Fondazione "Ugo Bordoni"

The increasing complexity of smart grid communication networks, driven by the integration of distributed energy resources and massive IoT sensor deployments, demands highly resilient and adaptive communication strategies. This paper proposes two high-resiliency management functions for 5G-enabled energy monitoring networks: an adaptive uplink power control mechanism and an adaptive multi-access traffic steering algorithm. The first dynamically reconfigures the transmission power of user equipment (UE) based on packet delay trends to mitigate interference and improve energy efficiency. The second leverages 3GPP's ATSSS (Access Traffic Steering, Switching, and Splitting) framework to redirect traffic between 5 G and Wi-Fi channels in response to SINR degradation. These functions were implemented and tested in a 5G-LENA based simulation platform. Experimental results show notable improvements in uplink throughput, latency reduction, and overall network stability.

The concept of the Digital Twin has recently gained prominence across various fields of science and technology. In the context of wireless communication systems, a Digital Twin typically refers to a virtual representation of propagation characteristics and channel impulse responses within a given environment. This letter explores the optimization of access point deployment and operation in a cell-free massive MIMO system by leveraging a Digital Twin of a predefined urban area, created using computer-aided ray-tracing techniques. Specifically, we propose methodologies to: (a) determine the optimal placement of access points to maximize coverage; (b) develop a switch-on/switch-off policy for access points based on scheduled users; and (c) for multi-antenna access points, establish a dynamic switch-on/switch-off strategy for RF chains, also based on scheduled users. Numerical results demonstrate the effectiveness of the proposed algorithms, highlighting the potential of Digital Twins as a valuable tool for network planning.

Il Contemporaneo, nato nel 1954, per finire poi declassato a supplemento di Rinascita nel 1965, merita oggi, in quanto principale rivista culturale del PCI, un’analisi approfondita. Se da un lato questa testata era espressione della sezione culturale, dall’altra rappresentava anche un primo tentativo di apertura verso posizioni non strettamente di partito, compreso un pubblico più ampio di quello meramente comunista, ed è proprio per questo che la si ritiene imprescindibile per affrontare un’indagine consapevole degli anni della destalinizzazione. È soprattutto attraverso l’analisi delle immagini e delle illustrazioni pubblicatevi nelle sue prime due serie, a partire da quelle appositamente realizzate da Renzo Vespignani per la prima pagina, che in questa sede si tenterà di delineare il mutamento della poetica realista dall’impianto nazional-popolare, prevalentemente rurale, dei primi anni Cinquanta verso una connotazione sempre più urbana ed esistenziale, anche grazie ad un confronto con le altre testate di partito (da Rinascita, a Vie Nuove a Il Calendario del popolo), dove invece tutto ciò si verificherà molto più lentamente.

Underwater acoustic communication shows unique challenges arising from the complex and dynamic nature of the propagation medium. Traditional approaches to enhance the communication efficiency have often fallen short due to the inherent uncertainties and limitations of underwater channels. Recently, the advances in artificial intelligence offer promising to address these challenges. Specifically, this paper presents an overview of the potential application of reinforcement learning to handle multiple access in underwater acoustic networks exploiting space and time domains. By leveraging reinforcement learning algorithms, autonomous agents can adaptively learn optimal communication strategies in response to changing environmental conditions, improving channel usage and, therefore, data throughput, reliability, and energy efficiency.

Underwater wireless sensor networks are gaining popularity since supporting a broad range of applications, both military and civilian. Wireless acoustics is the most widespread technology adopted in underwater networks, the realization of which must face several challenges induced by channel propagation like signal attenuation, multipath and latency. In order to address such issues, the attention of researchers has recently focused on the concept of cooperative communication and networking, borrowed from terrestrial systems and to be conveniently recast in the underwater scenario. In this paper, we present a comprehensive literature review about cooperative underwater wireless sensor networks, investigating how nodes cooperation can be exploited at the different levels of the network protocol stack. Specifically, we review the diversity techniques employable at the physical layer, error and medium access control link layer protocols, and routing strategies defined at the network layer. We also provide numerical results and performance comparisons among the most widespread approaches. Finally, we present the current and future trends in cooperative underwater networks, considering the use of machine learning algorithms to efficiently manage the different aspects of nodes cooperation.

