RSS 1.0Electrical and Computer Engineering Program
For more information visit: https://cemse.kaust.edu.sa/ece
Recent Submissions
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Analysis and Verification of Islanding Detection Techniques for Grid-integrated PV Systems(IEEE, 2023-03-28) [Conference Paper]The increase in solar energy installation capacity and the versatility of modern power inverters have enabled widespread penetration of distributed generation in modern power systems. Islanding detection techniques allow for fast detection and corrective action in the face of abnormal events. Current standards specify the operational limits for voltage, frequency, and detection time. Grid codes specify the procedures for disconnection to establish safe network maintenance conditions. Passive and active techniques require voltage, current, and frequency measurements and the definition of thresholds for detection. Operational parameters such as load mismatch and quality factors influence the detection capabilities. Falsepositive triggering due to grid transients can lead to unnecessary disconnection of distributed generation resources. In this paper, we analyze the performance of several islanding detection techniques presented in the literature and propose a modified 9-bus benchmark system to verify the robustness of passive and active methods against false-positive detections upon severe gridside transients. Simulation results attest to the superiority of active methods and raise awareness of the susceptibility of all investigated techniques to false islanding detection.
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Joint Trajectory Design and User Scheduling for Secure Aerial Underlay IoT Systems(IEEE Internet of Things Journal, Institute of Electrical and Electronics Engineers (IEEE), 2023-03-28) [Article]Unmanned aerial vehicles (UAVs) have been widely employed to enhance the end-to-end performance of wireless communications since the links between UAVs and terrestrial nodes are line-of-sight (LoS) with high probability. However, the broadcast characteristics of signal propagation in LoS links make them vulnerable to being wiretapped by malicious eavesdroppers, which poses a considerable challenge to the security of wireless communications. In this work, we investigate the security of aerial underlay Internet of Things (IoT) systems by jointly designing trajectory and user scheduling. An airborne base station transmits confidential messages to secondary users utilizing the same spectrum as the primary network. An aerial jammer transmits jamming signals to suppress the eavesdropper to enhance secrecy performance. The uncertainty of eavesdropping node locations is considered, and the average secrecy rate of the secondary user is maximized by optimizing multiple users’ scheduling, the UAVs’ trajectory, and transmit power. To solve the non-convex optimization problem with mixed multi-integer variable problem, we propose an iterative algorithm based on block coordinate descent and successive convex approximation. Numerical results verify the effectiveness of our proposed algorithm and demonstrate that our scheme is beneficial in improving the secrecy performance of aerial underlay IoT systems.
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Optimal RIS Partitioning and Power Control for Bidirectional NOMA Networks(Institute of Electrical and Electronics Engineers (IEEE), 2023-03-27) [Preprint]This study delves into the capabilities of reconfig- urable intelligent surfaces (RISs) in enhancing bidirectional non- orthogonal multiple access (NOMA) networks. The proposed approach partitions RIS to optimize the channel conditions for NOMA users, improving NOMA gain and eliminating the re- quirement for uplink (UL) power control. The proposed approach is rigorously evaluated under four practical operational regimes; 1) Quality-of-Service (QoS) sufficient regime, 2) RIS and power efficient regime, 3) max-min fair regime, and 4) maximum throughput regime, each subject to both UL and downlink (DL) QoS constraints. By leveraging decoupled nature of RIS portions and base station (BS) transmit power, closed-form solutions are derived to demonstrate how optimal RIS partitioning can meet UL-QoS requirements while optimal BS power control can ensure DL-QoS compliance. Our analytical findings are validated through simulations, highlighting the significant benefits that RISs can bring to the NOMA networks in the aforementioned operational scenarios.
