The design of 5G systems is considered as the next big challenge for the ICT community in the upcoming years. Besides increased bit rate and energy efficiency of the terminals and of the whole system, 5G aims at providing minimal latency to critical communication, seamless integration of IoT nodes and support to massive Machine-to-Machine (M2M) communication, all without degrading the quality of experience for traditional services. Although the general requirements of 5G systems are progressively taking shape, also thanks to the industrial-driven actions promoted by the H2020 framework of the EC, the technological issues raised by such a vision are still quite foggy. Nonetheless, general consensus has been reached upon the importance of few, key approaches and technologies, including massive MIMO, millimeter wave communication, machine learning for self-optimization of network parameters and policies, energy harvesting mechanisms for base stations and devices. While our interests extend over all such topics, currently our research activity is focused on a selected number of relevant challenges, as described below.

As the demand for higher data rates increases, one of the solutions available to operators is to reduce the size of the cell, thus increasing the spectral efficiency by enabling higher frequency reuse, while reducing transmit power. Moreover, the deployment of small cells indoor may help improving the wireless coverage where signal reception from the macro base station may be difficult, and may contribute to offload traffic from the macro cells, when required. Small cells can have different flavors, with low powered femtocells typically used in residential and enterprise deployments, and higher powered picocells used for wider outdoor coverage, or for filling in macro cell coverage holes. The concurrent operation of different classes of base stations is known as Heterogeneous Networks (HetNets). This configuration is foreseen as the next generation of cellular network infrastructure. However, the existence of multiple type of access nodes, such as macro, pico and femto base stations, raises new challenges because of complex interference conditions from node densification and self-deployed access. Our current research activity focuses on the use of context information to optimize the resource utilization in HetNets. We started by studying the handover process that, in a HetNet scenario, becomes particularly challenging due to the high variability of the coverage, transmit power, interference level, and traffic loading of the cells. Current handover policies, which have excellently served in classical cellular networks, reveal all their limits in this new environment, in incurring in outage periods when delaying handover for too long, or ping-pong effect (i.e., quick transitions between cells) when the handover is triggered with much anticipation. To avoid these performance losses, hence, the handover parameters need to be dynamically adapted to the context, i.e., the speed of the mobile users, the signal propagation coefficients for macro and femtocells, the location of the base stations, and so on. We are currently investigating these issues both mathematically, and by using machine-learning based techniques to infer the context parameters from the data available at the mobile user, i.e., its speed and direction, and the power of the beaconing signals transmitted by the base stations. We have also developed a mathematical model that makes it possible to derive the performance of a non-causal optimal handover strategy, which will be used as a benchmarks to assess the performance of the practical schemes we will propose.

As the telecommunication technology continues to evolve rapidly, fueling the growth of service coverage and capacity, new use cases and applications are being identified. Many of these new business areas (e.g., smart metering, in-car satellite navigation, E-health monitoring, smart cities) involve fully-automated communication between devices, without human intervention. This new form of communication is generally referred to as Machine-to-Machine (M2M) Communication, but also as Machine-type Communication (MCT), while the devices that are involved in this type of communication are called Machine-Type Devices (MTD), which include sensors, actuators, RFtags, smartphones, and so on. M2M communication paradigm is expected to play a significant role in future networks, both because the potentially huge number of MTDs that shall be connected to cellular networks and the characteristics of machine-type traffic. Indeed, differently from traditional broadband services, M2M communication is expected to generate, in most cases, sporadic transmissions of short packets. Nonetheless, while the data rate of a single M2M link is extremely low, the potentially huge number of MTDs that shall gain connectivity through a single Base Station will raise a number of issues related to the signaling and control traffic, which may become the bottleneck of the system. As a matter of fact, today’s standard for cellular networks are not designed to support massive MTD access, and will collapse under the weight of signaling traffic. In addition, although transmissions from machine devices are, in many cases, delay tolerant (smart metering, telemetry), there is also an important class of applications that require ultra-low latency (E-health, vehicular communications). Furthermore, most of MTDs are expected to be severely constrained in terms of computational and storage capabilities, and energy capacity. This scenario, hence, raises a number of challenges that need to be addressed in the next future, including: control overhead, energy efficiency, coverage extension, heterogeneous QoS support, robustness to malfunctioning devices, security, and scalability. The biggest challenge is to embed this type of traffic in the overall 5G architecture, so that M2M traffic can coexist with broadband data traffic. In this scenario, we are investigating the problem of managing massive access from a huge number of simple MTDs to a common powerful Base Station, capable of performing advanced reception processes such as multi-packet reception, successive interference cancellation, and so on. We start from a theoretical analysis of the problem, with the aim of finding information-theoretical results that shed light on the best access strategy to be used in this context. Then, we will move forward to define some practical access mechanisms, with the aim of maximizing the number of MTDs that can be served by a single base station, with minimum energy expenditure.

