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The advent of 5G positioning techniques by 3GPP has unlocked possibilities for applications in public safety, vehicular systems, and location-based services. However, these applications demand accurate and reliable positioning performance, which has led to the proposal of newer positioning techniques. To further advance the research on these techniques, in this paper, we develop a 3GPP-compliant 5G positioning testbed, incorporating gNodeBs (gNBs) and User Equipment (UE). The testbed uses New Radio (NR) Positioning Reference Signals (PRS) transmitted by the gNB to generate Time of Arrival (TOA) estimates at the UE. We mathematically model the inter-gNB and UE-gNB time offsets affecting the TOA estimates and examine their impact on positioning performance. Additionally, we propose a calibration method for estimating these time offsets. Furthermore, we investigate the environmental impact on the TOA estimates. Our findings are based on our mathematical model and supported by experimental results., Comment: 8 pages, 9 figures, Accepted in ACM Wintech 2024

Quantum illumination (QI) is an entanglement-based protocol for improving lidar/radar detection of unresolved targets beyond what a classical lidar/radar of the same average transmitted energy can do. Originally proposed by Lloyd as a discrete-variable quantum lidar, it was soon shown that his proposal offered no quantum advantage over its best classical competitor. Continuous-variable, specifically Gaussian-state, QI has been shown to offer true quantum advantage, both in theory and in table-top experiments. Moreover, despite its considerable drawbacks, the microwave version of Gaussian-state QI continues to attract research attention. Recently, however, Pannu et al. (arXiv:2407.08005 [quant-ph]) have: (1) combined the entangled state from Lloyd's QI with the channel models from Gaussian-state QI; (2) proposed a new positive operator-valued measurement for that composite setup; and (3) claimed that, unlike Gaussian-state QI, their QI achieves the Nair-Gu lower bound on QI target-detection error probability at all noise brightnesses. Pannu et al.'s analysis was asymptotic, i.e., it presumed infinite-dimensional entanglement. This paper works out the finite-dimensional performance of Pannu et al.'s QI. It shows that there is a threshold value for the entangled-state dimensionality below which there is no quantum advantage, and above which the Nair-Gu bound is approached asymptotically. Moreover, with both systems operating with error-probability exponents 1 dB lower than the Nair-Gu bound's, Pannu et al.'s QI requires much higher entangled-state dimensionality than does Gaussian-state QI to achieve useful error probabilities in both high-brightness (100 photons/mode) and moderate-brightness (1 photon/mode) noise. Furthermore, neither system has appreciable quantum advantage in low-brightness (<<1 photon/mode) noise., Comment: 12 pages, 3 figures

Wireless positioning in Non-Line-of-Sight (NLOS) scenarios is highly challenging due to multipath, which leads to deterioration in the positioning estimate. This study reexamines electromagnetic field principles and applies them to wireless positioning, resulting in new techniques that enhance positioning accuracy in NLOS scenarios. Further, we use the proposed method to analyze a public safety scenario where it is essential to determine the position of at-risk individuals within buildings, emphasizing improving the Z-axis position estimate. Our analysis uses the Geometrical Theory of Diffraction (GTD) to provide important signal propagation insights and develop a new NLOS path model. Next, we use Fisher information to derive necessary and sufficient conditions for 3D positioning using our proposed positioning technique and finally to lower bound the possible 3D and z-axis positioning performance. On applying this positioning technique in a public safety scenario, we show that it is possible to greatly improve both 3D and Z-axis positioning performance by directly estimating NLOS path lengths.

Quantum illumination (QI) is the task of querying a scene using a transmitter probe whose quantum state is entangled with a reference beam retained in ideal storage, followed by optimally detecting the target-returned light together with the stored reference, to make decisions on characteristics of targets at stand-off range, at precision that exceeds what is achievable with a classical transmitter of the same brightness and otherwise identical conditions. Using tools from perturbation theory, we show that in the limit of low transmitter brightness, high loss, and high thermal background, there is a factor of four improvement in the Chernoff exponent of the error probability in discriminating any number of apriori-known reflective targets when using a Gaussian-state entangled QI probe, over using classical coherent-state illumination (CI). While this advantage was known for detecting the presence or absence of a target, it had not been proven for the generalized task of discriminating between arbitrary target libraries. In proving our result, we derive simple general analytic expressions for the lowest-order asymptotic expansions of the quantum Chernoff exponents for QI and CI in terms of the signal brightness, loss, thermal noise, and the modal expansion coefficients of the target-reflected light's radiant exitance profiles when separated by a spatial mode sorter after entering the entrance pupil of the receiver's aperture., Comment: 6 pages, 2 figures, presented at ISIT 2024

