arXiv subjects

Ivan Iudice

Publications and source records attributed to Ivan Iudice.

14 recordsLinked to original sources

arXiv2026

AI-Driven Design of Stacked Intelligent Metasurfaces for Software-Defined Radio Applications

The integration of reconfigurable intelligent surfaces (RIS) into future wireless communication systems offers promising capabilities in dynamic environment shaping and spectrum efficiency. In this work, we present a consistent implementation of a stacked intelligent metasurface (SIM) model within the NVIDIA's AI-native framework Sionna for 6G physical layer research. Our implementation allows simulation and learning-based optimization of SIM-assisted communication channels in fully differentiable and GPU-accelerated environments, enabling end-to-end training for cognitive and software-defined radio (SDR) applications. We describe the architecture of the SIM model, including its integration into the TensorFlow-based pipeline, and showcase its use in closed-loop learning scenarios involving adaptive beamforming and dynamic reconfiguration. Benchmarking results are provided for various deployment scenarios, highlighting the model's effectiveness in enabling intelligent control and signal enhancement in non-terrestrial-network (NTN) propagation environments. This work demonstrates a scalable, modular approach for incorporating intelligent metasurfaces into modern AI-accelerated SDR systems and paves the way for future hardware-in-the-loop experiments.

eess.SP↗

arXiv2026

Conformal Reconfigurable Intelligent Surfaces: A Cylindrical Geometry Perspective

Curved reconfigurable intelligent surfaces (RISs) represent a promising frontier for next-generation wireless communication, enabling adaptive wavefront control on nonplanar platforms such as unmanned aerial vehicles and urban infrastructure. This work presents a systematic investigation of cylindrical RISs, progressing from idealized surface-impedance synthesis to practical implementations based on simple one-bit meta-atoms. Exact analytical and geometrical-optics-based models are first developed to explore fundamental design limits, followed by a semi-analytical formulation tailored to discrete, reconfigurable architectures. This model enables efficient beam synthesis using both evolutionary optimization and low-complexity strategies, including the minimum power distortionless response method, and is validated through full-wave simulations. Results confirm that one-bit RISs can achieve directive scattering with manageable sidelobe levels and minimal hardware complexity. These findings establish the viability of cylindrical RISs and open the door to their integration into dual-use wireless platforms for real-world communication scenarios.

eess.SP↗

arXiv2025

Randomized Space-Time Stacked Intelligent Metasurfaces for Massive Multiuser Downlink Connectivity

Stacked intelligent metasurfaces (SIMs) represent a key enabler for next-generation wireless networks, offering beamforming gains while significantly reducing radio-frequency chain requirements. In conventional space-only SIM architectures, the rate of reconfigurability of the SIM is equal to the inverse of the channel coherence time. This paper investigates a novel beamforming strategy for massive downlink connectivity using a randomized space-time (ST) coded SIM. In addition to conventional space-only metasurface layers, the proposed design integrates a ST metasurface layer at the input stage of the SIM that introduces random time variations over each channel coherence time interval. These artificial time variations enable opportunistic user scheduling and exploitation of multiuser diversity under slow channel dynamics. To mitigate the prohibitive overhead associated with full channel state information at the transmitter (CSIT), we propose a partial-CSIT-based beamforming scheme that leverages randomized steering vectors and limited user-side feedback based on signal quality measurements. Numerical results demonstrate that the proposed ST-SIM architecture achieves satisfactory sum-rate performance while significantly reducing CSIT acquisition and feedback overhead, thereby enabling scalable downlink connectivity in dense networks.

eess.SP↗

arXiv2025

A Methodological Framework for Positioning of Wireless Sensors in New Generation Launchers

In wireless sensor networks for reusable launchers, the electromagnetic characterization and electromagnetic compatibility analyses are relevant due to the reference operational scenario, which implies a complex, and sometimes dynamic, electromagnetic environment. This work proposes a methodological framework for the design of the network and for the analysis of the related electromagnetic environment within the stages of a given launcher. Based on the preliminary positioning of the network nodes, the framework prescribes a workflow and the related toolset for determining the optimal network topology focusing on the weights, the operation of the transceivers, and the overall radiated power. The optimal network configuration is simulated by using computational electromagnetics strategies in order to assess the electromagnetic environment induced by the sensor network itself. The paper provides some results concerning a case study for a specific launcher.

eess.SP↗

arXiv2024

Design of stacked intelligent metasurfaces with reconfigurable amplitude and phase for multiuser downlink beamforming

