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Marwa Chafii

Publications and source records attributed to Marwa Chafii.

At least 37 records · Page 2Linked to original sources

Hybrid Radar Fusion with Quantization: CRB-Rate Trade-offs and ADC Dynamic Range

Recent advancements have underscored the relevance of low-resolution analog-to-digital converters (ADCs) in integrated sensing and communication (ISAC) systems. Nevertheless, their specific impact on hybrid radar fusion (HRF) remains largely unexplored. In HRF systems, where uplink (UL) paths carry direct and reflected signals in the same frequency band, the reflected signal is often significantly weaker, making HRF performance particularly sensitive to ADC resolution. To study this effect, we use the quantized Cramér-Rao bound (CRB) to measure sensing accuracy. This work derives an upper bound on the quantized CRB for angle of arrival (AoA) estimation and explores CRB-rate trade-offs through two formulated optimization problems. Simulation results indicate that HRF becomes infeasible when the dynamic range of the received signal exceeds the dynamic range supported by the ADC, which is inherently limited by its resolution. Furthermore, the UL communication rate does not increase significantly when the ADC resolution is raised beyond a certain threshold. These observations highlight a fundamental trade-off between sensing and communication performance: while HRF performance benefits from higher ADC resolutions, the corresponding gains in communication rate plateau. This trade-off is effectively characterized using CRB-rate boundaries derived through simulation.

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Achievable Rate Optimization for Large Flexible Intelligent Metasurface Assisted Downlink MISO under Statistical CSI

The integration of electromagnetic metasurfaces into wireless communications enables intelligent control of the propagation environment. Recently, flexible intelligent metasurfaces (FIMs) have evolved beyond conventional reconfigurable intelligent surfaces (RISs), enabling three-dimensional surface deformation for adaptive wave manipulation. However, most existing FIM-aided system designs assume perfect instantaneous channel state information (CSI), which is impractical in large-scale networks due to the high training overhead and complicated channel estimation. To overcome this limitation, we propose a robust statistical-CSI-based optimization framework for downlink multiple-input single-output (MISO) systems with FIM-assisted transmitters. A block coordinate ascent (BCA)-based iterative algorithm is developed to jointly optimize power allocation and FIM morphing, maximizing the average achievable sum rate. Simulation results show that the proposed statistical-CSI-driven FIM design significantly outperforms conventional rigid antenna arrays (RAAs), validating its effectiveness and practicality.

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Flexible Intelligent Metasurface for Downlink Communications under Statistical CSI

Flexible intelligent metasurface (FIM) is a recently developed, groundbreaking hardware technology with promising potential for 6G wireless systems. Unlike conventional rigid antenna array (RAA)-based transmitters, FIM-assisted transmitters can dynamically alter their physical surface through morphing, offering new degrees of freedom to enhance system performance. In this letter, we depart from prior works that rely on instantaneous channel state information (CSI) and instead address the problem of average sum spectral efficiency maximization under statistical CSI in a FIM-assisted downlink multiuser multiple-input single-output setting. To this end, we first derive the spatial correlation matrix for the FIM-aided transmitter and then propose an iterative FIM optimization algorithm based on the gradient projection method. Simulation results show that with statistical CSI, the FIM-aided system provides a significant performance gain over its RAA-based counterpart in scenarios with strong spatial channel correlation, whereas the gain diminishes when the channels are weakly correlated.

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High-Resolution Sensing in Communication-Centric ISAC: Deep Learning and Parametric Methods

This paper introduces two novel algorithms designed to address the challenge of super-resolution sensing parameter estimation in bistatic configurations within communication-centric integrated sensing and communication (ISAC) systems. Our approach leverages the estimated channel state information derived from reference symbols originally intended for communication to achieve super-resolution sensing parameter estimation. The first algorithm, IFFT-C2VNN, employs complex-valued convolutional neural networks to estimate the parameters of different targets, achieving significant reductions in computational complexity compared to traditional methods. The second algorithm, PARAMING, utilizes a parametric method that capitalizes on the knowledge of the system model, including the transmit and receive array geometries, to extract the sensing parameters accurately. Through a comprehensive performance analysis, we demonstrate the effectiveness and robustness of both algorithms across a range of signal-to-noise ratios, underscoring their applicability in realistic ISAC scenarios.