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Hybrid 2D/CMOS microchips for memristive applications(Nature, Springer Science and Business Media LLC, 2023-03-27) [Article]Exploiting the excellent electronic properties of two-dimensional (2D) materials to fabricate advanced electronic circuits is a major goal for the semiconductors industry1-2. However, most studies in this field have been limited to the fabrication and characterization of isolated large (>1µm2) devices on unfunctional SiO2/Si substrates. Some studies integrated monolayer graphene on silicon microchips as large-area (>500µm2) interconnection3 and as channel of large transistors (~16.5µm2)4-5, but in all cases the integration density was low, no computation was demonstrated, and manipulating monolayer 2D materials was challenging because native pinholes and cracks during transfer increase variability and reduce yield. Here we present the fabrication of high-integration-density 2D/CMOS hybrid microchips for memristive applications — CMOS stands for complementary metal oxide semiconductor. We transfer a sheet of multilayer hexagonal boron nitride (h-BN) onto the back-end-of-line (BEOL) interconnections of silicon microchips containing CMOS transistors of the 180nm node, and finalize the circuits by patterning the top electrodes and interconnections. The CMOS transistors provide outstanding control over the currents across the h-BN memristors, which allows us to achieve endurances of ~5 million cycles in memristors as small as ~0.053µm2. We demonstrate in-memory computation by constructing logic gates, and measure spike-timing dependent plasticity (STDP) signals that are suitable for the implementation of spiking neural networks (SNN). The high performance and the relatively-high technology readiness level achieved represent a significant advance towards the integration of 2D materials in microelectronic products and memristive applications.
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Runtime Assurance for Safety-Critical Systems: An Introduction to Safety Filtering Approaches for Complex Control Systems(IEEE Control Systems, Institute of Electrical and Electronics Engineers (IEEE), 2023-03-24) [Article]More than three miles above the Arizona desert, an F-16 student pilot experienced a gravity-induced loss of consciousness, passing out while turning at nearly 9Gs (nine times the force of gravity), flying over 400 kn (over 460 mi/h). With its pilot unconscious, the aircraft turn devolved into a dive, dropping from over 17,000 ft to lower than 8,000 ft in altitude in less than 10 s. An auditory warning in the cockpit called out to the pilot “altitude, altitude” just before he crossed through 11,000 ft, switching to a command to “pull up” around 8,000 ft. Meanwhile, the student’s instructor was watching the event unfold from his own aircraft. As the student’s aircraft passed through 12,500 ft, the instructor called over the radio “two recover,” commanding the student (“two”) to end the dive. As the student’s aircraft passed through 11,000 ft, the instructor’s “two recover!” came with increased urgency. At 9,000 ft, and with terror rising in his voice, the instructor yelled “TWO RECOVER!” Fortunately, at the same time as the instructor’s third panicked radio call, a new runtime assurance (RTA) system kicked in to automatically recover the aircraft. The Automatic Ground Collision Avoidance System (Auto GCAS), an RTA system integrated on the jets fewer than two years earlier, in fall 2014, detected that the aircraft was about to collide, commanded a roll to wings level and pull-up maneuver, and recovered the aircraft fewer than 3,000 ft above the ground. The event described here occurred in May 2016. A video from the event was declassified and publicly released in September 2016, and the footage can be found at [1] . While Auto GCAS monitored the behavior of a safety-critical cyberphysical system with a human providing the primary control functions, the same concept is gaining attention in the autonomy community looking to assure safety while integrating complex and intelligent control system designs.
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Catch the Pitch of 5G FWA: EMF and Throughput Measurements of 3.5 GHz Standalone Deployment in a Baseball Stadium(IEEE Open Journal of the Communications Society, Institute of Electrical and Electronics Engineers (IEEE), 2023-03-23) [Article]The provisioning of 5G technology does not only involve mobile terminals, but also new services such as Fixed Wireless Access (FWA). The aim of this study is to examine the ElectroMagnetic Field (EMF) and throughput performance of a FWA deployment utilizing Standalone technology operating at 3.5 GHz. To address the unique characteristics of 5G FWA signals, an innovative framework has been designed based on the measurement of 5G FWA spectrum using four independent chains and an additional traffic generation chain to saturate the radio link capacity at the measurement location. Methodologies for evaluating 5G FWA exposure under conservative conditions, such as measurements of exposure during active traffic generation and maximum power extrapolations, are also introduced. Results from real measurements taken at a baseball stadium show that 5G FWA exposure is consistently low, typically below 0.4 V/m, with an upper bound of 0.59 V/m, while the achieved throughput is up to 250 Mbps. Additionally, the measured 5G exposure levels are a small fraction compared to those emitted by other technologies such as 4G. Furthermore, the values estimated by simulation from the output power counters of the base station are found to be in close agreement with the measured exposure levels.