High-rate, high-fidelity entanglement distribution is essential to the creation of a quantum internet, but recent achievements in fiber and satellite-based entanglement distribution fall far short of what is needed. Chen et al. [Phys. Rev. Appl. 19, 054209 (2023)] proposed a means for dramatically increasing entanglement-distribution rates via zero added-loss multiplexing (ZALM). ZALM's quantum transmitter employs a pair of Sagnac-configured spontaneous parametric downconverters (SPDCs), channelization via dense wavelength-division multiplexing (DWDM) filtering, and partial Bell-state measurements (BSMs) to realize a heralded source of frequency-multiplexed polarization-entangled biphotons. Each biphoton is transmitted to Alice and Bob with a classical message identifying its frequency channel and the heralded entangled state. Their quantum receivers use DWDM filtering and mode conversion to interface their received biphotons to intra-cavity color-center quantum memories. This paper delves deeply into ZALM's SPDCs, partial-BSMs, and loading of Alice and Bob's quantum memories. It derives the density operators for the SPDC sources and the quantum memories, allowing heralding probability, heralding efficiency, and fidelity to be evaluated for both the polarization-entangled biphotons and the loaded quantum memories, thus enabling exploration of the parameter space for optimizing ZALM performance. Even without optimization analysis, the paper already demonstrates two critical features of the ZALM architecture: the necessity of achieving a near-separable channelized biphoton wave function to ensure the biphoton sent to Alice and Bob is of high purity; and the premium placed on Alice and Bob's temporal-mode converters' enabling narrowband push-pull memory loading to ensure the arriving biphoton's state is faithfully transferred to the intra-cavity color centers., Comment: 26 pages, 15 figure, 1 table

We reexamine the well-known Duan-Kimble entanglement scheme, wherein the state of a single-photon qubit is entangled with a quantum memory consisting of a single-atom qubit in a strongly coupled optical cavity, providing the capability to load the photon's state into the memory. We correct a common error appearing in some subsequent papers regarding the validity of the single-photon reflectivity function that characterizes the essential phase shift at the heart of the protocol. Using the validated analytical solution, we introduce an improved scheme-the push-pull configuration-where the photon and cavity are tuned at the midpoint between atomic resonances and show that it can outperform the original on-off configuration in which the photon and cavity are tuned exactly to one of the atomic resonances. The performance metric used is the final memory-state fidelity versus the heralding probability, which determines the memory loading rate. The results should play a role in optimizing future quantum repeater schemes based on the Duan-Kimble protocol.

Enhancing 3D and Z-axis positioning accuracy is crucial for effective rescue in indoor emergencies, ensuring safety for emergency responders and at-risk individuals. Additionally, reducing the dependence of a positioning system on fixed infrastructure is crucial, given its vulnerability to power failures and damage during emergencies. Further challenges from a signal propagation perspective include poor indoor signal coverage, multipath effects and the problem of Non-Line-OfSight (NLOS) measurement bias. In this study, we utilize the mobility provided by a rapidly deployable Uncrewed Aerial Vehicle (UAV) based wireless network to address these challenges. We recognize diffraction from window edges as a crucial signal propagation mechanism and employ the Geometrical Theory of Diffraction (GTD) to introduce a novel NLOS path length model. Using this path length model, we propose two different techniques to improve the indoor positioning performance for emergency scenarios., Comment: Accepted for publication in ICC 2024