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From OFDM to AFDM: Enabling Adaptive Integrated Sensing and Communication in High-Mobility Scenarios

Integrated sensing and communication (ISAC) is a key feature of next-generation wireless networks, enabling a wide range of emerging applications such as vehicle-to-everything (V2X) and unmanned aerial vehicles (UAVs), which operate in high-mobility scenarios. Notably, the wireless channels within these applications typically exhibit severe delay and Doppler spreads. The latter causes serious communication performance degradation in the Orthogonal Frequency-Division Multiplexing (OFDM) waveform that is widely adopted in current wireless networks. To address this challenge, the recently proposed Doppler-resilient affine frequency division multiplexing (AFDM) waveform, which uses flexible chirp signals as subcarriers, shows great potential for achieving adaptive ISAC in high-mobility scenarios. This article provides a comprehensive overview of AFDM-ISAC. We begin by presenting the fundamentals of AFDM-ISAC, highlighting its inherent frequency-modulated continuous-wave (FMCW)-like characteristics. Then, we explore its ISAC performance limits by analyzing its diversity order, ambiguity function (AF), and Cramer-Rao Bound (CRB). Finally, we present several effective sensing algorithms and opportunities for AFDM-ISAC, with the aim of sparking new ideas in this emerging field.

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Upper Mid-Band Spectrum for 6G: Vision, Opportunity and Challenges

Driven by the pursuit of gigabit-per-second data speeds for future 6G mobile networks, in addition to the support of sensing and artificial intelligence applications, the industry is expanding beyond crowded sub-6 GHz bands with innovative new spectrum allocations. In this paper, we chart a compelling vision for 6G within the frequency range 3 (FR3) spectrum, i.e. $7.125$-$24.25$ $\GHz$, by delving into its key enablers and addressing the multifaceted challenges that lie ahead for these new frequency bands. Here we highlight the physical properties of this never-before used spectrum for cellular by reviewing recent channel measurements for outdoor and indoor environments, including path loss, delay and angular spreads, and material penetration loss, all which offer insights that underpin future 5G/6G wireless communication designs. Building on the fundamental knowledge of the channel properties, we explore FR3 spectrum agility strategies that balance coverage and capacity tradeoffs, while examining coexistence with incumbent systems, such as satellites, radio astronomy, and earth exploration. Moreover, we discuss the potential of massive multiple-input multiple-output technologies, challenges for commercial deployment, and potential solutions for FR3, including multiband sensing for FR3 integrated sensing and communications. Finally, we outline 6G standardization features that are likely to emerge from 3GPP radio frame innovations and open radio access network developments.

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ISAC Imaging by Channel State Information using Ray Tracing for Next Generation 6G

Integrated sensing and communications (ISAC) is emerging as a cornerstone technology for sixth generation (6G) wireless systems, unifying connectivity and environmental mapping through shared hardware, spectrum, and waveforms. The following paper presents an ISAC imaging framework utilizing channel state information (CSI) per-path components, transmitter (TX) positions, and receiver (RX) positions obtained from the calibrated NYURay ray tracer at 6.75 GHz in the upper mid-band. Our work shows how each resolvable multipath component can be extracted from CSI estimation and cast into an equivalent three-dimensional reflection point by fusing its angle and delay information, which is useful and challenging for multi-bounce reflections. The primary contribution of the paper is the two-segment reflection point optimization algorithm, which independently estimates the path lengths from the TX position and RX position to an equivalent reflection point (ERP) on the object surface, thus enabling precise geometric reconstruction. Subsequently, we aggregate the ERPs derived from multiple pairs of TX and RX positions, generating dense three dimensional point clouds representing the objects in the channel. Experimental results validate that the proposed ISAC imaging framework accurately reconstructs object surfaces, edges, and curved features. To the best of our knowledge, this paper provides the first demonstration of multi bounce ISAC imaging using wireless ray tracing at 6.75 GHz.