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High-performance MTJ-based sensors for monitoring of atmospheric pollution(AIP Advances, AIP Publishing, 2023-03-23) [Article]Solid and liquid particles in the atmosphere, referred to as airborne particulate matter (PM), have been rising significantly over the past two decades. Exposure to PM carries significant health risks such as lungs damage, heart disease, cancer, and death. PM2.5 is a subgroup of PM particles that are smaller than 2.5 µm and is a major concern as it is more harmful to health and more difficult to detect. One problematic component of PM2.5 is magnetite nanoparticles (<200 nm), which are readily absorbed into the bloodstream through the respiratory system. Eventually, magnetite nanoparticles deposit inside the brain causing neurodegenerative diseases such as Alzheimer’s or cancerous tumors by inducing oxidative stress. Additionally, Magnetite nanoparticles are often surrounded by heavy metal nanoparticles such as Cadmium and lead which are a great concern to the environment and health. Traditional PM detection methods such as laser scattering are bulky, expensive, and incapable of detecting particles smaller than 200 nm such as magnetite nanoparticles. Therefore, developing a low-cost highly sensitive sensor for monitoring magnetite nanoparticles is vital. Tunneling Magneto-Resistance (TMR) sensors are an attractive option due to their low-cost and high sensitivity toward magnetic nanoparticle detection. Moreover, developing a cheap, portable, and precise remote monitoring technique will allow for the creation of high spatial resolution highly sensitive monitoring networks for magnetic PM2.5. This work focuses on developing, modeling, and simulation of low-cost highly sensitive TMR sensor based on Magnetic Tunnel Junction (MTJ) that can detect and count magnetite nanoparticles.
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A Scalable Laser-Based Underwater Wireless Optical Communication Solution between Autonomous Underwater Vehicle Fleets(Elsevier BV, 2023-03-23) [Preprint]The development of multiple autonomous underwater vehicles (AUVs) has changed the way of relying on a single and expensive AUV to conduct underwater surveys, which is becoming increasingly attractive to marine researchers. Communication between AUV fleets is an urgent concern due to the data rate limitation of underwater acoustic communication. Laser-based underwater wireless optical communication (UWOC) is a potential solution once the link-establishing requirement between AUVs can be met. Due to the limited coverage area of the laser beam, the previous pointing, acquisition, and tracking (PAT) method is to quickly adjust the beam direction and search for the target according to the set scanning path. We propose a scalable laser-based link establishment method that combines the maneuvering of the AUV, the acoustic positioning, and the control of the optical system for increased efficiency. Our approach outperformed the existing PAT approach in a simulation environment and successfully established laser links. In actual machine experiments, the results proved that the proposed approach can be implemented in practical scenarios.
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Don't FREAK Out: A Frequency-Inspired Approach to Detecting Backdoor Poisoned Samples in DNNs(arXiv, 2023-03-23) [Preprint]In this paper we investigate the frequency sensitivity of Deep Neural Networks (DNNs) when presented with clean samples versus poisoned samples. Our analysis shows significant disparities in frequency sensitivity between these two types of samples. Building on these findings, we propose FREAK, a frequency-based poisoned sample detection algorithm that is simple yet effective. Our experimental results demonstrate the efficacy of FREAK not only against frequency backdoor attacks but also against some spatial attacks. Our work is just the first step in leveraging these insights. We believe that our analysis and proposed defense mechanism will provide a foundation for future research and development of backdoor defenses.
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5G-Aided RTK Positioning in GNSS-Deprived Environments(arXiv, 2023-03-23) [Preprint]This paper considers the localization problem in a 5G-aided global navigation satellite system (GNSS) based on real-time kinematic (RTK) technique. Specifically, the user's position is estimated based on the hybrid measurements, including GNSS pseudo-ranges, GNSS carrier phases, 5G angle-of-departures, and 5G channel delays. The underlying estimation problem is solved by steps that comprise obtaining the float solution, ambiguity resolution, and resolving the fixed solution. The analysis results show that the involvement of 5G observations can enable localization under satellite-deprived environments, inclusive of extreme cases with only 2 or 3 visible satellites. Moreover, extensive simulation results reveal that with the help of 5G observations, the proposed algorithm can significantly reduce the estimation error of the user's position and increase the success rate of carrier-phase ambiguity resolution.