This paper introduces ASCENT (context Aware Spectrum Coexistence Design and Implementation) toolset, an advanced context-aware terrestrial satellite spectrum sharing toolset designed for researchers, policymakers, and regulators. It serves two essential purposes (a) evaluating the potential for harmful interference to primary users in satellite bands and (b) facilitating the analysis, design, and implementation of diverse regulatory policies on spectrum usage and sharing. Notably, ASCENT implements a closed-loop feedback system that allows dynamic adaptation of policies according to a wide range of contextual factors (e.g., weather, buildings, summer/winter foliage, etc.) and feedback on the impact of these policies through realistic simulation. Specifically, ASCENT comprises the following components (i) interference evaluation tool for evaluating interference at the incumbents in a spectrum-sharing environment while taking the underlying contexts, (ii) dynamic spectrum access (DSA) framework for providing context-aware instructions to adapt networking parameters and control secondary terrestrial network's access to the shared spectrum band according to context aware prioritization, (iii) Context broker to acquire essential and relevant contexts from external context information providers; and (iv) DSA Database to store dynamic and static contexts and the regulator's policy information. The closed-loop feedback system of ASCENT is implemented by integrating these components in a modular software architecture. A case study of sharing the lower 12 GHz Ku band (12.2-12.7 GHz) with the 5G terrestrial cellular network is considered, and the usability of ASCENT is demonstrated by dynamically changing exclusion zone's radius in different weather conditions.

Purpose: One of the major reasons that totally implantable cochlear microphones are not readily available is the lack of good implantable microphones. An implantable microphone has the potential to provide a range of benefits over external microphones for cochlear implant users including the filtering ability of the outer ear, cosmetics, and usability in all situations. This paper presents results from experiments in human cadaveric ears of a piezofilm microphone concept under development as a possible component of a future implantable microphone system for use with cochlear implants. This microphone is referred to here as a drum microphone (DrumMic) that senses the robust and predictable motion of the umbo, the tip of the malleus. Methods: The performance was measured of five DrumMics inserted in four different human cadaveric temporal bones. Sensitivity, linearity, bandwidth, and equivalent input noise were measured during these experiments using a sound stimulus and measurement setup. Results: The sensitivity of the DrumMics was found to be tightly clustered across different microphones and ears despite differences in umbo and middle ear anatomy. The DrumMics were shown to behave linearly across a large dynamic range (46 dB SPL to 100 dB SPL) across a wide bandwidth (100 Hz to 8 kHz). The equivalent input noise (0.1-10 kHz) of the DrumMic and amplifier referenced to the ear canal was measured to be 54 dB SPL and estimated to be 46 dB SPL after accounting for the pressure gain of the outer ear. Conclusion: The results demonstrate that the DrumMic behaves robustly across ears and fabrication. The equivalent input noise performance was shown to approach that of commercial hearing aid microphones. To advance this demonstration of the DrumMic concept to a future prototype implantable in humans, work on encapsulation, biocompatibility, connectorization will be required.

Objective: We present the "UmboMic," a prototype piezoelectric cantilever microphone designed for future use with totally-implantable cochlear implants. Methods: The UmboMic sensor is made from polyvinylidene difluoride (PVDF) because of its low Young's modulus and biocompatibility. The sensor is designed to fit in the middle ear and measure the motion of the underside of the eardrum at the umbo. To maximize its performance, we developed a low noise charge amplifier in tandem with the UmboMic sensor. This paper presents the performance of the UmboMic sensor and amplifier in fresh cadaveric human temporal bones. Results: When tested in human temporal bones, the UmboMic apparatus achieves an equivalent input noise of 32.3 dB SPL over the frequency range 100 Hz to 7 kHz, good linearity, and a flat frequency response to within 10 dB from about 100 Hz to 6 kHz. Conclusion: These results demonstrate the feasibility of a PVDF-based microphone when paired with a low-noise amplifier. The reported UmboMic apparatus is comparable in performance to a conventional hearing aid microphone. Significance: The proof-of-concept UmboMic apparatus is a promising step towards creating a totally-implantable cochlear implant. A completely internal system would enhance the quality of life of cochlear implant users.