A novel technology based on stacked intelligent metasurfaces (SIM) has recently emerged. This platform involves cascading multiple metasurfaces, each acting as a digitally programmable physical layer within a diffractive neural network. SIM enable the implementation of signal-processing transformations directly in the electromagnetic wave domain, eliminating the need for expensive, high-precision, and power-intensive digital platforms. However, existing studies employing SIM in wireless communication applications rely solely on nearly passive structures that control only the phase of the meta-atoms in each layer. In this study, we propose a SIM-aided downlink multiuser transmission scheme, where the SIM at the base station (BS) end is designed by combining nearly passive layers with phase-only reconfiguration capabilities and active layers integrated with amplifier chips to enable amplitude control. Our optimal design aims at maximizing the sum rate for the best group of users by jointly optimizing the transmit power allocation at the BS and the wave-based beamforming at the SIM. In addition to the standard sum-power constraint at the BS, our optimization framework includes two additional constraints: (i) a per-stream power preserving constraint to prevent propagation losses across the SIM, and (ii) an amplitude constraint to account for power limitations for each active layer. To further reduce the complexity of the optimal beamforming solution, we explore a simple yet suboptimal zero-forcing (ZF) beamforming design, where the wave-based transformation implemented by the SIM is selected to eliminate interference among user streams. Finally, extensive Monte Carlo simulations demonstrate that incorporating both nearly passive and active layers within the SIM significantly enhances capacity compared to previously reported phase-only coding SIM.

eess.SP↗

arXiv2024

A real/fast-time simulator for impact assessment of spoofing & jamming attacks on GNSS receivers

In aviation, the impact of threats is becoming increasingly significant, particularly for global navigation satellite system (GNSS). Two relevant GNSS threats are represented by jamming and spoofing. In order to evaluate the technological solutions to counter GNSS attacks, such attacks should be assessed by means of a proper GNSS threat simulator. This work shows the implementation and the testing results of a GNSS security impact simulator which injects the desired threat scenarios as a deviations on the GNSS actual measurements. The proposed simulator can be integrated in both real- and fast-time simulation environments. The provided results confirm the effectiveness of the simulator, and include in-flight demonstrations by means of a flight experimental vehicle.

eess.SP↗

arXiv2024

CycloDSP: A cyclostationary signal analysis tool for GNU Radio

In this paper, we present a first attempt to incorporate in the GNU Radio ecosystem a tool called CycloDSP, devoted to the analysis of complex-valued cyclostationary signals. Such signals are ubiquitous in communication and signal processing, exhibiting periodic or almost periodic statistics that are characterized by a countable set of cycle frequencies, which are related to the main signal periodicities. Common cycle frequencies for modulated signals are multiple of the baudrate and/or combination of the carrier frequency and baudrate. Conventional estimation strategies for cyclostationary signal analysis typically exhibit a high computational burden. Many approaches aimed at reducing complexity exploit fast Fourier transform (FFT) algorithms, which are very efficient for batch data but are not suited for continuously streaming data, typically encountered in software-defined radio (SDR) applications. The aim of this paper is to develop an out-of-tree (OOT) GNU Radio module containing a set of building block functions, aimed at estimating functions, such as the cyclic correlation functions, typically employed for cyclostationary signal analysis. The proposed implementation must be designed so as to ensure high efficiency in processing continuous data streams of complex samples, both in terms of computational load and data storage, in order to be executed on general purpose computers. We tested our implementation by estimating in real-time the second-order cyclic statistics of a Gaussian minimum-shift keying (GMSK) modulated signal, which belongs to a class of signals commonly employed in aeronautical telemetry datalinks.

eess.SP↗

arXiv2023

A Hybrid NOMA-OMA Scheme for Inter-plane Intersatellite Communications in Massive LEO Constellations