In a nutshell, massive MIMO consists in using large arrays of antenna elements, with many more elements than typically used today, to provide diversity and compensate for path loss, thus making it possible to significantly increase the transmission capacity of the system, and the spectral and energy-efficiency. In addition, it provides many degrees of freedom, which can be exploited by means of beamforming in case the channel state information is available. Issues related to this topic are the current prohibitive cost, in terms of resource consumption, required by channel estimation and feedback, the complex interactions of pilot contamination and interference that Massive MIMO suffer from other cells and the lack of accurate channel models for Massive MIMO systems.

Modern wearable devices allow monitoring vital parameters such as heart or respiratory rates, electrocardiogram, photo-plethysmographic or even video signals, and are being massively commercialized in the consumer electronics market. A common issue of wearable technology is that signal processing and transmission are power demanding and, as such, require frequent battery charges. In our research, we consider biometric signal compression as a means to boost the battery life of wearables, while still allowing for fine-grained and long-term monitoring applications. We have proposed a few algorithms based on different approaches: 1) online motif extraction and pattern identification, 2) online and subject-adaptive dictionaries, and 3) denoising autoencoders. These techniques are compared with other recent algorithms from the literature based on: compressive sensing, discrete cosine and Wavelet transforms, principal component analysis and lightweight temporal compression. As we quantify in our performance evaluation, our algorithms allow reductions in the signal size of up to 70 (dictionary-based) or 100 (autoencoders) times, and obtain similar reductions in the energy demand, by still keeping the reconstruction error within 4% of the peak-to-peak signal amplitude.

We are investigating system identification techniques based on inertial signals from wearable devices, such as smartphones. Their goal is to recognize a target user from their way of walking, using the accelerometer and gyroscope (inertial) signals provided by a commercial smartphone worn in the front pocket of the user’s trousers. Our design features several innovations including: a robust and smartphone-orientation-independent walking cycle extraction block, a novel feature extractor based on convolutional neural networks, a one-class support vector machine to classify walking cycles, and the coherent integration of these into a multi-stage authentication system. To the best of our knowledge, our system is the first exploiting convolutional neural networks as universal feature extractors for gait recognition, and using classification results from subsequent walking cycles into a multi-stage decision making framework. Experimental results show the superiority of our approach against state-of-the-art techniques, leading to misclassification rates (either false negatives or positives) smaller than 0.15% in fewer than five walking cycles.

The signals used to design and test IDNet are freely downloadable here below. Our dataset features accelerometer and gyroscope signals collected from fifty users through a number of different smartphones. Motion traces were acquired wearing the smartphone in the front pocket of the user’s trousers. Multiple acquisition sessions were carried out for each user to account for multiple types of terrain and clothes. The collected traces were anonymized and organized in the below “.tar.gz” archive.