Non-terrestrial network (NTN) communication has garnered considerable attention from government entities, industries, and academia in recent times. NTN networks encompass a variety of systems, including Low Earth Orbit (LEO) satellites, Medium Earth Orbit (MEO) satellites, Geostationary Earth Orbit (GEO) satellites, High Altitude Platforms (HAPS), and Low Altitude Platforms (LAPS). Furthermore, the deployment of high-throughput satellites (HTS/VHTS) in the GEO space has gained momentum. While LEO and MEO satellites offer advantages such as low latency and reduced launching costs compared to GEO satellites, this study focuses on GEO satellites due to their stationary nature and broader coverage. In traditional cellular networks, each user equipment (UE) is allocated at least one resource block (RB), which is not shared with other UEs. However, in NTN communications, where the coverage area is extensive, dedicating an RB to only one UE is an inefficient utilization of radio resources. To address this challenge, fractional programming (FP), cognitive radio, and rate splitting multiple access (RSMA) are existing technologies. This paper aims to maximize spectral efficiency, average RBG rate, and sum rate for GEO satellite systems. However, achieving this objective involves dealing with a non-convex, NP-hard problem, as it requires the logarithmic sum of different fractions. Finding a global solution to such an NP-hard problem presents significant challenges. This paper introduces a novel alternate fractional programming algorithm specifically designed to tackle these complex NP-hard problems in the context of GEO NTN cellular networks. By employing this innovative approach, the study seeks to contribute to the optimization of NTN communication systems, enabling efficient resource allocation and improved network performance.

We study the problem of Byzantine fault tolerance in a distributed optimization setting, where there is a group of $N$ agents communicating with a trusted centralized coordinator. Among these agents, there is a subset of $f$ agents that may not follow a prescribed algorithm and may share arbitrarily incorrect information with the coordinator. The goal is to find the optimizer of the aggregate cost functions of the honest agents. We will be interested in studying the local gradient descent method, also known as federated learning, to solve this problem. However, this method often returns an approximate value of the underlying optimal solution in the Byzantine setting. Recent work showed that by incorporating the so-called comparative elimination (CE) filter at the coordinator, one can provably mitigate the detrimental impact of Byzantine agents and precisely compute the true optimizer in the convex setting. The focus of the present work is to provide theoretical results to show the convergence of local gradient methods with the CE filter in a nonconvex setting. We will also provide a number of numerical simulations to support our theoretical results.

In part II, an op-amp-based drive is proposed and designed. Subsequently, a very accurate model for the drive circuit and the current loop is developed as a simulation platform, while its simplified version is derived, tailored for efficient design purposes. Through a comprehensive evaluation, the accuracy and efficacy of both the actuator and drive circuit modeling is scrutinized, showcasing their superiorities over existing approaches. The importance of eddy current modeling is underscored. Also, the effectiveness of the designed current loop and its practical trade-offs are engineered and discussed. Then, three DSP-based position control techniques are implemented: pole placement with voltage drive, pole placement with current drive, and nonlinear control with feed linearization. Both full-order and reduced-order observers are leveraged to estimate the unmeasured states. The performance of control designs across various applications are evaluated through indices such as rise time, overshoot, steady-state error, and large-signal tracking in the step response as well as bandwidth, robustness, phase margin, sensitivity, disturbance rejection, and noise rejection in the frequency domain. The distinctive features of implemented control strategy are compared, offering a nuanced discussion of their respective advantages and drawbacks, shedding light on their potential applications.

This paper presents analytical modeling and design of a high-acceleration, low-vibration slotless double-sided linear motor with an arbitrary Halbach array for lithography machines used in semiconductor manufacturing technology. Amperian current and magnetic charge models of permanent magnets are integrated into a hybrid approach to develop comprehensive analytical modeling. Unlike conventional methods that treat magnets as sources for Poisson's equations, the solution is reduced to Laplace's equations, with magnets being represented as boundary conditions. The magnetic fields and potentials within distinct regions, along with machine quantities such as shear stress, force-angle characteristics, torque profile, attraction force, misalignment force, and back-EMF, are derived, comprehensively analyzed, and compared to FEM results for accuracy validation. In addition, two models based on Poisson's equations in terms of scalar and vector potentials are derived, compared, and analyzed. Finally, design optimization and sensitivity analysis of a linear stage for lithography applications are discussed.

