arXiv subjects

Gianmaria Ventura

Publications and source records attributed to Gianmaria Ventura.

6 recordsLinked to original sources

arXiv2026

Reliable Doppler Estimation in Asynchronous Moving ISAC Devices via IMU Integration

We present an Integrated Sensing And Communication (ISAC) framework for the joint estimation of the Doppler frequency of a passive mobile target in a bistatic scenario with clock-asynchronous nodes and where the Receiver (RX) is static but the Transmitter (TX) is mobile. In such a setup, previous geometric solutions are integrated with an Inertial Measurement Unit (IMU) device at the TX, coming up with a truly joint data fusion and estimation algorithm based on extended Kalman filtering. The approach jointly estimates the target Doppler frequency, along with the speed and direction of motion of the TX and it is robust to the unavailability of static paths between the TX and RX pair, a condition that makes previous solutions ineffective. The developed extended Kalman filter strikes a balance between the accuracy of ISAC and the IMU reliability. The proposed solution is validated via numerical simulations, obtaining a median Doppler error of 1.2% with a smartphone-grade IMU under realistic operating conditions.

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arXiv2026

AsyMov: Integrated Sensing and Communications with Asynchronous Moving Devices

Estimating the Doppler frequency shift caused by moving targets is one of the key objectives of Integrated Sensing And Communication (ISAC) systems, as it enables applications such as target classification, human activity recognition, and gait analysis. In practical scenarios, Doppler estimation is hindered by the movement of transmitter and receiver devices, and by the phase offsets caused by their clock asynchrony. Existing approaches have separately addressed these two aspects, either assuming clock-synchronous moving devices or asynchronous static ones. In fact, jointly tackling device motion and clock asynchrony is extremely challenging, as the Doppler shift from device movement differs for each propagation path and the phase offsets are time-varying. In this work, we present AsyMov, a method to estimate the bistatic Doppler frequency of a target and its velocity in ISAC setups featuring mobile and asynchronous devices. It leverages the channel impulse response at the receiver, by originally exploiting the invariance of phase offsets across propagation paths and the bistatic geometry, where the target Doppler and the device velocity are jointly estimated by a newly proposed alternating minimization algorithm. Moreover, it can be seamlessly integrated with device velocity measurements obtained from onboard sensors (if available), for enhanced reliability. Here, AsyMov is thoroughly characterized by way of theory (Cramér-Rao bound), simulation, and experiments, implementing it on an IEEE 802.11ay testbed and testing it on multiple setups in the 60 GHz and 28 GHz bands, including moving human subjects. Numerical and experimental results show superior performance against state-of-the-art methods and are on par with scenarios featuring static ISAC devices.

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arXiv2025

Toward Multiband Sensing in FR3: Frequency Anisotropy Characterization and Non-Contiguous Bands Aggregation Algorithms

Frequency Range 3 (FR3) in the 7-24 GHz band will be the new spectrum for 6G wireless networks. The bandwidth availability and diversity of FR3 offer unprecedented opportunities for coherent multiband Integrated Sensing and Communications (ISAC), which aggregates the carrier phase information from multiple frequency bands to increase the sensing resolution to the cm-level. However, the frequency anisotropy of sensing targets over GHz-wide bands and the non-contiguity of the 6G spectrum, pose critical challenges to the application of existing multiband ISAC techniques. We present the first study on coherent multiband sensing in FR3. We experimentally characterize the frequency anisotropy of targets and propose new phase coherence metrics for multiband processing. Then, we analyze the impact of non-contiguous FR3 bands considered by 3GPP, and design a new algorithm to mitigate the resulting sensing artifacts, outperforming existing techniques. Our results represent a first step toward fully developing multiband ISAC for FR3.

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arXiv2024

Authentication by Location Tracking in Underwater Acoustic Networks

Physical layer message authentication in underwater acoustic networks (UWANs) leverages the characteristics of the underwater acoustic channel (UWAC) as a fingerprint of the transmitting device. However, as the device moves its UWAC changes, and the authentication mechanism must track such variations. In this paper, we propose a context-based authentication mechanism operating in two steps: first, we estimate the position of the underwater device, then we predict its future position based on the previously estimated ones. To check the authenticity of the transmission, we compare the estimated and the predicted position. The location is estimated using a convolutional neural network taking as input the sample covariance matrix of the estimated UWACs. The prediction uses either a Kalman filter or a recurrent neural network (RNN). The authentication check is performed on the squared error between the predicted and estimated positions. The solution based on the Kalman filter outperforms that built on the RNN when the device moves according to a correlated Gauss-Markov mobility model, which reproduces a typical underwater motion.

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arXiv2024

Bistatic Doppler Frequency Estimation with Asynchronous Moving Devices for Integrated Sensing and Communications

In this letter, we present for the first time a method to estimate the bistatic Doppler frequency of a target with clock asynchronous and mobile Integrated Sensing And Communication (ISAC) devices. Existing approaches have separately tackled the presence of phase offsets due to clock asynchrony or the additional Doppler shift due to device movement. However, in real ISAC scenarios, these two sources of phase nuisance are concurrently present, making the estimation of the target's Doppler frequency particularly challenging. Our method solves the problem using the sole wireless signal at the receiver, exploiting the invariance of phase offsets across multipath components and the bistatic geometry in an original way. The proposed method is validated via simulation, exploring the impact of different system parameters. Numerical results show that our approach is a viable way of estimating Doppler frequency in bistatic asynchronous ISAC scenarios with mobile devices.

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arXiv2023

Towards Decentralized Predictive Quality of Service in Next-Generation Vehicular Networks

To ensure safety in teleoperated driving scenarios, communication between vehicles and remote drivers must satisfy strict latency and reliability requirements. In this context, Predictive Quality of Service (PQoS) was investigated as a tool to predict unanticipated degradation of the Quality of Service (QoS), and allow the network to react accordingly. In this work, we design a reinforcement learning (RL) agent to implement PQoS in vehicular networks. To do so, based on data gathered at the Radio Access Network (RAN) and/or the end vehicles, as well as QoS predictions, our framework is able to identify the optimal level of compression to send automotive data under low latency and reliability constraints. We consider different learning schemes, including centralized, fully-distributed, and federated learning. We demonstrate via ns-3 simulations that, while centralized learning generally outperforms any other solution, decentralized learning, and especially federated learning, offers a good trade-off between convergence time and reliability, with positive implications in terms of privacy and complexity.

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