pwc-archive/papers-with-abstracts huggingface dataset:
Multi-Objective System-by-Design for mm-Wave Automotive Radar Antennas
Authors: P. Rosatti, M. Salucci, L. Poli, A. Massa
Date: 2022-03-02 00:00:00
Tasks: Computational Efficiency

The computationally-efficient solution of multi-objective optimization problems (MOPs) arising in the design of modern electromagnetic (EM) microwave devices is addressed. Towards this end, a novel System-by-Design (SbD) method is developed to effectively explore the solution space and to provide the decision maker with a set of optimal trade-off solutions minimizing multiple and (generally) contrasting objectives. The proposed MO-SbD method proves a high computational efficiency, with a remarkable time saving with respect to a competitive state-of-the-art MOP solution strategy, thanks to the "smart" integration of evolutionary-inspired concepts and operators with artificial intelligence (AI) and machine learning (ML) techniques. Representative numerical results are reported to provide the interested users with useful insights and guidelines on the proposed optimization method as well as to assess its effectiveness in designing mm-wave automotive radar antennas.
Multi-Scale Single-Bit RP-EMS Synthesis for Advanced Propagation Manipulation through System-by-Design
Authors: G. Oliveri, P. Rocca, M. Salucci, D. Erricolo, A. Massa
Date: 2022-03-02 00:00:00

A new method for synthesizing Single-Bit Reconfigurable Passive Electromagnetic Skins (1RP-EMSs) featuring advanced beam shaping capabilities is proposed. By using single-bit unit cells, the multi-scale problem of controlling 1RP-EMSs is formulated as a two-phase process. First, the macro-scale synthesis of the discrete surface current that radiates the electromagnetic (EM) field fitting user-designed requirements is performed by means of an innovative quantized version of the iterative projection method (QIPM). Successively, the meta-atom states of the 1RP-EMS are optimized with a customized implementation of the System-by-Design paradigm to yield a 1RP-EMS that supports such a feasible reference current. A representative set of numerical results is reported to assess the effectiveness of the proposed approach in designing and controlling single-bit meta-atom RP-EMSs that enable complex wave manipulations.
A machine learning accelerated inverse design of underwater acoustic polyurethane coatings with cylindrical voids
Authors: Hansani Weeratunge, Zakiya Shireen, Sagar Iyer, Richard Sandberg, Saman Halgamuge, Adrian Menzel, Andrew Phillips, Elnaz Hajizadeh
Date: 2022-03-02 00:00:00

Here, we report the development of a detailed "Materials Informatics" framework for the design of acoustic coatings for underwater sound attenuation through integrating Machine Learning (ML) and statistical optimization algorithms with a Finite Element Model (FEM). The finite element models were developed to simulate the realistic performance of the acoustic coatings based on polyurethane (PU) elastomers with embedded cylindrical voids. The FEM results revealed that the frequency-dependent viscoelastic behavior of the polyurethane matrix has a significant impact on the magnitude and frequency of the absorption peak associated with the cylinders at low frequencies, which has been commonly ignored in previous studies on similar systems. The data generated from the FEM was used to train a Deep Neural Network (DNN) to accelerate the design process, and subsequently, was integrated with a Genetic Algorithm (GA) to determine the optimal geometric parameters of the cylinders to achieve maximized, broadband, low-frequency waterborne sound attenuation. A significant, broadband, low-frequency attenuation is achieved by optimally configuring the layers of cylindrical voids and using attenuation mechanisms, including Fabry-P\'erot resonance and Bragg scattering of the layers of voids. Integration of the machine learning technique into the optimization algorithm further accelerated the exploration of the high dimensional design space for the targeted performance. The developed DNN exhibited significantly increased speed (by a factor of $4.5\times 10^3$ ) in predicting the absorption coefficient compared to the conventional FEM(s). Therefore, the acceleration brought by the materials informatics framework brings a paradigm shift to the design and development of acoustic coatings compared to the conventional trial-and-error practices.
High Noise Immune Time-domain Inversion via Cascade Network (TICaN) for Complex Scatterers
Authors: Hongyu Gao, Yinpeng Wang, Qiang Ren, Zixi Wang, Liangcheng Deng, Chenyu Shi
Date: 2022-03-03 00:00:00
Tasks: Denoising, GPU