Electromechanical models are crucial in the design and control of motors and actuators. Modeling, identification, drive, and current control loop of a limited-rotation actuator with magnetic restoration is presented. New nonlinear and linearized electromechanical models are developed for the design of the drive as well as small and large signal controls of the actuator. To attain a higher accuracy and an efficient design, and the eddy-currents in the laminations and magnet are modeled. This involves analytically solving 1-D and 2-D diffusion equations, leading to the derivation of a lumped-element circuit for system-level analyses, such as control system design. Additionally, the study analyzes and incorporates the impact of pre-sliding friction. The actuator is prototyped, and the paper delves into the identification of the model, presenting a procedure for parameter extraction. A close agreement is observed between the results obtained from the model, finite element analysis, and experimental results. The superiority of the proposed model over previous approaches is highlighted. Part II of the paper is dedicated to the drive circuit, the current control, as well as linear and nonlinear position control system designs.

Time series anomaly detection is challenging due to the complexity and variety of patterns that can occur. One major difficulty arises from modeling time-dependent relationships to find contextual anomalies while maintaining detection accuracy for point anomalies. In this paper, we propose a framework for unsupervised time series anomaly detection that utilizes point-based and sequence-based reconstruction models. The point-based model attempts to quantify point anomalies, and the sequence-based model attempts to quantify both point and contextual anomalies. Under the formulation that the observed time point is a two-stage deviated value from a nominal time point, we introduce a nominality score calculated from the ratio of a combined value of the reconstruction errors. We derive an induced anomaly score by further integrating the nominality score and anomaly score, then theoretically prove the superiority of the induced anomaly score over the original anomaly score under certain conditions. Extensive studies conducted on several public datasets show that the proposed framework outperforms most state-of-the-art baselines for time series anomaly detection., Comment: NeurIPS 2023 (https://neurips.cc/virtual/2023/poster/70582)

High time-bandwidth product signal and idler pulses comprised of independent identically distributed two-mode squeezed vacuum (TMSV) states are readily produced by spontaneous parametric downconversion. These pulses are virtually unique among entangled states in that they offer quantum performance advantages -- over their best classical-state competitors -- in scenarios whose loss and noise break their initial entanglement. Broadband TMSV states' quantum advantage derives from its signal and idler having a strongly nonclassical phase-sensitive cross correlation, which leads to information bearing signatures in lossy, noisy scenarios stronger than what can be obtained from classical-state systems of the same transmitted energy. Previous broadband TMSV receiver architectures focused on converting phase-sensitive cross correlation into phase-insensitive cross correlation, which can be measured in second-order interference. In general, however, these receivers fail to deliver broadband TMSV states' full quantum advantage, even if they are implemented with ideal equipment. This paper introduces the correlation-to-displacement receiver -- a new architecture comprised of a correlation-to-displacement converter, a programmable mode selector, and a coherent-state information extractor -- that can be configured to achieve quantum optimal performance in known sensing and communication protocols for which broadband TMSV provides quantum advantage that is robust against entanglement-breaking loss and noise., Comment: 15+17 pages, 12+9 figures. A preliminary version of the manuscript can be found in arXiv:2207.06609

The widespread proliferation of mmW devices has led to a surge of interest in antenna arrays. This interest in arrays is due to their ability to steer beams in desired directions, for the purpose of increasing signal-power and/or decreasing interference levels. To enable beamforming, array coefficients are typically stored in look-up tables (LUTs) for subsequent referencing. While LUTs enable fast sweep times, their limited memory size restricts the number of beams the array can produce. Consequently, a receiver is likely to be offset from the main beam, thus decreasing received power, and resulting in sub-optimal performance. In this letter, we present BeamShaper, a deep neural network (DNN) framework, which enables fast and accurate beamsteering in any desirable 3-D direction. Unlike traditional finite-memory LUTs which support a fixed set of beams, BeamShaper utilizes a trained NN model to generate the array coefficients for arbitrary directions in \textit{real-time}. Our simulations show that BeamShaper outperforms contemporary LUT based solutions in terms of cosine-similarity and central angle in time scales that are slightly higher than LUT based solutions. Additionally, we show that our DNN based approach has the added advantage of being more resilient to the effects of quantization noise generated while using digital phase-shifters., Comment: 7 pages, 5 figures, accepted to Milcom2023. Not published yet(Sep 2023)