Microfluidics is a multidisciplinary field with practical applications to the design of systems, called Lab-on-a-Chip (LoC), where tiny volumes of fluids are circulated through channels with millimeter size and driven into structures where precise chemical/physical processes take place. At this scale, fluids may exhibit specific behaviors that are unobserved at macro scales. These properties are at the basis of a number of applications, ranging from the inkjet printer heads to DNA sequencing chips, and have been recently exploited in the development of Lab-on-Chip (LoC) systems or, more generally, Microfluidic Machines (MMs), that are currently used for different purposes, included the synthesis of particles for therapeutic delivery, drug discovery, biomolecule synthesis, diagnostic testing, DNA sequencing.
The interest on microfluidics has been increasing over the last few years and, recently, droplet-based microfluidic circuits capable of performing simple logical operations have been proposed and experimentally tested, paving the way to a new research branch known as microfluidic networking. The overall objective of microfluidic networking is to realize switching and networking elements that make it possible to interconnect specialized LoCs in a flexible and modular system, possibly using only hydrodynamics properties. Such an architecture would unleash the still largely unexpressed potential of the microfluidic technology, producing a leap forward in many fields, included the pharmaceutical, chemical, and medical sectors. This challenge calls for interdisciplinary competences, which range from telecommunication engineering to physics and chemistry, and can open the way to a number of exciting research trails!

The first component of any networks are the the switches. Microfluidic networks are no exception. A possible solution to switch droplets across a microfluidic network consists in electro-hydrodynamic actuation that, however, requires specific and complex circuitry with a large number of electrical connections and high power source. Furthermore, the contact of electrodes with fluids may give rise to corrosion problems and unwanted reactions. Most of these problems are solved by adopting a purely hydrodynamic approach that only relies on the actuators (pumps and reservoirs) at the periphery of the chip (the boundary system) and on the channel geometries and hydrodynamic forces that act on the fluids to control the droplets in the network. The basic principle is that droplets flow along the path with minimum instantaneous hydraulic resistance, meanwhile increasing the resistance of the channel they are crossing. Thus, an isolated droplet entering a T or Y junction through the inlet will proceed towards the outlet with minimum instantaneous hydraulic resistance, while a closely following droplet may be driven to the other outlet. Therefore, it is possible to steer a payload droplet through a series of junctions by modulating its distance with respect to a certain number of control droplets. However, the flow behavior in complex microfluidic systems is affected by a number of interdependent factors that make the fluid flow at any one location depend upon the properties of the entire system. Furthermore, the time behavior of a droplet-based microfluidic network is also difficult to predict, because the motion of the droplets across the channels will continuously change the hydraulic resistance of different parts of the network and, hence, the flow rates of the continuous phase in different channels that, in turn, affect the speed of the droplets. All these interdependencies make extremely difficult to figure out the effect of combining together simple structures into a more complex system and to assess the time dynamics of a network in presence of multiple droplets. In this area, one interesting challenge concerns the comparison between switching mechanisms based on different physical quantities, such as the inter-distance between the droplets, or their length.

Recently, physics researchers have advanced the idea of exploiting microfluidic systems to build tiny computing units, and the possibility of using them in order to realize simple boolean functions has been experimentally proved. Even more interesting is the recent proposal of introducing communication notions in the microfluidic domain, e.g., encoding information in the distance between consecutive drops. Inspired by these works, we carried out some experiments using real microfluidic devices with the intent of investigating a proper way to transmit information in a microfluidic channel. In particular, we exploited the T-junction droplet generator governing laws in order to modulate the length of generated droplets (and, consequently, their interdistance) in a sort of binary Pulse Amplitude Modulation scheme. Results show that the noise that affects both droplet length and inter-distance can be modeled as a zero-mean normal random process, whose variance, however, depends on the transmitted symbol, i.e., on the working point of the system. More specifically, droplet-based modulation exhibits stronger noise for symbols associated to relatively short droplets, while interdistance-based modulation is more noisy when droplets are more spaced apart. Overall, however, droplet interdistance appears to be more robust a signal than droplet length for PAM modulation, though both techniques can achieve relatively low bit error probability in the considered scenarios. Although this analysis moves some initial steps toward the performance characterization of a microfluidic-based PAM transmission system, the way to go is still very long and unexplored. As an example, the transient behavior exhibited by the droplet generation circuit when changing the volumetric flow rates at the input has not yet been analyzed, nor has it been considered the actual bitrate that can be achieved with such a mechanism. These an other interesting challenges are left for future work.

