arXiv subjects

Silvio Mandelli

Publications and source records attributed to Silvio Mandelli.

At least 19 recordsLinked to original sources

arXiv2026

BASIIS: Bistatic Angular Sampling and Interpolation for ISAC Setups

Integrated Sensing and Communications (ISAC) is a defining feature of 6G, extending cellular networks with radar-like sensing at limited additional overhead. In bistatic deployments, sensing requires coordinating the transmitter (TX) and receiver (RX) arrays to scan the Cartesian product of angle of departure and arrival, resulting in a four-dimensional sampling problem in the angular domain. This work establishes a complete angular sampling framework for bistatic ISAC, extending the DFT-based optimal-sampling methodology to the full azimuth and elevation domains of both arrays. We show that the bistatic geometry couples the TX and RX elevation angles, and represent this coupling through the ortho-baseline coarray, a virtual array that captures the joint elevation aperture of the array pair. From the coarray we derive a minimal sampling and interpolation scheme, near-lossless and realizable with any beamforming architecture. Monte Carlo simulations confirm the proposed minimal acquisition essentially equalizes the detection accuracy of dense oversampled imaging while acquiring 3 to 5 times fewer TX-RX direction pairs. This allows having bistatic operations with drastically reduced overhead on the radio resource usage of ISAC systems.

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arXiv2026

Parametric Channel Estimation with Hardware Impaired Hybrid Beamformers: Sensing, Communications, and Power Efficiency Tradeoffs

Due to high power consumption and hardware costs of fully digital arrays, hybrid beamformers are often considered as a more economic alternative. Furthermore, using high resolution analog to digital converters (ADCs) can also have prohibitive power consumption, which leads to lower resolution converters being considered for radio frequency (RF) front end design. The finite quantization resolution as well as the nonlinearities caused by the power amplifiers (PAs) and low noise amplifiers (LNAs) can have a substantial impact on system performance. While widely studied for communications, the impact of hardware impairments on sensing performance is considerably less explored. In this work, we study the interplay between hybrid beamforming architectures, hardware impairments, and sensing and communications performance. Additionally, we define the concept of double-isotropy for pilot-combiner pairs, formalizing the notion of a perfectly energy-fair beam sweep. The multiple start (MS) space alternating generalized expectation maximization algorithm (SAGE) is also introduced, aimed at addressing the optimization issues arising from parametric channel estimation (PCE) in hybrid beamformed systems. We then provide a set of numerical results assessing the impacts of beamformer architecture and ADC resolution on PCE, sensing, and communications performance. The results show that medium resolution ADCs lead to the most power efficient configurations, with the best tradeoff between power consumption and performance for the majority of beamforming architectures. Additionally, fully digital beamforming architectures with high resolution converters can often be substituted for a hybrid beamformer setup with medium resolution converters without significant performance loss at a lower power consumption and overall hardware cost.

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arXiv2026

Reliable UAV Detection with ISAC

Unmanned Aerial Vehicle (UAV) detection is one prominent use case of Integrated Sensing and Communication (ISAC) systems in 5G-Advanced and future 6G networks. In this paper, we present experimental results for the detection of a small UAV using unmodified commercial 5G hardware for mono-static Orthogonal Frequency-Division Multiplexing (OFDM) radar and compare them with the expected performance based on models for link budget and hardware impairments. We show that reliable detection with sub-meter accuracy is still possible in over 500 meters distance in a challenging radio environment rich of strong clutter.

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arXiv2026

Reliable Non-Line-of-Sight Intrusion Detection with Integrated Sensing and Communications Hardware

Non-line-of-sight (NLOS) sensing has the potential to enable use cases like intrusion detection in occluded areas, increasing the value provided by Integrated Sensing and Commu- nications (ISAC) in future 6G cellular networks. In this paper, we present a reliable NLOS intrusion detection system based on a millimeter-wave ISAC proof-of-concept. By leveraging reflections off a large surface, the proposed system addresses the challenge of detecting moving targets in cluttered indoor industrial scenarios where the direct line-of-sight is obstructed. A signal processing pipeline including a tracking stage, comparing a Kalman Filter (KF)- and a probability hypothesis density (PHD) filter-based approach, is applied to detect targets and track movements in NLOS. Experimental validation conducted in the ARENA2036 industrial research campus demonstrates that our system can reliably detect target presence in NLOS while avoiding false alarms. Tests with synthetically generated false peaks further demonstrate the robustness of our system to false alarms. Overall, the results underline the potential of NLOS ISAC as a promising technology for enabling intrusion detection and monitoring use cases.