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3GPP-Compliant Radar Cross Section Characterization of Indoor Factory Targets

The following paper presents a systematic 3rd Generation Partnership Project (3GPP)-compliant characterization of radar cross section (RCS) for indoor factory (InF) objects, including small and mid-sized unmanned aerial vehicles (UAVs), robotic arms, and automated guided vehicles (AGVs). Through measurements in the 25-28 GHz range, we validate the 3GPP standardized log-normal distribution model for RCS for above-mentioned target objects. The 3GPP-complaint RCS parameters obtained for the small-sized UAV are in close agreement (<1 dB deviation) with 3GPP agreed values. The mid-sized UAVs exhibit higher reflectivity compared to the small-sized UAV due to enhanced specular components attributed to material and lithium-ion battery packs. The robotic arm exhibits dynamic RCS behavior due to mechanical articulation, whereas UAVs show clear size-dependent reflectivity patterns in AGVs. Our findings provide empirical validation for RCS characterization for integrated sensing and communication channel modeling in InF environments.

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Beamforming Design for Secure RIS-Enabled ISAC: Passive RIS vs. Active RIS

The forthcoming sixth-generation (6G) communications standard is anticipated to provide integrated sensing and communication (ISAC) as a fundamental service. These ISAC systems present unique security challenges because of the exposure of information-bearing signals to sensing targets, enabling them to potentially eavesdrop on sensitive communication information with the assistance of sophisticated receivers. Recently, reconfigurable intelligent surfaces (RISs) have shown promising results in enhancing the physical layer security of various wireless communication systems, including ISAC. However, the performance of conventional passive RIS (pRIS)-enabled systems are often limited due to multiplicative fading, which can be alleviated using active RIS (aIRS). In this paper, we consider the problem of beampattern gain maximization in a secure pRIS/aRIS-enabled ISAC system, subject to signal-to-interference-plus-noise ratio constraints at communication receivers, and information leakage constraints at an eavesdropping target. For the challenging non-convex problem of joint beamforming design at the base station and the pRIS/aRIS, we propose a novel successive convex approximation (SCA)-based method. Unlike the conventional alternating optimization (AO)-based methods, in the proposed SCA-based approach, all of the optimization variables are updated simultaneously in each iteration. The proposed method shows significant performance superiority for pRIS-aided ISAC system compared to a benchmark scheme using penalty-based AO method. Moreover, our simulation results also confirm that aRIS-aided system has a notably higher beampattern gain at the target compared to that offered by the pRIS-aided system for the same power budget. We also present a detailed complexity analysis and proof of convergence for the proposed SCA-based method.

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Urban Outdoor Propagation Measurements and Channel Models at 6.75 GHz FR1(C) and 16.95 GHz FR3 Upper Mid-Band Spectrum for 5G and 6G

Global allocations in the upper mid-band spectrum (4--24 GHz) necessitate a comprehensive exploration of the propagation behavior to meet the promise of coverage and capacity. This paper presents an extensive Urban Microcell (UMi) outdoor propagation measurement campaign at 6.75 GHz and 16.95 GHz conducted in Downtown Brooklyn, USA, using a 1 GHz bandwidth sliding correlation channel sounder over 40--880 m propagation distance, encompassing seven Line of Sight (LOS) and 13 Non-Line of Sight (NLOS) locations. Analysis of the path loss (PL) reveals lower directional and omnidirectional PL exponents compared to mmWave and sub-THz frequencies in the UMi environment, using the close-in (CI) free space PL (FSPL) model with a 1 m reference distance. Additionally, a decreasing trend in root mean square (RMS) delay spread (DS) and angular spread (AS) with increasing frequency was observed. The measured NLOS RMS DS and RMS AS mean values (as computed by 3GPP methods) are found to be consistently lower compared to 3GPP model predictions. Point-data tables with corresponding site-specific environmental information for all measured statistics at each TX-RX location are provided to support the models and results. The spatio-temporal statistics presented here offer valuable insights for the design of next-generation wireless systems and networks.

