-ACIA), resulting in divergent perspectives and potentially hindering interoperability. To bridge this gap, this article offers a unified characterization of (i) the main IIoT application domains, (ii) their respective requirements, (iii) the principal technological gaps existing in the current literature, and, most importantly, (iv) we propose a systematic approach for assessing and addressing the identified research challenges. Therefore, this article serves as a roadmap for future research endeavors, promoting a unified vision of the IIoT paradigm and fostering collaborative efforts to advance the field.

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arXiv2022

Mo3: a Modular Mobility Model for future generation mobile wireless networks

Mobility modeling in 5G and beyond 5G must address typical features such as time-varying correlation between mobility patterns of different nodes, and their variation ranging from macro-mobility (kilometer range) to micro-mobility (sub-meter range). Current models have strong limitations in doing so: the widely used reference-based models, such as the Reference Point Group Mobility (RPGM), lack flexibility and accuracy, while the more sophisticated rule-based (i.e. behavioral) models are complex to set-up and tune. This paper introduces a new rule-based Modular Mobility Model, named Mo3, that provides accuracy and flexibility on par with behavioral models, while preserving the intuitiveness of the reference-based approach, and is based on five rules: 1) Individual Mobility, 2) Correlated Mobility, 3) Collision Avoidance, 4) Obstacle Avoidance and 5) Upper Bounds Enforcement. Mo3 avoids introducing acceleration vectors to define rules, as behavioral models do, and this significantly reduces complexity. Rules are mapped one-to-one onto five modules, that can be independently enabled or replaced. Comparison of time-correlation features obtained with Mo3 vs. reference-based models, and in particular RPGM, in pure micro-mobility and mixed macro-mobility / micro-mobility scenarios, shows that Mo3 and RPGM generate mobility patterns with similar topological properties (intra-group and inter-group distances), but that Mo3 preserves a spatial correlation that is lost in RPGM - at no price in terms of complexity - making it suitable for adoption in 5G and beyond 5G.

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arXiv2021

Lexical Access Model for Italian -- Modeling human speech processing: identification of words in running speech toward lexical access based on the detection of landmarks and other acoustic cues to features

Modelling the process that a listener actuates in deriving the words intended by a speaker requires setting a hypothesis on how lexical items are stored in memory. This work aims at developing a system that imitates humans when identifying words in running speech and, in this way, provide a framework to better understand human speech processing. We build a speech recognizer for Italian based on the principles of Stevens' model of Lexical Access in which words are stored as hierarchical arrangements of distinctive features (Stevens, K. N. (2002). "Toward a model for lexical access based on acoustic landmarks and distinctive features," J. Acoust. Soc. Am., 111(4):1872-1891). Over the past few decades, the Speech Communication Group at the Massachusetts Institute of Technology (MIT) developed a speech recognition system for English based on this approach. Italian will be the first language beyond English to be explored; the extension to another language provides the opportunity to test the hypothesis that words are represented in memory as a set of hierarchically-arranged distinctive features, and reveal which of the underlying mechanisms may have a language-independent nature. This paper also introduces a new Lexical Access corpus, the LaMIT database, created and labeled specifically for this work, that will be provided freely to the speech research community. Future developments will test the hypothesis that specific acoustic discontinuities - called landmarks - that serve as cues to features, are language independent, while other cues may be language-dependent, with powerful implications for understanding how the human brain recognizes speech.

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arXiv2021

Lexical and syntactic gemination in Italian consonants -- Does a geminate Italian consonant consist of a repeated or a strengthened consonant?

Two types of consonant gemination characterize Italian: lexical and syntactic. Italian lexical gemination is contrastive, so that two words may differ by only one geminated consonant. In contrast, syntactic gemination occurs across word boundaries, and affects the initial consonant of a word in specific contexts, such as the presence of a monosyllabic morpheme before the word. This study investigates the acoustic correlates of Italian lexical and syntactic gemination, asking if the correlates for the two types are similar in the case of stop consonants. Results confirmed previous studies showing that duration is a prominent gemination cue, with a lengthened consonant closure and a shortened pre-consonant vowel for both types. Results also revealed the presence, in about 10-12% of instances, of a double stop-release burst, providing strong support for the biphonematic nature of Italian geminated stop consonants. Moreover, the timing of these bursts suggests a different planning process for lexical vs. syntactic geminates. The second burst, when present, is accommodated within the closure interval in syntactic geminates, while lexical geminates are lengthened by the extra burst. This suggests that syntactic gemination occurs during a post-lexical phase of production planning, after timing has already been established.

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arXiv2021

Estimation of the Frequency of Occurrence of Italian Phonemes in Text

The purpose of this project was to derive a reliable estimate of the frequency of occurrence of the 30 phonemes - plus consonant geminated counterparts - of the Italian language, based on four selected written texts. Since no comparable dataset was found in previous literature, the present analysis may serve as a reference in future studies. Four textual sources were considered: Come si fa una tesi di laurea: le materie umanistiche by Umberto Eco, I promessi sposi by Alessandro Manzoni, a recent article in Corriere della Sera (a popular daily Italian newspaper), and In altre parole by Jhumpa Lahiri. The sources were chosen to represent varied genres, subject matter, time periods, and writing styles. Results of the analysis, which also included an analysis of variance, showed that, for all four sources, the frequencies of occurrence reached relatively stable values after about 6,000 phonemes (approx. 1,250 words), varying by <0.025%. Estimated frequencies are provided for each single source and as an average across sources.