In future energy grids, an intelligent and coordinated use of distributed generators (DG) based on renewables holds the potential of boosting the grid efficiency, for example, in terms of reduction of power losses, reactive power compensation, load balancing and peak shaving, while also relieving electricity production plants from some of the power load. This requires the addition of communication and smart metering capabilities to the power grid, and their careful orchestration. Our present focus is on the design of a set of control and communication algorithms to optimally manage the micro grid in terms of electrical performance and energy trading policies. These will exploit the computational and communication capabilities offered by the smart gateways that will be installed within each structure. In particular, we note that optimal pricing procedures are needed to assure that the end users equipped with DGs are willing to contribute to the enhancement of the power grid’s performance. The joint investigation of pricing techniques combined with suitable communication and control aspects has not been subject to an in depth theoretical study yet, despite being of great importance for the successful design and the deployment of the foreseen distributed smart grid infrastructure. Our project is rather ambitious and challenging as it involves techniques from telecommunications, electrical engineering and control systems. Up to now, research has mostly been carried out in isolation within these fields, leading to control strategies that are efficient in terms of smart grid’s performance but either neglect important telecommunication details or are difficult to implement as they do not well suit current market models. Our proposal is instead to tackle the distributed optimization of smart grids through a synergistic approach, where market (pricing) models are jointly modeled and designed together with communication and control algorithms.

Accurate statistical characterizations of daily power demand for different types of buildings and users (as, for example, households, shops and factories) is key to the study of smart grids. In addition to the energy consumption, we are also concerned with modeling the hourly energy price from real grids. These traces are instrumental to identify suitable statistical predictive models for the energy market. These models are being used within co-simulation tools and as well as the input of mathematical optimization frameworks.

We are tackling the design of optimal pricing policies based on metering and communication capabilities. These policies guarantee that, at any given time, the network is driven through an efficient operating point in terms of revenue for the users and the grid operator (market efficiency), while also assuring that the power grid is efficiently operated (electrical efficiency). In detail, the optimization algorithm will determine optimal discount factors (on the prices proposed by the energy producers) that will govern the local energy market, with the objective of driving the electricity grid’s performance toward selected (and pluggable) optimization goals.

We are addressing the design distributed online algorithms to jointly drive the smart grid toward efficient working points in terms of power quality and market. This solution shall also account for an efficient use of the state of charge of the distributed storage devices so that they are, at any time, within their operating range.

We are also engaged in the implementation of a full-fledged smart grid simulator accounting for: a) electrical power grid topology and dynamics. Grid topologies will be generated according to random graph theory applied to real-world power grid topologies; b) statistical characterization of photovoltaic electrical energy generation. This characterization will account for the photovoltaic panel technology and size, geographical coordinates, azimuthal and tilt orientation parameters and the month of the year selected for the simulation run; c) statistical characterization of electrical power demand by end users. This characterization will account for active and reactive power demand variations on a minute basis; d) communication network architecture, topology and physical layer dynamics; e) communication protocol stack; f) real time, plug-and-play, grid optimization techniques; g) dynamic energy pricing and marked dynamics.

Underwater networking poses serious challenges to network designers, as no straightforward translation exists between protocols for the terrestrial wireless radio environment and their underwater counterparts. The main reason behind this is the different nature of the underwater acoustic channel: long propagation delays (the average propagation speed of an acoustic wave is about 1500 m/s underwater, nearly 200’000 times smaller than radio waves in the air), strong multipath effects, long-term channel variations, and last but not least a much smaller bandwidth available (due to the use of acoustic frequencies, i.e., in the tens of kHz range), which turns into lower transmit bit rates. While radio and optical waves may also be an option for underwater communications, acoustic waves still foster a lot of interest, as they are currently the only means to reach distances longer than a few hundred meters. With the proper configuration of transmission hardware parameters, acoustic waves can travel up to tens of kilometers, making long range communication feasible, albeit at a possibly very low bit rate.

As there is no widely agreed upon model for the channel, we seek new models that are sufficiently compact yet simple enough to be plugged into a network simulator. This activity is carried out in cooperation with institutions and research centers that can provide real data from undersea measurement campaigns. 

Underwater acoustic channel can be simulated using ray-tracer as well. We develop the WOSS Framework to obtain realistic acustic channel realization based on ray-tracer to be used in underwater network simulators.

