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Ahmad Bazzi

Publications and source records attributed to Ahmad Bazzi.

At least 37 records · Page 2Linked to original sources

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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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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On the Secrecy-Sensing Optimization of RIS-assisted Full-Duplex Integrated Sensing and Communication Network

Integrated sensing and communication (ISAC) has recently emerged as a viable technique for establishing sensing and communication using the same resources. Nonetheless, the operation of ISAC networks is often challenged by the absence of a direct link between the sensing node and the targets, and by the risk of disclosing confidential data to malicious targets when using the same signal for both tasks. In this paper, a robust reconfigurable intelligent surface (RIS)-aided scheme for securing a full-duplex (FD) ISAC network is proposed. The considered network consists of uplink and downlink users served in FD through a multi-antenna dual-functional radar communication base station (BS), which employs co-located multi-antenna communication-radar arrays to detect multiple malicious targets while preserving communication secrecy in their presence. Additionally, the BS utilizes an optimized artificial noise (AN) that serves to disrupt the malicious targets' reception and increase the sensing power. By optimally designing the RIS phase shifts, transmit beamforming, AN covariance, and uplink users' transmit power and combining vectors using an alternating optimization-based algorithm, the network's sensing performance is maximized under secrecy and total power constraints. Numerical results present the proposed scheme's efficacy, particularly when a direct link between the BS and the various nodes/targets is absent.

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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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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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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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Low Dynamic Range for RIS-aided Bistatic Integrated Sensing and Communication

The following paper presents a reconfigurable intelligent surface (RIS)-aided integrated sensing and communication (ISAC) system model scenario, where a base station communicates with a user, and a bi-static sensing unit, i.e. the passive radar (PR), senses targets using downlink signals. Given that the RIS aids with communication and sensing tasks, this paper introduces new interfering paths that can overwhelm the PR with unnecessarily high power, namely the path interference (PI), \textit{which is itself a combination of two interfering paths, the direct path interference (DPI) and the reflected path interference (RPI)}. For this, we formulate an optimization framework that allows the system to carry on with its ISAC tasks, through analog space-time beamforming at the sensing unit, in collaboration with RIS phase shift and statistical transmit covariance matrix optimization, while minimizing the PI power. As the proposed optimization problem is non-convex, we tailor a block-cyclic coordinate descent (BCCD) method to decouple the non-convex sub-problem from the convex one. A Riemannian conjugate gradient method is devised to generate the RIS and PR space-time beamforming phase shifts per BCCD iteration, while the convex sub-problem is solved via off-the-shelf solvers. Simulation results demonstrate the effectiveness of the proposed solver when compared with benchmarking ones.

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Sum Secrecy Rate Maximization for Full Duplex ISAC Systems

In integrated sensing and communication (ISAC) systems, the target of interest may \textit{intentionally disguise itself as an eavesdropper}, enabling it to intercept and tap into the communication data embedded in the ISAC waveform. The following paper considers a full duplex (FD)-ISAC system, which involves multiple malicious targets attempting to intercept both uplink (UL) and downlink (DL) communications between the dual-functional radar and communication (DFRC) base station (BS) and legitimate UL/DL communication users (CUs). For this, we formulate an optimization framework that allows maximization of both UL and DL sum secrecy rates, under various power budget constraints for sensing and communications. As the proposed optimization problem is non-convex, we develop a method called Iterative Joint Taylor-Block cyclic coordinate descent (IJTB) by proving essential lemmas that transform the original problem into a more manageable form. In essence, IJTB alternates between two sub-problems: one yields UL beamformers in closed-form, while the other approximates the solution for UL power allocation, artificial noise covariance, and DL beamforming vectors. This is achieved through a series of Taylor approximations that effectively \textit{"convexify"} the problem, enabling efficient optimization. Simulation results demonstrate the effectiveness of the proposed solver when compared with benchmarking ones. Our findings reveal that the IJTB algorithm shows fast convergence, reaching stability within approximately $10$ iterations. In addition, all benchmarks reveal a substantial decline in the sum secrecy rate, approaching zero as the eavesdropper distance reaches $17$ meters, underscoring their vulnerability in comparison to IJTB.