Communication between satellites in low-Earth orbit (LEO) constellations takes place through inter-satellite links (ISLs). Unlike intra-plane ISLs, which interconnect satellites belonging to the same orbital plane with fixed relative distance, inter-plane ISLs experience significant Doppler frequency shifts, since satellites belonging to different orbital planes exhibit timevarying relative distance (required, e.g., to minimize the risk of physical collisions between satellites). In this paper, we consider the problem of connecting multiple satellites, belonging to a massive LEO constellation, to a receiving satellite, referred to as the sink. Specifically, we consider a hybrid multiple access scheme, which employs a combination of non-orthogonal multiple access (NOMA), where radio-frequency ISLs share the same time-frequency resource blocks, and orthogonal multiple access (OMA), where ISLs employ orthogonal resource blocks. The set of satellites transmitting towards the sink is divided into groups, where NOMA is employed within each group, whereas OMA is used to separate different groups. Such a scheme subsumes as special cases both pure-OMA and pure-NOMA. Our study highlights that similar Doppler frequency shifts have a significant impact on the individual rates of the satellites in a pure-NOMA scheme, thus reducing the network fairness of this technique. Motivated by such a fact, we develop design strategies of the proposed hybrid NOMA-OMA scheme, which exploit inter-plane Doppler frequency diversity to enhance fairness among the satellites, while ensuring a significantly higher sumrate capacity compared to the pure-OMA technique. Numerical results corroborate our theoretical analysis, by demonstrating both the fairness enhancement of the proposed techniques over the pure-NOMA scheme, as well as their capacity improvement over the pure-OMA one.

eess.SP↗

arXiv2022

Sensing Technologies for Crowd Management, Adaptation, and Information Dissemination in Public Transportation Systems: A Review

Management of crowd information in public transportation (PT) systems is crucial, both to foster sustainable mobility, by increasing the user's comfort and satisfaction during normal operation, as well as to cope with emergency situations, such as pandemic crises, as recently experienced with COVID-19 limitations. This paper presents a taxonomy and review of sensing technologies based on Internet of Things (IoT) for real-time crowd analysis, which can be adopted in the different segments of the PT system (buses/trams/trains, railway/metro stations, and bus/tram stops). To discuss such technologies in a clear systematic perspective, we introduce a reference architecture for crowd management, which employs modern information and communication technologies (ICT) in order to: (i) monitor and predict crowding events; (ii) implement crowd-aware policies for real-time and adaptive operation control in intelligent transportation systems (ITSs); (iii) inform in real-time the users of the crowding status of the PT system, by means of electronic displays installed inside vehicles or at bus/tram stops/stations, and/or by mobile transport applications. It is envisioned that the innovative crowd management functionalities enabled by ICT/IoT sensing technologies can be incrementally implemented as an add-on to state-of-the-art ITS platforms, which are already in use by major PT companies operating in urban areas. Moreover, it is argued that, in this new framework, additional services can be delivered to the passengers, such as, e.g., on-line ticketing, vehicle access control and reservation in severely crowded situations, and evolved crowd-aware route planning.

cs.CY↗

arXiv2022

A cloud-assisted ADS-B network for UAVs based on SDR

Integration of Unmanned Aerial Vehicles (UAVs) or "drones" into the civil aviation airspace is a problem of increasing interest in the aviation community, as testified by many initiatives developed worldwide. Many traditional surveillance solutions for manned aircrafts employ the Automatic Dependent System-Broadcast (ADS-B) technology, which however might present several drawbacks when used for UAVs, especially smaller ones and/or those flying at very low altitudes. We present in this paper a cloud-based surveillance solution for UAVs, which can be considered as an enhancement of a conventional ADS-B system. The proposed solution leverages inexpensive on-board transceivers for transmitting positional messages from the UAVs to the ground. A network of ADS-B gateways, based on the software-defined radio (SDR) paradigm, format the positional messages into valid ADS-B signals and rebroadcast them in the air, allowing thus to emulate a true ADS-B system and overcoming the main disadvantages of the conventional implementation. A preliminary performance analysis of the proposed approach, based on queuing theory, shows the main tradeoffs of the considered approach. Moreover, a physical-layer laboratory implementation of the proposed solution is presented, based on off-the-shelf SDR hardware, which is programmed using the open-source GNU Radio environment.

eess.SP↗

arXiv2021

Detection and blind channel estimation for UAV-aided wireless sensor networks in smart cities under mobile jamming attack

Unmanned aerial vehicles (UAVs) can be integrated into wireless sensor networks (WSNs) for smart city applications in several ways. Among them, a UAV can be employed as a relay in a "store-carry and forward" fashion by uploading data from ground sensors and metering devices and, then, downloading it to a central unit. However, both the uploading and downloading phases can be prone to potential threats and attacks. As a legacy from traditional wireless networks, the jamming attack is still one of the major and serious threats to UAV-aided communications, especially when also the jammer is mobile, e.g., it is mounted on a UAV or inside a terrestrial vehicle. In this paper, we investigate anti-jamming communications for UAV-aided WSNs operating over doubly-selective channels in the downloading phase. In such a scenario, the signals transmitted by the UAV and the malicious mobile jammer undergo both time dispersion due to multipath propagation effects and frequency dispersion caused by their mobility. To suppress high-power jamming signals, we propose a blind physical-layer technique that jointly detects the UAV and jammer symbols through serial disturbance cancellation based on symbol-level post-sorting of the detector output. Amplitudes, phases, time delays, and Doppler shifts - required to implement the proposed detection strategy - are blindly estimated from data through the use of algorithms that exploit the almost-cyclostationarity properties of the received signal and the detailed structure of multicarrier modulation format. Simulation results corroborate the anti-jamming capabilities of the proposed method, for different mobility scenarios of the jammer.