We are currently analyzing a number of MAC solutions by means of simulations and stochastic models, in order to discover which features make one protocol perform better than others, with the final objective to create a novel protocol encompassing the best behaviors seen in other approaches.

Multihop underwater networks will require delay-tolerant routing protocols, that work well in the presence of very long propagation delays. We are currently analyzing the relevant routing tradeoffs that allow, e.g., to save energy by choosing wisely which nodes will relay messages. We are also designing efficient broadcasting techniques based on Hybrid ARQ.

We collaborate with research institutions to define joint sea trial activities which allow for network protocol evaluation as well as channel characterization; this feeds novel insight and provides directions to all above tasks.

Authors	Title		Venue/Journal
Davide Costa, Filippo Campagnaro and Michele Zorzi	Robot Operating System (ROS) Talks Underwater: an Open-Source Communication Middleware to Control Underwater Vehicles		IEEE METROSea 2025
Vincenzo Cimino, Filippo Campagnaro and Michele Zorzi	A Reliable Transfer File Protocol over UDP for Multihop Underwater Acoustic Networks		IEEE METROSea 2025
Federico Marin, Antonio Montanari, Filippo Campagnaro and Michele Zorzi (University of Padova, Italy)	Characterization of Low-Cost Transducers for Underwater Communications		IEEE METROSea 2025
Filippo Donegà, Filippo Bragato, Filippo Campagnaro and Michele Zorzi	A Lightweight AI-powered Framework for Multimodal Underwater Networks		UACE 2025
Davide Cosimo, Lorenzo Bazzarello, Vincenzo Cimino, Filippo Donegà, Federico Guerra, Filippo Campagnaro, Michele Zorzi, Riccardo Costanzi, Andrea Caiti	Improving Underwater Acoustic Network Performance with AUV Swarm Mobility and Environmental Awareness		IEEE/MTS Oceans 2025 Brest
Diego Spinosa, Jacopo Lazzarin, Filippo Campagnaro, Michele Zorzi	A Practical Evaluation of Forward Error Correction Schemes and PSK Detection Parameters for Underwater Acoustic Transmissions		IEEE/MTS Oceans 2025 Brest
Mauro Biagi, Andrea Petroni, Filippo Campagnaro, Michele Zorzi	Invisible Light Communications: Ultraviolet Enabling Robust High-Rate Underwater Communications		IEEE Wireless Communications 2025
Matin Ghalkhani, Jianyu Zhang, Filippo Campagnaro, Michele Zorzi	UWGS: Geometry-Based Enhanced Time Synchronization in Underwater Acoustic Mobile Networks		Asilomar 2024
Dimitri Sotnik, Roberto Francescon, Filippo Campagnaro, Michael Goetz, Ivor Nissen, Michele Zorzi	From Real-World Data to Synthetic Models: a Time-Varying Approach for Underwater Networks		ACM WUWNET 2024
Nils Moroz, Filippo Campagnaro, Lu Shen, Benjamin T. Henson, Florian Mahieu, Yuriy Zakharov, Paul D. Mitchell	Statistical ON-OFF Link Modeling Based on Sea Trial Data		ACM WUWNET 2024
Antonio Montanari, Vincenzo Cimino, Diego Spinosa, Filippo Donegà, Federico Marin, Filippo Campagnaro, Michele Zorzi	PSK modulation for Underwater Communication and One-Way Travel-Time Ranging with the Low-Cost Subsea Software-Defined Acoustic Modem		ACM WUWNET 2024
Filippo Campagnaro, Matin Ghalkhani, Riccardo Tumiati, Federico Marin, Matteo Dal Grande, Alessandro Pozzebon, Davide De Battisti, Roberto Francescon, Michele Zorzi	Monitoring the Venice Lagoon: an IoT Cloud-Based Sensor Network Approach		IEEE JOE 2024