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arXiv2020

Consonant gemination in Italian: the affricate and fricative case

Consonant gemination in Italian affricates and fricatives was investigated, completing the overall study of gemination of Italian consonants. Results of the analysis of other consonant categories, i.e. stops, nasals, and liquids, showed that closure duration for stops and consonant duration for nasals and liquids, form the most salient acoustic cues to gemination. Frequency and energy domain parameters were not significantly affected by gemination in a systematic way for all consonant classes. Results on fricatives and affricates confirmed the above findings, i.e., that the primary acoustic correlate of gemination is durational in nature and corresponds to a lengthened consonant duration for fricative geminates and a lengthened closure duration for affricate geminates. An inverse correlation between consonant and pre-consonant vowel durations was present for both consonant categories, and also for both singleton and geminate word sets when considered separately. This effect was reinforced for combined sets, confirming the hypothesis that a durational compensation between different phonemes may serve to preserve rhythmical structures. Classification tests of single vs. geminate consonants using the durational acoustic cues as classification parameters confirmed their validity, and highlighted peculiarities of the two consonant classes. In particular, a relatively poor classification performance was observed for affricates, which led to refining the analysis by considering dental vs. non-dental affricates in two different sets. Results support the hypothesis that dental affricates, in Italian, may not appear in intervocalic position as singletons but only in their geminate form.

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arXiv2020

Consonant gemination in Italian: the nasal and liquid case

All Italian consonants affected by gemination, that is affricates, fricatives, liquids, nasals, and stops, were analyzed within a project named GEMMA that lasted over a span of about 25 years. Results of the analysis on stops, as published in (Esposito, A., and Di Benedetto, M. G. (1999). "Acoustic and Perceptual Study of Gemination in Italian Stops," The Journal of the Acoustical Society of America, ASA, Vol. 30, pp. 175-185) showed that the main acoustic cue to gemination in Italian was closure duration, while frequency and energy domain parameters were not significantly affected by gemination. This paper - the first of a set of two covering all remaining consonants - addresses nasals and liquids; its companion paper addresses affricates and fricatives. Results on nasals and liquids confirm the findings on stops, in particular that the primary acoustic cue to gemination in Italian is durational in nature and corresponds to a lengthened consonant duration. Results also show an inverse correlation between consonant and pre-consonant vowel durations which is, however, also present when considering singleton vs. geminate word sets separately, indicating a sort of duration compensation between these segments to eventually preserve rhythmical structures; this inverse correlation is reinforced when considering singleton and geminate sets combined. Classification tests of singleton vs. geminate consonants show that, for both nasals and liquids, best classification scores are obtained when consonant duration is used as a classification parameter. Although slightly less performing, the ratio between consonant and pre-consonant vowel durations is also a potential good candidate for automatic classification of geminate vs singleton nasals and liquids in Italian.

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arXiv2020

Coverage and Deployment Analysis of Narrowband Internet of Things in the Wild

Narrowband Internet of Things (NB-IoT) is gaining momentum as a promising technology for massive Machine Type Communication (mMTC). Given that its deployment is rapidly progressing worldwide, measurement campaigns and performance analyses are needed to better understand the system and move toward its enhancement. With this aim, this paper presents a large scale measurement campaign and empirical analysis of NB-IoT on operational networks, and discloses valuable insights in terms of deployment strategies and radio coverage performance. The reported results also serve as examples showing the potential usage of the collected dataset, which we make open-source along with a lightweight data visualization platform.

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arXiv2019

ViFi: Virtual Fingerprinting WiFi-based Indoor Positioning via Multi-Wall Multi-Floor Propagation Model

Widespread adoption of indoor positioning systems based on WiFi fingerprinting is at present hindered by the large efforts required for measurements collection during the offline phase. Two approaches were recently proposed to address such issue: crowdsourcing and RSS radiomap prediction, based on either interpolation or propagation channel model fitting from a small set of measurements. RSS prediction promises better positioning accuracy when compared to crowdsourcing, but no systematic analysis of the impact of system parameters on positioning accuracy is available. This paper fills this gap by introducing ViFi, an indoor positioning system that relies on RSS prediction based on Multi-Wall Multi-Floor (MWMF) propagation model to generate a discrete RSS radiomap (virtual fingerprints). Extensive experimental results, obtained in multiple independent testbeds, show that ViFi outperforms virtual fingerprinting systems adopting simpler propagation models in terms of accuracy, and allows a sevenfold reduction in the number of measurements to be collected, while achieving the same accuracy of a traditional fingerprinting system deployed in the same environment. Finally, a set of guidelines for the implementation of ViFi in a generic environment, that saves the effort of collecting additional measurements for system testing and fine tuning, is proposed.

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