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arXiv2026

Experimental Demonstration of Multi-Target Tracking in Integrated Sensing and Communication

For a wide range of envisioned integrated sensing and communication (ISAC) use cases, it is necessary to incorporate tracking techniques into cellular communication systems. While numerous multi-target tracking (MTT) algorithms exist, they have not yet been applied to real-world ISAC, with its challenges such as clutter and non-optimal hardware with design emphasis on communication instead of sensing. In this work, we showcase MTT based on the probability hypothesis density (PHD) filter in the range and radial speed domain. The measurements are taken with a 5G compliant ISAC proof-of-concept in a real factory environment, where the pedestrian-like targets are generated by a radar target emulator. We detail the complete pipeline, from measurement acquisition to evaluation, with a focus on the post-processing of the raw captured data and the tracking itself. Our end-to-end evaluation and comparison to simulations show good MTT performance with mean absolute ranging error <1.5m and detection rates >91% for realistic but challenging scenarios.

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arXiv2026

Survey on Integrated Sensing and Communication Performance Modeling and Use Cases Feasibility

As the research community starts to address the* key features of 6G cellular standards, one of the agreed bridge topics to be studied already in 5G advanced releases is Integrated Sensing and Communication (ISAC). The first efforts of the research community are focusing on ISAC enablers, fundamental limits, and first demonstrators, that show that the time has come for the deployment of sensing functionalities in cellular standards. This survey paper takes a needed step towards ISAC deployment, providing an analytical toolkit to model cellular systems' sensing performance, accounting for both their fundamental and practical constraints. We then elaborate on the likely features of 6G systems to provide the feasible sensing key performance indicators (KPIs) in the frequency ranges spanned by cellular networks, including the potential new bands available in 6G, the Frequency Range 3 (FR3). We further validate our framework by visually investigating ISAC constraints with simulation examples. Finally, we assess the feasibility of few selected scenarios that can be enabled by ISAC, highlighting in each of them the limiting factor and, thus, which gaps should be filled by the research and standardization communities in the next years.

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arXiv2026

Breaking the CP Limit: Robust Long-Range OFDM Sensing via Interference Cleaning

In orthogonal frequency-division multiplexing-based radar and integrated sensing and communication systems, the sensing range is traditionally limited by the round-trip time corresponding to the cyclic prefix duration. Targets whose echoes arrive after this duration induce intersymbol interference (ISI) and associated intercarrier interference (ICI), which significantly degrade detection performance, elevate the interference-noise floor in the radar image, and reduce the useful signal power due to window mismatch. Existing methods face a trade-off between recovering useful signal and suppressing interference, particularly in multi-target scenarios. This paper proposes two frameworks to resolve this dilemma, offering a flexible trade-off between computational cost and target detection performance. First, a signal model is derived, demonstrating that ISI and ICI-oriented interference often dominates thermal noise in high-dynamic-range scenarios. To combat the ISI and ICI-based interference-noise floor increase, joint-interference cancellation with coherent compensation is proposed. This approach is an efficient evolution of the successive-interference cancellation algorithm, utilizing high-precision chirp Z-transform estimation and frequency-domain coherent compensation to recover weak distant targets. For scenarios requiring maximum precision, the full reconstruction-based sliding window scheme is presented, which shifts the receive window to capture optimal signal energy while performing full-signal reconstruction for all detected targets. Numerical results show that both methods outperform state-of-the-art benchmarks.

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arXiv2026

Synthetic Aperture Communication: Principles and Application to Massive IoT Satellite Uplink

While synthetic aperture radar is widely adopted to provide high-resolution imaging at long distances using small arrays, the concept of coherent synthetic aperture communication (SAC) has not yet been explored. This article introduces the principles of SAC for direct satellite-to-device uplink, showcasing precise direction-of-arrival estimation for user equipment (UE) devices, facilitating spatial signal separation, localization, and easing link budget constraints. Simulations for a low Earth orbit satellite at 600 km orbit and two UE devices performing orthogonal frequency-division multiplexing-based transmission with polar coding at 3.5 GHz demonstrate block error rates below 0.1 with transmission powers as low as -10 dBm, even under strong interference when UE devices are resolved but fall on each other's strongest angular sidelobe. These results validate the ability of the proposed scheme to address mutual interference and stringent power limitations, paving the way for massive Internet of Things connectivity in non-terrestrial networks.