Davide Cosimo, Antonio Montanari, Daniele Sebino Terracciano, Lorenzo Bazzarello, Riccardo Costanzi, Filippo Campagnaro, Michele Zorzi	Comparative Analysis of Throughput Maximization Strategies in Underwater Acoustic Networks: Results from At-Sea Experiments		IEEE METROSea 2024
Matin Ghalkhani, Federico Marin, Filippo Campagnaro, Michele Zorzi	Enhancing IoT Cloud Infrastructure and Data Visualization for Real-Time Monitoring of the Venice Lagoon with SENSWICH		IEEE METROSea 2024
Filippo Donegà, Roberto Francescon, Filippo Campagnaro, Ivor Nissen, Michele Zorzi	A Collaborative Reputation Mechanism for Underwater Acoustic Networks		IEEE UComms 2024
Antonio Montanari, Federico Marin, Vincenzo Cimino, Diego Spinosa, Filippo Donegà, Davide Cosimo, Lorenzo Bazzarello, Daniele Natale, Filippo Campagnaro, Michele Zorzi	Experimenting Various JANUS Frequency Bands with the Subsea Software-Defined Acoustic Modem		IEEE UComms 2024
A. Montanari, F. Campagnaro, M. Zorzi	An Adaptive MAC-Agnostic Ranging Scheme for Underwater Acoustic Mobile Networks		Elsevier Computer Networks
F. Donegà, E. Bortolozzo, R. Francescon, F. Campagnaro, M. Zorzi	A security system for spreading information about malicious behaviors in underwater wireless sensor networks		IEEE/MTS Oceans 2024 Singapore
J. Lazzarin, F. Campagnaro, M. Padovan, E. Rossi, I. Karakosta-Amarantidou, F. Picciariello, F. Vedovato, G. Vallone, P. Villoresi, M. Zorzi	Quantum Key Distribution for Secure Encryption in Underwater Networks		IEEE/MTS Oceans 2024 Singapore
J. Zhang, F. Campagnaro, A. Montanari, M. Zorzi	One-way Ranging for Mobile Underwater Acoustic Networks with Long Interaction Periods		IEEE/MTS Oceans 2024 Singapore
A. Ortile, F. Campagnaro, F. Chiariotti, M. Zorzi	Unmanned Marine Vehicle Cooperative Offshore Infrastructure Monitoring with Multimodal Underwater Feature Transmission		ACM WUWNet 2023 Shenzhen
V. Cimino, F. Campagnaro, M. Zorzi	A Mine Countermeasure System with Low-Cost AUV Swarms		ACM WUWNet 2023 Shenzhen
F. Campagnaro, F. Steinmetz, B.C. Renner, M. Zorzi	Affordable underwater acoustic modems and their application in everyday life: a complete overview		ACM WUWNet 2023 Shenzhen
M. Ghalkhani, F. Campagnaro, A. Pozzebon, D. De Battisti, M. Biagi, M. Zorzi	A LoRaWAN Network for the Real-Time Monitoring of the Venice Lagoon: Preliminary Tests		IEEE/OES Metrosea 2023 Malta
H. Dol, K. Blom, D. Sotnik, I. Nissen, R. Otnes, A. Komulainen, F. Campagnaro	EDA-SALSA: Development of a self-reconfigurable protocol stack for robust underwater acoustic networking		IEEE/MTS Oceans 2023 Limerick
Riccardo Tumiati, Filippo Campagnaro, Irene Cappelli, Alessandro Pozzebon, Michele Zorzi	Modeling the underwater electromagnetic radio frequency channel in the DESERT Underwater network simulator		IEEE/MTS Oceans 2023 Limerick
Jianyu Zhang, Filippo Campagnaro, Michele Zorzi	Spatial-reuse TDMA for Large Scale Underwater Acoustic Multi-hop Grid Networks		IEEE/MTS Oceans 2023 Limerick
Roberto Francescon, Filippo Campagnaro, Federico Favaro, Federico Guerra, Michele Zorzi	Software Defined Underwater Communications: an Experimental Platform for Research		IEEE/MTS Oceans 2023 Limerick
Alessandro Pozzebon, Irene Cappelli, Filippo Campagnaro, Roberto Francescon and Michele Zorzi	LoRaWAN Transmissions in Salt Water for Superficial Marine Sensor Networking: Laboratory and Field Tests		MDPI Sensors