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Polyoxometalate-cyclodextrin supramolecular entities for real-time in situ monitoring of dopamine released from neuroblastoma cells(Biosensors & bioelectronics, Elsevier BV, 2023-03-23) [Article]Optimized and sensitive biomarker detection has recently been shown to have a critical impact on quality of diagnosis and medical care options. In this research study, polyoxometalate-γ-cyclodextrin metal-organic framework (POM-γCD MOF) was utilized as an electrocatalyst to fabricate highly selective sensors to detect in-situ released dopamine. The POM-γCD MOF produced multiple modes of signals for dopamine including electrochemical, colorimetric, and smartphone read-outs. Real-time quantitative monitoring of SH-SY5Y neuroblastoma cellular dopamine production was successfully demonstrated under various stimuli at different time intervals. The POM-CD MOF sensor and linear regression model were used to develop a smartphone read-out platform, which converts dopamine visual signals to digital signals within a few seconds. Ultimately, POM-γCD MOFs can play a significant role in the diagnosis and treatment of various diseases that involve dopamine as a significant biomarker.
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Spatial Path Index Modulation in mmWave/THz-Band Integrated Sensing and Communications(arXiv, 2023-03-22) [Preprint]As the demand for wireless connectivity continues to soar, the fifth generation and beyond wireless networks are exploring new ways to efficiently utilize the wireless spectrum and reduce hardware costs. One such approach is the integration of sensing and communications (ISAC) paradigms to jointly access the spectrum. Recent ISAC studies have focused on upper millimeter-wave and low terahertz bands to exploit ultrawide bandwidths. At these frequencies, hybrid beamformers that employ fewer radio-frequency chains are employed to offset expensive hardware but at the cost of lower multiplexing gains. Wideband hybrid beamforming also suffers from the beam-split effect arising from the subcarrier-independent (SI) analog beamformers. To overcome these limitations, this paper introduces a spatial path index modulation (SPIM) ISAC architecture, which transmits additional information bits via modulating the spatial paths between the base station and communications users. We design the SPIM-ISAC beamformers by first estimating both radar and communications parameters by developing beam-split-aware algorithms. Then, we propose to employ a family of hybrid beamforming techniques such as hybrid, SI, and subcarrier-dependent analog-only, and beam-split-aware beamformers. Numerical experiments demonstrate that the proposed SPIM-ISAC approach exhibits significantly improved spectral efficiency performance in the presence of beam-split than that of even fully digital non-SPIM beamformers.
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Impact of Evanescence Process on Three-Dimensional Sub-Diffusion based Molecular Communication Channel(IEEE Transactions on NanoBioscience, Institute of Electrical and Electronics Engineers (IEEE), 2023-03-21) [Article]In most of the existing works of molecular communication (MC), the standard diffusion environment is taken into account where the mean square displacement (MSD) of an information molecule (IM) scales linearly with time. On the contrary, this work considers the sub-diffusion motion that appears in crowded and complex (porous or fractal) environments (movement of the particles in the living cells) where the particle’s MSD scales as a fractional order power law in time. Moreover, we examine an additional evanescence process resulting from which the molecules can degrade before hitting the boundary of the receiver (RX). Thus, in this work, we present a 3D MC system with a point transmitter (TX) and the spherical RX with the sub-diffusive behavior of an IM along with its evanescence. Furthermore, an IM’s closed-form expressions for the arrival probability and the first passage time density (FPTD) are emulated in the above context. Additionally, we investigate the performance of MC by using the concentration-based modulation technique in a sub-diffusion channel. Finally, the considered MC channel is exploited in terms of the probability of detection, probability of false alarm, and probability of error for different parameters such as the reaction rate, fractional power, and radius of the RX.