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Achievable Sum Secrecy Rate of STAR-RIS-Enabled MU-MIMO ISAC

Various emerging applications in sixth-generation (6G) wireless demand a seamless integration of communication and sensing services, driving the development of integrated sensing and communication (ISAC) systems. Using a common waveform for both functions introduces additional security challenges, as information-bearing signals are vulnerable to eavesdropping. While a variety of secure beamforming designs are proposed in the literature for metasurface-enabled ISAC systems with single-antenna users and eavesdroppers, optimal designs for multi-antenna scenarios remain unexplored. This paper addresses this gap by studying a simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS)-enabled multi-user multiple-input multiple-output (MU-MIMO) ISAC system and proposing an optimal beamforming design to maximize the sum secrecy rate while ensuring sensing quality for multiple targets. An alternating-optimization based iterative solution is developed to tackle the non-convex optimization problem. The presented analysis confirms that the computational complexity of the proposed algorithm grows linearly with the number of metasurface elements. Our numerical results show the benefit of using STAR-RIS to increase the sum secrecy rate of the MU-MIMO ISAC system compared to its corresponding conventional RIS (cRIS)-enabled and w/o RIS systems.

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Green Integration of Sensing, Communication, and Power Transfer via STAR-RIS

The upcoming sixth-generation (6G) wireless standard is anticipated to support a variety of applications that will require a seamless integration of sensing and communication services in a single network infrastructure. At the same time, 6G is also expected to support millions of low-powered Internet-of-Things (IoT) devices. Previous studies have demonstrated that the power requirements of these IoT devices can be met through wireless power transfer facilitated by intelligent metasurfaces. Therefore, in this paper, we try to formulate and answer a fundamental question: How much transmit power is required for an integrated sensing, communication, and power transfer (ISCPT) system? More specifically, we consider the problem of optimal active, passive, and receive beamforming design for a simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS)-enabled ISCPT system with multiple sensing targets, multiple information receivers, and multiple energy receivers, to minimize the required transmit power from the base station, while guaranteeing predefined sensing, communication, and energy harvesting requirements. To tackle the challenging non-convex optimization problem, we use an alternating optimization (AO)-based approach, where the receive beamforming is obtained in closed form while the active and passive beamforming are obtained using a second-order cone program (SOCP) approach. Our numerical results show the benefit of using STAR-RIS to reduce the transmit power requirement for the ISCPT system compared to its corresponding conventional RIS (cRIS)-enabled and non-RIS ISCPT systems.

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Towards ISAC RIS-Enabled Passive Radar Target Localization

Incorporating integrated sensing and communication capabilities into forthcoming 6G wireless networks is crucial for achieving seamless synchronization between the digital and physical worlds. The following paper focuses on a scenario where a passive radar (PR) is subject to weak line-of-sight signals of opportunity, emanating from an access point and subsequently reflecting off targets, ultimately reaching the PR. Furthermore, a normalized least mean squares method is presented for jointly detecting the number of targets and estimating target angles of arrival (AoAs). The algorithm iteratively adjusts the steering vector estimates to minimize a suitable error cost function, while the target AoAs are identified via a peak-finding search conducted on the resulted power spectrum. Simulation results show the capabilities of the proposed localization method, as well as a 14 dB dynamic range reduction that can be achieved at the PR.

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Mutual Information Based Pilot Design for ISAC

The following paper presents a novel orthogonal pilot design dedicated for \textcolor{black}{integrated sensing and communications (ISAC)} systems performing multi-user communications and target detection. After careful characterization of both sensing and communication metrics based on mutual information (MI), we propose a multi-objective optimization problem (MOOP) tailored for pilot design, dedicated for simultaneously maximizing both sensing and communication MIs. Moreover, the MOOP is further simplified to a single-objective optimization problem, which characterizes trade-offs between sensing and communication performances. Due to the non-convex nature of the optimization problem, we propose to solve it via the projected gradient descent method on the Stiefel manifold. Closed-form gradient expressions are derived, which enable execution of the projected gradient descent algorithm. Furthermore, we prove convergence to a fixed orthogonal pilot matrix. Finally, we demonstrate the capabilities and superiority of the proposed pilot design, and corroborate relevant trade-offs between sensing MI and communication MI. In particular, significant signal-to-noise ratio (SNR) gains for communication are reported, while re-using the same pilots for target detection with significant gains in terms of probability of detection for fixed false-alarm probability. Other interesting findings are reported through simulations, such as an \textit{information overlap} phenomenon, whereby the fruitful ISAC integration can be fully exploited.

