Dynamic Spectrum Sharing (DSS) allows the transmission of 5G services on existing 4G LTE networks to deploy 5G networks rapidly. It is a straightforward solution requiring only software updates, thus enabling operators to initiate nationwide coverage with minimal expenses. According to the IEC 62232 standard, measurement of human exposure to electromagnetic fields (EMFs) produced by a DSS system can be accomplished by a vector spectrum analyzer (VSA) or a method referred to as Maximum Power Extrapolation (MPE). The vector evaluation entails measuring the broadcast channel of the 5G or LTE technology while assuming that both broadcast and traffic channels are transmitted on the same beam and employing a suitable extrapolation method. Instead, the objective of the MPE procedure is to estimate the potential maximum field level at the measurement point. Both measurement methodologies rely on the knowledge of the implemented system. In this paper, we introduce an experimental study to evaluate the influence of these methodologies in a complex scenario like DSS, where multiple technologies operate within the same bandwidth.
Smart mobility is one of the major application domains of smart cities. It has become increasingly important for the daily management of cities. In this context, smart mobility can help to improve the well-being of citizens through the provision of an efficient mobility system and adequate services. Never-theless, although extensive research on practical cases of smart mobility, pursuing sustainability goals requires to investigate the components of smart mobility and the technical requirements of smart mobility systems to promote their integration. Based on this premise, the SAMOTHRACE project aims to design and validate a holistic smart mobility framework through a multidisciplinary approach. In this regard, this paper provides a project overview with some hints on research investigation directions. Specifically, the four research strands will be overviewed concerning (i) in-vehicle communications, (ii) transport models for the implementation of digital twin, (iii) collaborative machine learning solutions for vehicular scenarios and (iv) models for the placement of virtual functions inside the vehicles. The most challenging issue within SAMOTHRACE project related to this smart mobility area concerns the model implementation and related procedures and their integration in a comprehensive research framework. This paper lays the basis for future research developments to help address the project in a more holistic way, fostering smart mobility within cities.
The investigations examined the applicability of radiofrequency (RF) electromagnetic field (EMF) data loggers (DL), readily available on the market, for assessing worker exposure to the strong EMF (i.e. near its sources) in the microenvironment where strong and complex (in the frequency domain) exposure may exist - at frequencies within the DL's declared measurement frequency band and outside of it (outof-band frequency), e.g. exposure to RF and also 50 Hz (out-ofband) EMF. The results of laboratory tests and field studies show that, based on: (i) the real RF-DL metrological parameters (including its out-of-band sensitivity) and (ii) the frequency pattern of EMF in a microenvironment under question, as anticipated from previous tests, a possible false detection that it is a highly RF-exposed environment may be reinterpreted into the relevant evaluating of exposure to the out-of-band frequency EMF component. Using the approach of three-step exposure evaluation (including: (1) laboratory tests on the out-of-band sensitivity of available RF-DL; (2) environmental tests of real frequency pattern of exposure in the microenvironment under question; (3) expert-assisted interpretation of the results of RF-DL measurements), may technically allow the extension of the frequency range of workers' EMF exposure (beyond measurement frequency ranges declared for DLs available on the market), which may be (quasi)autonomously monitored in a real working environment with respect to its timing and level.
There is clear evidence indicating that the standardized Sensing-Based Semi-Persistent Scheduling scheme in Out-of-coverage possesses specific vulnerabilities. This unsatisfactory performance lies in the absence of coordination in channel scheduling and transmission time. Specifically, the determination to re-assign a resource after the reservation period expires is currently based on a random selection process, without consideration of the actual interference encountered by the utilized resources. In this study, a novel scheme is proposed to markedly improve the random selection method for vehicle positioning.
Over the past decades, the advancement of lab-on-a-chip (LoC) technology and its utilization in biochemical and biomedical analysis has paved the way for the development of portable and on-site detection devices known as point-of-care (PoC) detection systems. These systems are characterized by their affordability, simplicity, and ability to provide rapid sample-to-answer results accessible to non-technical operators. In this context, we focus on highlighting the advantages of integrating ring resonator-based biosensors into PoC devices, so we analyse four different configurations of the aforementioned device in silicon-on-insulator (SOI) technology, comparing their performances in detecting changes in the refractive index of the top cladding. All rings are fabricated with a small ring radius in order to minimize the footprint and the integration in a future PoC system.