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UAV Assisted IoT Geo-positioning Solution Employing Low-Cost Bluetooth Enabled Tags(IEEE, 2023-03-20) [Conference Paper]Technology integration has enabled value-added services and quality-of-life enhancement in almost all aspects of modern life. In this paper, we present a UAV and low-cost Bluetooth low energy (BLE) tags-based location search system which enables a cart take-home service for shoppers of a supermarket in a model smart colony. The presented system has quality-of-life enhancement as well as carbon footprint reduction effects and can be integrated with the existing security and/or transport system of the model smart colony. Conducted field trials on location accuracy of the system are also presented, showing that carts left by residents outside the home can be located within 6.58m and carts taken inside homes or buildings can be located within 16.43m.
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Resident Population Density-Inspired Deployment of K-tier Aerial Cellular Network(IEEE Transactions on Wireless Communications, Institute of Electrical and Electronics Engineers (IEEE), 2023-03-20) [Article]Using Unmanned Aerial Vehicles (UAVs) to enhance network coverage has proven a variety of benefits compared to terrestrial counterparts. One of the commonly used mathematical tools to model the locations of the UAVs is stochastic geometry (SG). However, in the existing studies, both users and UAVs are often modeled as homogeneous point processes. In this paper, we consider an inhomogeneous Poisson point process (PPP)-based model for the locations of the users that captures the degradation in the density of active users as we move away from the town center. In addition, we propose the deployment of aerial vehicles following the same inhomogeneity of the users to maximize the performance. In addition, a multi-tier network model is also considered to make better use of the rich space resources. Then, the analytical expressions of the coverage probability for a typical user and the total coverage probability are derived. Finally, we optimize the coverage probability with limitations of the total number of UAVs and the minimum local coverage probability. Finally we give the optimal UAV distribution parameters when the maximum overall coverage probability is reached.
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Flexible self-powered DUV photodetectors with high responsivity utilizing Ga2O3/NiO heterostructure on buffered Hastelloy substrates(Applied Physics Letters, AIP Publishing, 2023-03-20) [Article]In this research, β-Ga2O3/NiO heterostructures were grown directly on CeO2 buffered Hastelloy flexible substrates. With pulsed laser deposition under high temperatures, as-grown β-Ga2O3 and NiO thin films have a preferred out-of-plane orientation along the ⟨−201⟩ and ➎111➉ directions. This is due to the ideal epitaxial ability of the CeO2 buffer layer, which serves as a perfect template for the epitaxial growth of single-oriented NiO and β-Ga2O3 by creating a constant gradient from CeO2 (2.7 Å along ➎001➉) to NiO (2.9 Å along ➎110➉), and eventually to β-Ga2O3 (3.04 Å along ➎010➉). The Hastelloy substrates endow photodetectors with good deformability and mechanical robustness. Moreover, owing to the type-II band alignment of β-Ga2O3/NiO heterostructures, the photodetectors have a good photocurrent at zero bias under 284 nm of light illumination. In addition, the photocurrent is significantly higher than when using an analogous heterostructure (as described in some previous reports), because the β-Ga2O3 and NiO thin films are crystalized along a single orientation with fewer defects.
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Computationally Budgeted Continual Learning: What Does Matter?(arXiv, 2023-03-20) [Preprint]Continual Learning (CL) aims to sequentially train models on streams of incoming data that vary in distribution by preserving previous knowledge while adapting to new data. Current CL literature focuses on restricted access to previously seen data, while imposing no constraints on the computational budget for training. This is unreasonable for applications in-the-wild, where systems are primarily constrained by computational and time budgets, not storage. We revisit this problem with a large-scale benchmark and analyze the performance of traditional CL approaches in a compute-constrained setting, where effective memory samples used in training can be implicitly restricted as a consequence of limited computation. We conduct experiments evaluating various CL sampling strategies, distillation losses, and partial fine-tuning on two large-scale datasets, namely ImageNet2K and Continual Google Landmarks V2 in data incremental, class incremental, and time incremental settings. Through extensive experiments amounting to a total of over 1500 GPU-hours, we find that, under compute-constrained setting, traditional CL approaches, with no exception, fail to outperform a simple minimal baseline that samples uniformly from memory. Our conclusions are consistent in a different number of stream time steps, e.g., 20 to 200, and under several computational budgets. This suggests that most existing CL methods are particularly too computationally expensive for realistic budgeted deployment.