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Designing Waveforms with Adjustable PAPR for Integrated Sensing and Communication

This paper presents a new optimization framework dedicated for integrated sensing and communication (ISAC) waveform design. In particular, the problem aims at maximizing the total achievable sum-rate, through multi-user interference minimization, while preserving a certain level of similarity to a given desired radar waveform. Aiming towards feasible and practical PHY architectures, we also offer the flexibility of tuning the peak-to-average power ratio to a desired level. Towards this design, a non-convex optimization problem is formulated, and an alternating direction method of multipliers based solution is derived to converge towards the superiority of the final ISAC waveform. Finally, simulation results validate the proposed ISAC waveform design, as compared to state-of-the-art solutions.

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Statistical and Deterministic RCS Characterization for ISAC Channel Modeling

In this study, we perform a statistical analysis of the radar cross section (RCS) for various test targets in an indoor factory at \(25\)-\(28\) GHz, with the goal of formulating parameters that may be used for target identification and other sensing applications for future wireless systems. The analysis is conducted based on measurements in monostatic and bistatic configurations for bistatic angles of \(20^\circ\), \(40^\circ\), and \(60^\circ\), which are functions of transmitter-receiver (T-R) and target positions, via accurate \(3\)dB beamwidth of \(10^\circ\) in both azimuth and elevation planes. The test targets include unmanned aerial vehicles, an autonomous mobile robot, and a robotic arm. We utilize parametric statistical distributions to fit the measured RCS data. The analysis reveals that the \textit{lognormal and gamma distributions} are effective in modeling the RCS of the test targets over different reflecting points of the target itself, i.e. when target is in motion. Additionally, we provide a framework for evaluating the deterministic bistatic RCS of a rectangular sheet of laminated wood, due to its widespread use in indoor hotspot environments. Novel deterministic and statistical RCS models are evaluated, incorporating dependencies on the bistatic angle, T-R distance (\(2\)m -\(10\)m) and the target. The results demonstrate that some proposed RCS models accurately fit the measured data, highlighting their applicability in bistatic configurations.

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Reinforcement Learning for Enhancing Sensing Estimation in Bistatic ISAC Systems with UAV Swarms

This paper introduces a novel Multi-Agent Reinforcement Learning (MARL) framework to enhance integrated sensing and communication (ISAC) networks using unmanned aerial vehicle (UAV) swarms as sensing radars. By framing the positioning and trajectory optimization of UAVs as a Partially Observable Markov Decision Process, we develop a MARL approach that leverages centralized training with decentralized execution to maximize the overall sensing performance. Specifically, we implement a decentralized cooperative MARL strategy to enable UAVs to develop effective communication protocols, therefore enhancing their environmental awareness and operational efficiency. Additionally, we augment the MARL solution with a transmission power adaptation technique to mitigate interference between the communicating drones and optimize the communication protocol efficiency. Moreover, a transmission power adaptation technique is incorporated to mitigate interference and optimize the learned communication protocol efficiency. Despite the increased complexity, our solution demonstrates robust performance and adaptability across various scenarios, providing a scalable and cost-effective enhancement for future ISAC networks.

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An Experimental Multi-Band Channel Characterization in the Upper Mid-Band

The following paper provides a multi-band channel measurement analysis on the frequency range (FR)3. This study focuses on the FR3 low frequencies 6.5 GHz and 8.75 GHz with a setup tailored to the context of integrated sensing and communication (ISAC), where the data are collected with and without the presence of a target. A method based on multiple signal classification (MUSIC) is used to refine the delays of the channel impulse response estimates. The results reveal that the channel at the lower frequency 6.5 GHz has additional distinguishable multipath components in the presence of the target, while the one associated with the higher frequency 8.75 GHz has more blockage. The set of results reported in this paper serves as a benchmark for future multi-band studies in the FR3 spectrum.

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