High-dimensional quantum entanglement is a cornerstone for advanced technology enabling large-scale noise-tolerant quantum systems, fault-tolerant quantum computing, and distributed quantum networks. The recently developed biphoton frequency comb (BFC) provides a powerful platform for high-dimensional quantum information processing in its spectral and temporal quantum modes. Here we propose and generate a singly-filtered high-dimensional BFC via spontaneous parametric down-conversion by spectrally shaping only the signal photons with a Fabry-Perot cavity. High-dimensional energy-time entanglement is verified through Franson-interference recurrences and temporal correlation with low-jitter detectors. Frequency- and temporal- entanglement of our singly-filtered BFC is then quantified by Schmidt mode decomposition. Subsequently, we distribute the high-dimensional singly-filtered BFC state over a 10 km fiber link with a post-distribution time-bin dimension lower bounded to be at least 168. Our demonstrations of high-dimensional entanglement and entanglement distribution show the capability of the singly-filtered quantum frequency comb for high-efficiency quantum information processing and high-capacity quantum networks., Comment: 30 pages, 4 figures

Cloud droplets containing ice-nucleating particles (INPs) may freeze at temperatures above the homogeneous freezing threshold temperature. This process, referred to as immersion freezing, is one of the modulators of aerosol-cloud interactions in the Earth's atmosphere. In modeling studies, immersion freezing is often described using either so-called "singular" or "time-dependent" parameterizations. Here, we juxtapose both approaches and discuss them in the context of probabilistic particle-based cloud microphysics modeling. First, using a box model, we contrast how both parameterizations respond to different idealized ambient cooling rate profiles and quantify the impact of the polydispersity of the immersed surface spectrum on the frozen fraction evolution. Second, using a prescribed-flow two-dimensional cloud model, we illustrate the implications of applying the singular model in simulations with flow regimes relevant to ambient cloud conditions rather than to the cloud-chamber experiments on which these parameterizations are built upon. We discuss the critical role of the attribute-space sampling strategy for particle-based model simulations in modeling heterogeneous ice nucleation which is contingent on the presence of relatively sparse immersed INPs. The key takeaways include: (i) The singular approach, constituting a time-integrated form of a more general time-dependent approach, is only applicable under a limited range of ambient cooling rates. (ii) The time-dependent approach, especially when based on water-activity, is suitable for integration with particle-based model components of detailed aerosol composition and collisional growth/breakup. (iii) A flow-coupled aerosol-budget-resolving simulation shows the benefits and challenges of modeling cloud condensation nuclei activation and immersion freezing on insoluble ice nuclei with super-particle methods.

Decentralized vehicle-to-everything (V2X) networks (i.e., C-V2X Mode-4 and NR-V2X Mode-2) utilize sensing-based semi-persistent scheduling (SPS) where vehicles sense and reserve suitable radio resources for Basic Safety Message (BSM) transmissions at prespecified periodic intervals termed as Resource Reservation Interval (RRI). Vehicles rely on these received periodic BSMs to localize nearby (transmitting) vehicles and infrastructure, referred to as cooperative awareness. Cooperative awareness enables line of sight and non-line of sight localization, extending a vehicle's sensing and perception range. In this work, we first show that under high vehicle density scenarios, existing SPS (with prespecified RRIs) suffer from poor cooperative awareness, quantified as tracking error. Decentralized vehicle-to-everything (V2X) networks (i.e., C-V2X Mode-4 and NR-V2X Mode-2) utilize sensing-based semi-persistent scheduling (SPS) where vehicles sense and reserve suitable radio resources for Basic Safety Message (BSM) transmissions at prespecified periodic intervals termed as Resource Reservation Interval (RRI). Vehicles rely on these received periodic BSMs to localize nearby (transmitting) vehicles and infrastructure, referred to as cooperative awareness. Cooperative awareness enables line of sight and non-line of sight localization, extending a vehicle's sensing and perception range. In this work, we first show that under high vehicle density scenarios, existing SPS (with prespecified RRIs) suffer from poor cooperative awareness, quantified as tracking error.