A procedure to extract rain attenuation from MEO satellite signals is presented in the framework of MEKaP (MEO Ka-band Propagation), a European Space Agency (ESA) funded project. This task involves removing from the received signal the effects induced by the presence of gases along the path, by the change in the distance to the satellite and by the variation of the onboard antenna gain as perceived at the ground station. To this aim, ancillary data are exploited, such as satellite ephemeris, ERA5 products and some basic information on the onboard antenna. Some preliminary examples of the rain attenuation derived in three sites with different climatic conditions (Milan and Rome, Italy; Aveiro, Portugal) are reported, showing the effectiveness of the proposed procedure. Once refined, such methodology will be applied to all the data collected during the experimental campaign (from 1/1/2022 to 31/12/2023) to produce rain attenuation statistics, in turn useful for the evaluation and development of propagation models for NGSO satellite links (e.g. prediction of the rain attenuation complementary cumulative distribution function).

The Alphasat TDP#5 experiment, dedicated to Prof. Aldo Paraboni, is an Italian Space Agency (ASI) science experiment to investigate radio propagation channel in the Ka and Q bands. Sapienza University of Rome, in collaboration with the Higher Institute of Communications and Information Technology (ISCTI) and the Ugo Bordoni Foundation (FUB), has joined the experiment with two receivers, one for each frequency, installed at the Ministry of Business and Made in Italy (MIMIT) in Rome. In this paper, we present a methodology for the retrieval of the excess attenuation and tropospheric scintillation from the Alphasat received beacon signal at Ka and Q band. Scintillation amplitude results in clearair condition acquired over three months are compared with the ITU-R model. Experiment characteristics and data processing details are also presented.

The exponential growth and complexity of geospatial data necessitate innovative management strategies to address the increasing computational demands of Geographical Information System (GIS) services. GIS is connected to the social context, and its use as a decision-support tool is gaining broader acceptance with the need to ensure high Quality of Service (QoS). While cloud computing offers new capabilities for GIS, the physical distance between cloud infrastructure and end-users often leads to high network latency, compromising QoS. Multi-Access Edge Computing (MEC) emerges as a promising solution to limit latency and enhance system performance, particularly for real-time and multi-device applications. However, integrating GIS services into edge-cloud architectures presents significant challenges in terms of task scheduling and service placement. This letter proposes a queueing theory-based model designed to optimize the performance of GIS workloads within edge-cloud architectures. The model, based on a closed Jackson network, is designed to assist in the efficient design and deployment of edge systems that meet QoS and Service Level Agreement (SLA) requirements. The proposed framework is validated through a real-world case study, with performance metrics such as throughput and response time evaluated to ensure optimal system sizing and performance. The results underscore the potential of this approach for designing scalable and efficient edge-cloud architectures tailored to geospatial services.

The paper presents the results of an experimental measurement campaign to verify 2G and 3G mobile networks voice quality in the refarming and switch-off transition phase towards migration to 4G/5G technologies. Measurements have been performed on the whole Italian territory including main cities, suburban areas and extra-urban scenarios (e.g., highways). The results illustrated in this paper are focused on the probability of success in making 2G/3G voice calls through the analysis of appropriate indicators as a function of different parameters such as speed mobility, environment scenarios. Data from different operators are aggregated at national level and a comparison of 4 different campaigns performed from 2019 to 2022 is presented.

Underwater acoustic communications are limited by the following channel impairments: time variability, narrow bandwidth, multipath, frequency selective fading and the Doppler effect. Orthogonal Frequency Division Modulation (OFDM) is recognized as an effective solution to such impairments, especially when optimally designed according to the propagation conditions. On the other hand, OFDM implementation requires accurate channel knowledge atboth transmitter and receiver sides. Long propagation delay may lead to outdated channel information. In this work, we present an adaptive OFDM scheme where channel state information is predicted through a Kalman-like filter so as to optimize communication parameters, including the cyclic prefix length. This mechanism aims to mitigate the variability of channel delay spread. This is cast in a protocol where channel estimation/prediction are jointly considered, so as to allow efficiency. The performance obtained through extensive simulations using real channels and interference show the effectiveness of the proposed scheme, both in terms of rate and reliability, at the expense of an increasing complexity. However, this solution is significantly preferable to the conventional mechanism, where channel estimation is performed only at the receiver, with channel coefficients sent back to the transmit node by means of frequent overhead signaling.