Filippo Campagnaro, Roberto Francescon, Emanuele Coccolo, Antonio Montanari, Michele Zorzi	A Software-Defined Underwater Acoustic Modem for Everyone: Design and Evaluation		IEEE IoTMag 2023
Emanuele Coccolo, Cosmin Delea, Fabian Steinmetz, Roberto Francescon, Alberto Signori, Ching Nok Au, Filippo Campagnaro, Vincent Schneider, Federico Favaro, Johannes Oeffner, Christian Renner, Michele Zorzi	System Architecture and Communication Infrastructure for the RoboVaaS project		IEEE Journal of Oceanic Engineering 2023
Filippo Campagnaro, Fabian Steinmetz, Bernd-Christian Renner	Survey on Low-Cost Underwater Sensor Networks: From Niche Applications to Everyday Use		MDPI JMSE 2023
Federico Mason, Federico Chiariotti, Andrea Zanella, Michele Zorzi	Automatic Shark Detection via Underwater Acoustic Sensing		IEEE IoTMag 2022
Antonio Montanari, Filippo Campagnaro, Michele Zorzi	One- and Two-Way Travel Time Ranging in Underwater Acoustic Mobile Networks		WUWNet 2022 Boston – US
Nicola Toffolo, Antonio Montanari, Filippo Campagnaro, Michele Zorzi	Modeling acoustic channel variability in underwater network simulators from real field experimental data		MTS/IEEE Oceans 2022 Hampton Roads – US
Filippo Campagnaro, Nicola Toffolo, Alessandro Pozzebon, Roberto Francescon, Alberto Barausse, Laura Airoldi, Michele Zorzi	A Network Infrastructure for Monitoring Coastal Environments and Study Climate Changes in Marine Systems		MTS/IEEE Oceans 2022 Hampton Roads – US
Emanuele Coccolo, Roberto Francescon, Filippo Campagnaro, Michele Zorzi	Field Tests of the Software Defined Modem Prototype for the MODA Project		IEEE UComms 2022
Filippo Campagnaro, Nicola Toffolo, Michele Zorzi	Modeling acoustic channel variability in underwater network simulators from real field experiment data		MDPI Electronics 2022
A. Pal, Filippo Campagnaro, K. Ahraf, R. Rahman, A. Ashok, H. Guo	Communication for Underwater Sensor Networks: A Comprehensive Summary		ACM Transactions on Sensor Networks 2022
Alberto Signori, Filippo Campagnaro, Ivor Nissen, Michele Zorzi	Channel-Based Trust Model for Security in Underwater Acoustic Networks		IEEE Internet of Things Journal 2022
Emanuele Coccolo, Filippo Campagnaro, Davide Tronchin, Antonio Montanari, Roberto Francescon, Lorenzo Vangelista , Michele Zorzi	Underwater Acoustic Modem for a MOrphing Distributed Autonomous Underwater Vehicle (MODA)		MTS/IEEE Oceans 2022 Chennai – India
Alberto Signori, Emanuele Coccolo, Filippo Campagnaro, Ivor Nissen, Michele Zorzi	Trustworthiness in the GUWMANET+ Protocol for Underwater Acoustic Mobile Ad-Hoc Networks		ACM WUWNet 2021
Alberto Signori, Federico Chiariotti, Filippo Campagnaro, Roberto Petroccia, Konstantinos Pelekanakis, Pietro Paglierani, João Alves, Michele Zorzi	A Geometry-Based Game Theoretical Model of Blind and Reactive Underwater Jamming		IEEE Transactions on Wireless Communications
Davide Tronchin, Roberto Francescon, Filippo Campagnaro, Alberto Signori, Roberto Petroccia, Konstantinos Pelekanakis, Pietro Paglierani, João Alves, Michele Zorzi	A Secure Cross-Layer Communication Stack for Underwater Acoustic Networks		MTS/IEEE Oceans 2021 San Diego – Porto
Filippo Campagnaro, Alberto Signori, Roald Otnes, Michael Goetz, Dimitri Sotnik, Arwid Komulainen, Ivor Nissen, Federico Favaro, Federico Guerra, Michele Zorzi	A Simulation Framework for Smart Adaptive Long- and Short-range Acoustic Networks		MTS/IEEE Oceans 2021 San Diego – Porto