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Multi-Functional RIS for a Multi-Functional System: Integrating Sensing, Communication, and Wireless Power Transfer

Communication networks are evolving from solely emphasizing communication to facilitating multiple functionalities. In this regard, integrated sensing, communication, and powering (ISCAP) provides an efficient way of enabling data transmission, radar sensing, and wireless power transfer simultaneously. Such a multi-functional network requires a multi-functional architectural solution. Toward this end, sensor-aided zero-energy reconfigurable intelligent surfaces (SAZE-RISs) offer an energy-efficient solution for ISCAP by meeting the requirements of the end users as well as supplying power for the RIS. This paper explores the use of SAZE-RIS within the ISCAP framework. First, we present the general system architecture, operational protocols, and main application scenarios for employing SAZE-RIS in ISCAP. Next, we discuss methods for managing the conflicting requirements of communication, sensing, and powering within ISCAP and the role of SAZE-RIS in this process. We then provide a detailed case study complete with simulation results, offering valuable insights into the design choices and tradeoffs that come into play when adopting this technology. Furthermore, we discuss the related challenges and open research avenues, highlighting areas that require further exploration to fully realize the potential of SAZE-RIS within this ISCAP framework.

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Layered Chirp Spread Spectrum Modulations for LPWANs

This article examines two chirp spread spectrum techniques specifically devised for low-power wide-area networks (LPWANs) to optimize energy and spectral efficiency (SE). These methods referred to as layered CSS (LCSS) and layered dual-mode CSS (LDMCSS), involves utilizing multiple layers for multiplexing symbols with varying chirp rates. These waveform designs exemplify a high degree of SE compared to existing schemes. Additionally, LDMCSS necessitates a lesser number of layers than LCSS to attain comparable SE, thereby reducing computational complexity. These proposed techniques can employ coherent and non-coherent detection and can be adjusted to achieve various spectral efficiencies by altering the number of multiplexed layers. Unlike our proposed LCSS and LDMCSS, other CSS alternatives for LPWANs cannot provide the same level of flexibility and SE. The performance of these techniques is evaluated in terms of bit error rate under different channel conditions, as well as with phase and frequency offsets.

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Complex Neural Network based Joint AoA and AoD Estimation for Bistatic ISAC

Integrated sensing and communication (ISAC) in wireless systems has emerged as a promising paradigm, offering the potential for improved performance, efficient resource utilization, and mutually beneficial interactions between radar sensing and wireless communications, thereby shaping the future of wireless technologies. In this work, we present two novel methods to address the joint angle of arrival and angle of departure estimation problem for bistatic ISAC systems. Our proposed methods consist of a deep learning (DL) solution leveraging complex neural networks, in addition to a parameterized algorithm. By exploiting the estimated channel matrix and incorporating a preprocessing step consisting of a coarse timing estimation, we are able to notably reduce the input size and improve the computational efficiency. In our findings, we emphasize the remarkable potential of our DL-based approach, which demonstrates comparable performance to the parameterized method that explicitly exploits the multiple-input multiple-output (MIMO) model, while exhibiting significantly lower computational complexity.

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On Hybrid Radar Fusion for Integrated Sensing and Communication

The following paper introduces a novel integrated sensing and communication (ISAC) scenario termed hybrid radar fusion. In this setting, the dual-functional radar and communications (DFRC) base station (BS) acts as a mono-static radar in the downlink (DL), for sensing purposes, while performing its DL communication tasks. Meanwhile, the communication users act as distributed bi-static radar nodes in the uplink (UL) following a frequency-division duplex protocol. The DFRC BS fuses the information available at different DL and UL resource bands to estimate the angles-of-arrival (AoAs) of the multiple targets existing in the scene. In this work, we derive the maximum likelihood (ML) criterion for the hybrid radar fusion problem at hand. Additionally, we design efficient estimators; the first algorithm is based on an alternating optimization approach to solve the ML criterion, while the second one designs an optimization framework that leads to an alternating subspace approach to estimate AoAs for both the target and users. Finally, we demonstrate the superior performance of both algorithms in different scenarios, and the gains offered by these proposed methods through numerical simulations.

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RIS-Enabled Integrated Sensing and Communication for 6G Systems

The following paper proposes a new target localization system design using an architecture based on reconfigurable intelligent surfaces (RISs) and passive radars (PRs) for integrated sensing and communications systems. The preamble of the communication signal is exploited in order to perform target sensing tasks, which involve detection and localization. The RIS in this case can aid the PR in sensing targets that are otherwise not seen by the PR itself, due to the many obstacles encountered within the propagation channel. Therefore, this work proposes a localization algorithm tailored for the integrated sensing and communications RIS-aided architecture, which is capable of uniquely positioning targets within the scene. The algorithm is capable of detecting the number of targets along with estimating the position of targets via angles and times of arrival. Our simulation results demonstrate the performance of the localization method in terms of different localization and detection metrics and for increasing RIS sizes.

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