eess.SP↗

arXiv2021

Channel State Acquisition in Uplink NOMA for Cellular-Connected UAV: Exploitation of Doppler and Modulation Diversities

Integration of unmanned aerial vehicles (UAVs) for surveillance or monitoring applications into fifth generation (5G) New Radio (NR) cellular networks is an intriguing problem that has recently tackled a lot of interest in both academia and industry. For an efficient spectrum usage, we consider a recently-proposed sky-ground nonorthogonal multiple access (NOMA) scheme, where a cellular-connected UAV acting as aerial user (AU) and a static terrestrial user (TU) are paired to simultaneously transmit their uplink signals to a base station (BS) in the same time-frequency resource blocks. In such a case, due to the highly dynamic nature of the UAV, the signal transmitted by the AU experiences both time dispersion due to multipath propagation effects and frequency dispersion caused by Doppler shifts. On the other hand, for a static ground network, frequency dispersion of the signal transmitted by the TU is negligible and only multipath effects have to be taken into account. To decode the superposed signals at the BS through successive interference cancellation, accurate estimates of both the AU and TU channels are needed. In this paper, we propose channel estimation procedures that suitably exploit the different circular/noncircular modulation formats (modulation diversity) and the different almost-cyclostationarity features (Doppler diversity) of the AU and TU by means of widely-linear time-varying processing. Our estimation approach is semi-blind since Doppler shifts and time delays of the AU are estimated based on the received data only, whereas the remaining relevant parameters of the AU and TU channels are acquired relying also on the available training symbols, which are transmitted by the AU and TU in a nonorthogonal manner.

eess.SP↗

arXiv2020

Separable MSE-based design of two-way multiple-relay cooperative MIMO 5G networks

While the combination of multi-antenna and relaying techniques has been extensively studied for Long Term Evolution Advanced (LTE-A) and Internet of Things (IoT) applications, it is expected to still play an important role in 5th Generation (5G) networks. However, the expected benefits of these technologies cannot be achieved without a proper system design. In this paper, we consider the problem of jointly optimizing terminal precoders/decoders and relay forwarding matrices on the basis of the sum mean square error (MSE) criterion in multiple-input multiple-output (MIMO) two-way relay systems, where two multi-antenna nodes mutually exchange information via multi-antenna amplify-and-forward relays. This problem is nonconvex and a local optimal solution is typically found by using iterative algorithms based on alternating optimization. We show how the constrained minimization of the sum-MSE can be relaxed to obtain two separated subproblems which, under mild conditions, admit a closed-form solution. Compared to iterative approaches, the proposed design is more suited to be integrated in 5G networks, since it is computationally more convenient and its performance exhibits a better scaling in the number of relays.

eess.SP↗

arXiv2020

Design and performance analysis of channel estimators under pilot spoofing attacks in multiple-antenna systems

In multiple antenna systems employing time-division duplexing, spatial precoder design at the base station (BS) leverages channel state information acquired through uplink pilot transmission, under the assumption of channel reciprocity. Malicious eavesdroppers can start pilot spoofing attacks to alter such design, so as to improve their eavesdropping performance in downlink. The aim of this paper is to study the effects of pilot spoofing attacks on uplink channel estimation, by assuming that the BS knows the angle of arrivals (AoAs) of the legitimate channels. Specifically, after assessing the performance of the simple least squares estimator (LSE), we consider more sophisticated estimators, such as the maximum likelihood estimator (MLE) and different versions of the minimum mean square error estimator (MMSEE), involving different degrees of a priori information about the pilot spoofing attacks. Theoretical analysis and numerical simulations are used to compare the performance of such estimators. In particular, we analytically demonstrate that the spoofing effects in the high signal-to-noise regime can be completely suppressed, under certain conditions involving the AoAs of the legitimate and spoofing channels. Moreover, we show that even an imperfect knowledge of the AoAs and of the average transmission power of the spoofing signals allows the MLE and MMSEE to achieve significant performance gains over the LSE.

eess.SP↗