Roberto Francescon, Filippo Campagnaro, Emanuele Coccolo, Alberto Signori, Federico Guerra, Federico Favaro, Michele Zorzi	An Event-Based Stack For Data Transmission Through Underwater Multimodal Networks		IEEE Ucomms 2021
Filippo Campagnaro, Alberto Signori, Michele Zorzi	Wireless Remote Control for Underwater Vehicles		Journal of Marine Science and Engineering
Filippo Campagnaro, Davide Tronchin, Alberto Signori, Roberto Petroccia, Konstantinos Pelekanakis, Pietro Paglierani, Joāo Alves, Michele Zorzi	Replay-Attack Countermeasures for Underwater Acoustic Networks		MTS/IEEE Global Oceans 2020
Cosmin Delea, Emanuele Coccolo, Salvador Fernandez Covarrubias, Filippo Campagnaro, Federico Favaro, Roberto Francescon, Vincent Schneider, Johannes Oeffner, Michele Zorzi	Communication Infrastructure and Cloud Computing in Robotic Vessel as-a-Service Application		MTS/IEEE Global Oceans 2020
Alberto Signori, Filippo Campagnaro, Kim-Fabian Wachlin, Ivor Nissen, Michele Zorzi	On the Use of Conversation Detection to Improve the Security of Underwater Acoustic Networks		MTS/IEEE Global Oceans 2020
Federico Mason, Federico Chiariotti, Filippo Campagnaro, Andrea Zanella, Michele Zorzi	Low-cost AUV Swarm Localization Through Multimodal Underwater Acoustic Networks		MTS/IEEE Global Oceans 2020
Tommaso Zugno, Filippo Campagnaro, Michele Zorzi	Controlling in real-time an ASV-carried ROV for quay wall and ship hull inspection through wireless links in harbor environments		MTS/IEEE Global Oceans 2020
Davide Magrin, Alberto Signori, Davide Tronchin, Filippo Campagnaro, Michele Zorzi	Collaboration of LoRaWAN and Underwater Acoustic Communications in Sensor Data Collection Applications		MTS/IEEE Global Oceans 2020
Federico Chiariotti, Alberto Signori, Filippo Campagnaro, Michele Zorzi	Underwater Jamming Attacks as Incomplete Information Games		IEEE INFOCOM Workshop WCNEE 2020
Alberto Signori, Federico Chiariotti, Filippo Campagnaro, Michele Zorzi	A Game-Theoretic and Experimental Analysis of Energy-Depleting Underwater Jamming Attacks		IEEE Internet of Things Journal
Paolo Casari, Filippo Campagnaro, Elizaveta Dubrovinskaya, Roberto Francescon, Amir Dagan, Shlomo Dahan, Michele Zorzi, Roee Diamant	ASUNA: A Topology Dataset for Underwater Network Emulation		IEEE Journal of Oceanic Engineering
Alberto Signori, Filippo Campagnaro, Fabian Steinmetz, Bernd-Christian Renner, Michele Zorzi	Data Gathering from a Multimodal Dense Underwater Acoustic Sensor Network Deployed in Shallow Fresh Water Scenarios		Journal of Sensor and Actuator Networks
Alberto Signori, Chiara Pielli, Federico Chiariotti, Marco Giordani, Filippo Campagnaro, Nicola Laurenti, Michele Zorzi	Jamming the Underwater: a Game-Theoretic Analysis of Energy-Depleting Jamming Attacks		ACM WUWNet 2019
Filippo Campagnaro, Fabian Steinmetz, Alberto Signori, Davide Zordan, Bernd-Christian Renner, Michele Zorzi	Data Collection in Shallow Fresh Water Scenarios with Low-Cost Underwater Acoustic Modems		UACE 2019
Davide Zordan, Filippo Campagnaro, Michele Zorzi	On the feasibility of an Anti-grounding Service with Autonomous Surface Vessels		MTS/IEEE Oceans19 Marseille
Alberto Signori, Filippo Campagnaro, Davide Zordan, Federico Favaro, Michele Zorzi	Underwater Acoustic Sensors Data Collection in the Robotic Vessels as-a-Service Project		MTS/IEEE Oceans19 Marseille

Previous works can be found at this link