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Ti3C2Tx MXene van der Waals gate contact for GaN high electron mobility transistors(Advanced Materials, Wiley, 2023-03-20) [Article]Gate controllability is a key factor that determines the performance of GaN high electron mobility transistors (HEMTs). However, at traditional metal-GaN interface, direct chemical interaction between metal and GaN can result in fixed charges and traps, which can significantly deteriorate the gate controllability. In this study, Ti3C2Tx MXene films were integrated into GaN HEMTs as the gate contact, wherein van der Waals heterojunctions were formed between MXene films and GaN without direct chemical bonding. The GaN HEMTs with enhanced gate controllability exhibited an extremely low off-state current (IOFF) of 10−7 mA/mm, a record high ION/IOFF current ratio of ∼1013 (which is six orders of magnitude higher than conventional Ni/Au contact), a high off-state drain breakdown voltage of 1085 V, and a near-ideal subthreshold swing of 61 mV/dec. This work shows the great potential of MXene films as gate electrodes in wide-bandgap semiconductor devices.
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Customizable Graphite-on-Paper based Keypads: Toward Disposable and Recyclable Wireless Human-Machine Interfaces(IEEE Journal on Flexible Electronics, Institute of Electrical and Electronics Engineers (IEEE), 2023-03-17) [Article]There is a rapid increase in the use of affordable electronic devices and human-machine interfaces (HMIs) with short serviceable life in almost every aspect of our lives. It’s estimated that the Waste Electrical and Electronic Equipment (WEEE) and e-waste generated in year 2021 was 57.5 million metric tons (Mt) and it is expected that the production of e-waste will increase to 110 Mt by the end of 2050. To mitigate these wastes, green HMIs are required which can be customized for multiple applications and can be recycled or disposed of with minimal environmental impact. This work presents customizable graphite-on-paper (GOP) based keypad consists of interdigitated capacitive (IDC) touch sensors is demonstrated as HMIs to interact with different electronic and media applications wirelessly. The GOP keypads are fabricated through facile and green fabrication process by direct writing of graphite on flexible paper substrate. The GOP keypads can be fabricated in a home setting as the required materials are readily available, i.e., paper, pencils, Arduino. The GOP keypads can be easily disposed of or recycled at the end of its life or requirement due to the employment of biodegradable materials like paper and graphite. The IDC touch sensors are optimized by analyzing the number of electrode fingers, finger’s width, finger’s overlap length and spacing between the electrode fingers. The same GOP keypad is customized to interact with different electronic and media applications wirelessly i.e., laptop cursor navigation, calculator app on mobile, numeric keypad etc. The customizable GOP keypads have potential to be used as green wireless HMIs to enforce a circular economy by mitigating electronic and plastic waste, which leads to the vision of a sustainable and green world.
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Deep Reinforcement Learning Based Beamforming Codebook Design for RIS-aided mmWave Systems(IEEE, 2023-03-17) [Conference Paper]Reconfigurable intelligent surfaces (RISs) are envisioned to play a pivotal role in future wireless systems with the capability of enhancing propagation environments by intelligently reflecting the signals toward the target receivers. However, the optimal tuning of the phase shifters at the RIS is a challenging task due to the passive nature of reflective elements and the high complexity of acquiring channel state information (CSI). Conventionally, wireless systems rely on pre-defined reflection beamforming codebooks for both initial access and data transmission. However, these existing pre-defined codebooks are commonly not adaptive to the environments. Moreover, identifying the best beam is typically performed using an exhaustive search that leads to high beam training overhead. To address these issues, this paper develops a multi-agent deep reinforcement learning framework that learns how to jointly optimize the active beamforming from the BS and the RIS-reflection beam codebook relying only on the received power measurements. To accelerate learning convergence and reduce the search space, the proposed model divides the RIS into multiple partitions and associates beam patterns to the surrounding environments with low computational complexity. Simulation results show that the proposed learning framework can learn optimized active BS beamforming and RIS reflection codebook. For instance, the proposed MA-DRL approach with only 6 beams outperforms a 256-beam discrete Fourier transform (DFT) codebook with a 97% beam training overhead reduction.
