arXiv subjects

Marcus Henninger

Publications and source records attributed to Marcus Henninger.

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

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

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

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

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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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

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

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

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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arXiv2024

Bistatic Information Fusion for Positioning and Tracking in Integrated Sensing and Communication

The distributed nature of cellular networks is one of the main enablers for integrated sensing and communication (ISAC). For target positioning and tracking, making use of bistatic measurements is non-trivial due to their non-linear relationship with Cartesian coordinates. Most of the literature proposes geometric-based methods to determine the target's location by solving a well-defined set of equations stemming from the available measurements. The error covariance to be used for Bayesian tracking is then derived from local Taylor expansions. In our work we adaptively fuse any subset of bistatic measurements using a maximum likelihood (ML) framework, allowing to incorporate every possible combination of available measurements, i.e., transmitter angle, receiver angle and bistatic range. Moreover, our ML approach is intrinsically flexible, as it can be extended to fuse an arbitrary number of measurements by multistatic setups. Finally, we propose both a fixed and dynamic way to compute the covariance matrix for the position error to be fed to Bayesian tracking techniques, like a Kalman filter. Numerical evaluations with realistic cellular communications parameters at mmWave frequencies show that our proposal outperforms the considered baselines, achieving a location and velocity root mean square error of 0.25 m and 0.83 m/s, respectively.

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arXiv2024

Pilot-Based SFO Estimation for Bistatic Integrated Sensing and Communication

Enabling bistatic radar sensing within the context of integrated sensing and communication (ISAC) for future sixth generation mobile networks demands strict synchronization accuracy, which is particularly challenging to be achieved with over-the-air synchronization. Existing algorithms handle time and frequency offsets adequately, but provide insufficiently accurate sampling frequency offset (SFO) estimates that result in degradation of obtained radar images in the form of signal-to-noise ratio loss and migration of range and Doppler shift. This article introduces an SFO estimation algorithm named tilt inference of time offset (TITO) for orthogonal frequency-division multiplexing (OFDM)-based ISAC. Using available pilot subcarriers, TITO obtains channel impulse response estimates and extracts information on the SFO-induced delay migration to a dominant reference path with constant range, Doppler shift, and angle between transmit and receive ISAC nodes. TITO then adaptively selects the delay estimates that are only negligibly impaired by SFO-induced intersymbol interference, ultimately employing them to estimate the SFO. Assuming a scenario without a direct line-of-sight (LoS) between the aforementioned transmitting and receiving ISAC nodes, a system concept with a relay reflective intelligent surface (RIS) is used to create the aforementioned reference path is proposed. Besides a mathematical derivation of accuracy bounds, simulation and measurements at 26.2 GHz are presented to demonstrate TITO's superiority over existing methods in terms of SFO estimation accuracy and robustness.

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arXiv2024

Feasibility of Non-Line-of-Sight Integrated Sensing and Communication at mmWave

One rarely addressed direction in the context of Integrated Sensing and Communication (ISAC) is non-line-of-sight (NLOS) sensing, with the potential to enable use cases like intrusion detection and to increase the value that wireless networks can bring. However, ISAC networks impose challenges for sensing due to their communication-oriented design. For instance, time division duplex transmission creates spectral holes in time, resulting in spectral replicas in the radar image. To counteract this, we evaluate different channel state information processing strategies and discuss their tradeoffs. We further propose an ensemble of techniques to detect targets in NLOS conditions. Our approaches are validated with experiments using a millimeter wave ISAC proof of concept in a factory-like environment. The results show that target detection in NLOS is generally possible with ISAC.

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arXiv2024

Bistatic OFDM-based ISAC with Over-the-Air Synchronization: System Concept and Performance Analysis

Integrated sensing and communication (ISAC) has been defined as one goal for 6G mobile communication systems. In this context, this article introduces a bistatic ISAC system based on orthogonal frequency-division multiplexing (OFDM). While the bistatic architecture brings advantages such as not demanding full duplex operation with respect to the monostatic one, the need for synchronizing transmitter and receiver is imposed. In this context, this article introuces a bistatic ISAC signal processing framework where an incoming OFDM-based ISAC signal undergoes over-the-air synchronization based on preamble symbols and pilots. Afterwards, bistatic radar processing is performed using either only pilot subcarriers or the full OFDM frame. The latter approach requires estimation of the originally transmitted frame based on communication processing and therefore error-free communication, which can be achieved via appropriate channel coding. The performance and limitations of the introduced system based on both aforementioned approaches are assessed via an analysis of the impact of residual synchronization mismatches and data decoding failures on both communication and radar performances. Finally, the performed analyses are validated by proof-of-concept measurement results.

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