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arXiv2026

Energy Efficient Downlink mMIMO Using Dynamic Antenna and Power Adaptation

Massive multiple-input multiple-output (mMIMO) technology and its future evolutions are expected to address the high data rate demands of sixth generation (6G) communication systems. At the same time, network energy savings (NES) is essential in reducing the operational costs and meeting the sustainability goals of network operators. In this regard, we propose a dynamic scheme for joint antenna and power adaptation to improve NES from a user scheduling and resource allocation perspective. Antenna adaptation is performed using the multiple channel state information resource signal (CSI-RS) framework. Furthermore, the recently introduced transmit power-aware link adaptation scheme, referred to as POLITE for short, is used as the power adaptation technique. The proposed scheme adapts to variations in users' instantaneous traffic and channel conditions to opportunistically maximize NES while also inherently accounting for the user throughput. Numerical simulation results show that the proposed scheme consistently achieves a balance between NES and user perceived throughput (UPT) for different network load conditions. Especially in low and light load conditions, the proposed scheme significantly improves the intra-cell interference and boosts the overall NES, while ensuring that UPT is unaffected.

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arXiv2026

Bistatic ISAC: Practical Challenges and Solutions

This article presents and discusses challenges and solutions for practical issues in bistatic integrated sensing and communication (ISAC) in 6G networks. Considering orthogonal frequency-division multiplexing as the adopted waveform, a discussion on system design aiming to achieve both a desired sensing key performance indicators and limit the impact of hardware impairments is presented. In addition, signal processing techniques to enable over-the-air synchronization and generation of periodograms with range, Doppler shift, and angular information are discussed. Simulation results are then presented for a cellular-based ISAC scenario considering system parameterization compliant to current 5G and, finally, a discussion on open challenges for future deployments is presented.

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arXiv2026

Weather Estimation for Integrated Sensing and Communication

One of the key features of sixth-generation (6G) mobile communications will be integrated sensing and communication (ISAC). While the main goal of ISAC in standardization efforts is to detect objects, the byproducts of radar operations can be used to enable new services in 6G, such as weather sensing. Even though weather radars are the most prominent technology for weather detection and monitoring, they are expensive and usually neglect areas in close vicinity. To this end, we propose reusing the dense deployment of 6G base stations for weather sensing purposes by detecting and estimating weather conditions. We implement both a classifier and a regressor as a convolutional neural network trained across measurements with varying precipitation rates and wind speeds. We implement our approach in an ISAC proof-of-concept and conduct a multi-week experiment campaign. Experimental results show that we are able to jointly and accurately classify weather conditions with accuracies of 99.38% and 98.99% for precipitation rate and wind speed, respectively. For estimation, we obtain mean absolute errors of 1.2 mm/h and 1.5 km/h, for precipitation rate and wind speed, respectively. These findings indicate that weather sensing services can be reliably deployed in 6G ISAC networks, broadening their service portfolio and boosting their market value.

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arXiv2026

Hybrid Resource Allocation Scheme for Bistatic ISAC with Data Channels

Bistatic integrated sensing and communication (ISAC) enables efficient reuse of the existing cellular infrastructure and is likely to play an important role in future sensing networks. In this context, ISAC using the data channel is a promising approach to improve the bistatic sensing performance compared to relying solely on pilots. One of the challenges associated with this approach is resource allocation: the communication link aims to transmit higher modulation order (MO) symbols to maximize the throughput, whereas a lower MO is preferable for sensing to achieve a higher signal-to-noise ratio in the radar image. To address this conflict, this paper introduces a hybrid resource allocation scheme. By placing lower MO symbols as pseudo-pilots on a suitable sensing grid, we enhance the bistatic sensing performance while only slightly reducing the spectral efficiency of the communication link. Simulation results validate our approach against different baselines and provide practical insights into how decoding errors affect the sensing performance.

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arXiv2025

Target Classification for Integrated Sensing and Communication in Industrial Deployments

Integrated Sensing and Communication (ISAC) systems enable cellular networks to jointly operate as communication technology and sense the environment. While opportunities and potential performance have been largely investigated in simulations, few experimental works have showcased Automatic Target Recognition (ATR) effectiveness in a real-world deployment based on cellular radio units. To bridge this gap, this paper presents an initial study investigating the feasibility of ATR for ISAC. Our ATR solution uses a Deep Learning (DL)-based detector to infer the target class directly from the radar images generated by the ISAC system. The DL detector is evaluated with experimental data from a ISAC testbed based on commercially available mmWave radio units in the ARENA 2036 industrial research campus located in Stuttgart, Germany. Experimental results demonstrate accurate classification performance, demonstrating the feasibility of ATR ISAC with cellular hardware in our setup. We finally provide insights about the open generalization challenges, that will fuel future work on the topic.

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arXiv2025

Angular Estimation Comparison with ISAC PoC

The introduction of Integrated Sensing and Communications (ISAC) in cellular systems is not expected to result in a shift away from the popular choice of cost- and energy-efficient analog or hybrid beamforming structures. However, this comes at the cost of limiting the angular capabilities to a confined space per acquisitions. Thus, as a prerequisite for the successful implementation of numerous ISAC use cases, the need for an optimal angular estimation of targets and their separation based on the minimal number of angular samples arises. In this work, different approaches for angular estimation based on a minimal, DFT-based set of angular samples are evaluated. The samples are acquired through sweeping multiple beams of an ISAC proof of concept (PoC) in the industrial scenario of the ARENA2036. The study's findings indicate that interpolation approaches are more effective for generalizing across different types of angular scenarios. While the orthogonal matching pursuit (OMP) approach exhibits the most accurate estimation for a single, strong and clearly discriminable target, the DFT-based interpolation approach demonstrates the best overall estimation performance.

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arXiv2025

Benchmarking CFAR and CNN-based Peak Detection Algorithms in ISAC under Hardware Impairments

Peak detection is a fundamental task in radar and has therefore been studied extensively in radar literature. However, Integrated Sensing and Communication (ISAC) systems for sixth generation (6G) cellular networks need to perform peak detection under hardware impairments and constraints imposed by the underlying system designed for communications. This paper presents a comparative study of classical Constant False Alarm Rate (CFAR)-based algorithms and a recently proposed Convolutional Neural Network (CNN)-based method for peak detection in ISAC radar images. To impose practical constraints of ISAC systems, we model the impact of hardware impairments, such as power amplifier nonlinearities and quantization noise. We perform extensive simulation campaigns focusing on multi-target detection under varying noise as well as on target separation in resolution-limited scenarios. The results show that CFAR detectors require approximate knowledge of the operating scenario and the use of window functions for reliable performance. The CNN, on the other hand, achieves high performance in all scenarios, but requires a preprocessing step for the input data.

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arXiv2025

Target Detection for ISAC with TDD Transmission

Integrated sensing and communication (ISAC) poses various challenges that arise from the communication-centric design of cellular networks. One of them is target detection with time division duplex (TDD) transmission used in current 5G and future 6G deployments, where the periodic on-off behavior of the transmitter creates impulsive sidelobes in the radar point spread function (PSF). These can be mistaken for actual targets by conventional peak detection techniques, leading to false alarms. In this work, we first analytically describe the range-Doppler PSF due to TDD windowing. We then propose a computationally efficient method that leverages the PSF to distinguish impulsive sidelobes from valid target peaks. Simulation results and outdoor drone measurements with an ISAC proof of concept demonstrate the capability of our algorithm, showing that it can achieve reliable target detection while limiting false alarms.

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arXiv2025

Optimal Azimuth Sampling and Interpolation for Bistatic ISAC Setups

A key challenge in future 6G Integrated Sensing and Communications (ISAC) networks is to define the angular operations of transmitter and receiver, i.e., the sampling task of the angular domains, to acquire information about the environment. In this work we extend previous analysis for optimal angular sampling of monostatic setups to two-dimensional bistatic deployments, that are as important as the former in future ISAC cellular scenarios. Our approach overcomes the limitations of suboptimal prior art sampling and interpolation techniques, such as spline interpolation. We demonstrate that separating azimuth operations of the two transmit and receive arrays is optimal to sample the angular domain in an array-specific normalized angular frequency (NAF). This allows us to derive a loss-less reconstruction of the angular domain, enabling a more efficient and accurate sampling strategy for bistatic sensing applications compared to legacy approaches. As demonstrated by different Monte Carlo experiments, our approach enables future bistatic ISAC deployments with better performance compared to the other suboptimal solutions.

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arXiv2025

Integrated Long-range Sensing and Communications in Multi Target Scenarios using CP-OFDM

6G communication systems promise to deliver sensing capabilities by utilizing the orthogonal frequency division multiplexing (OFDM) communication signal for sensing. However, the cyclic prefix inherent in OFDM systems limits the sensing range, necessitating compensation techniques to detect small, distant targets like drones. In this paper, we show that state-of-the-art coherent compensation methods fail in scenarios involving multiple targets, resulting in an increased noise floor in the radar image. Our contributions include a novel multi target coherent compensation algorithm and a generalized signal-to-interference-and-noise ratio for multiple targets to evaluate the performance. Our algorithm achieves the same detection performance at long distances requiring only 3.6% of the radio resources compared to classical OFDM radar processing. This enables resource efficient sensing at long distances in multi target scenarios with legacy communications-only networks.

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