In this paper, a high noise immune time-domain inversion cascade network (TICaN) is proposed to reconstruct scatterers from the measured electromagnetic fields. The TICaN is comprised of a denoising block aiming at improving the signal-to-noise ratio, and an inversion block to reconstruct the electromagnetic properties from the raw time-domain measurements. The scatterers investigated in this study include complicated geometry shapes and high contrast, which cover the stratum layer, lossy medium and hyperfine structure, etc. After being well trained, the performance of the TICaN is evaluated from the perspective of accuracy, noise-immunity, computational acceleration, and generalizability. It can be proven that the proposed framework can realize high-precision inversion under high-intensity noise environments. Compared with traditional reconstruction methods, TICaN avoids the tedious iterative calculation by utilizing the parallel computing ability of GPU and thus significantly reduce the computing time. Besides, the proposed TICaN has certain generalization ability in reconstructing the unknown scatterers such as the famous Austria rings. Herein, it is confident that the proposed TICaN will serve as a new path for real-time quantitative microwave imaging for various practical scenarios.
Re-ordering of Hadamard matrix using Fourier transform and gray-level co-occurrence matrix for compressive single-pixel imaging
Authors: Pedro G. Vaz, Andreia Gaudêncio, L. F. Requicha Ferreira, Anne Humeau-Heurtier, Miguel Morgado, João Cardoso
Date: 2022-03-09 00:00:00
Tasks: Image Quality Assessment, Image Reconstruction

One of the most active research fields in single-pixel imaging is the influence of the sampling basis and its order in the quality of the reconstructed images. This paper presents two new orders, ascending scale (AS) and ascending inertia (AI), of the Hadamard basis and test their performance, using simulation and experimental methods, for low sampling ratios (0.5 to 0.01). These orders were compared with two state-of-the-art orders, cake-cutting (CC) and total gradient (TG), using TVAL3 as the reconstruction algorithm and three noise levels. These newly proposed orders have better reconstructed image quality on the simulation data set (110 images) and achieved structure similarity index values higher than CC order. The experimental data set (2 images) showed that the AS and AI orders performed better with a sampling ratio of 0.5, while for lower sampling ratio the performance of AS, AI and CC was similar. The TG order performed worst in the majority of the cases. Finally, the simulation results present clear evidence that peak signal-to-noise ratio (PSNR) is not a reliable image quality assessment (IQA) metric to assess image reconstruction quality in the context of single pixel imaging.
Window Filtering Algorithm for Pulsed Light Coherent Combining of Low Repetition Frequency
Authors: Jiali Zhang, Jie Cao, Qun Hao, Yang Cheng, Liquan Dong, Bin Han, Xuesheng Liu
Date: 2022-03-03 00:00:00

The multi-dithering method has been well verified in phase locking of polarization coherent combination experiment. However, it is hard to apply to low repetition frequency pulsed lasers, since there exists an overlap frequency domain between pulse laser and the amplitude phase noise and traditional filters cannot effectively separate phase noise. Aiming to solve the problem in this paper, we propose a novel method of pulse noise detection, identification, and filtering based on the autocorrelation characteristics between noise signals. In the proposed algorithm, a self-designed window algorithm is used to identify the pulse, and then the pulse signal group in the window is replaced by interpolation, which effectively filter the pulse signal doped in the phase noise within 0.1 ms. After filtering the pulses in the phase noise, the phase difference of two pulsed beams (10 kHz) is successfully compensated to zero in 1 ms, and the coherent combination of closed-loop phase lock is realized. At the same time, the phase correction times are few, the phase lock effect is stable, and the final light intensity increases to the ideal value (0.9 Imax).
Non-Smooth Integrability Theory
Authors: Yuhki Hosoya
Date: 2022-03-09 00:00:00

We study a method for calculating the utility function from a candidate of a demand function that is not differentiable, but is locally Lipschitz. Using this method, we obtain two new necessary and sufficient conditions for a candidate of a demand function to be a demand function. The first concerns the Slutsky matrix, and the second is the existence of a concave solution to a partial differential equation. Moreover, we show that the upper semi-continuous weak order that corresponds to the demand function is unique, and that this weak order is represented by our calculated utility function. We provide applications of these results to econometric theory. First, we show that, under several requirements, if a sequence of demand functions converges to some function with respect to the metric of compact convergence, then the limit is also a demand function. Second, the space of demand functions that have uniform Lipschitz constants on any compact set is compact under the above metric. Third, the mapping from a demand function to the calculated utility function becomes continuous. We also show a similar result on the topology of pointwise convergence.
Multi-Material Blind Beam Hardening Correction Based on Non-Linearity Adjustment of Projections
Authors: Ammar Alsaffar, Kaicong Sun, Sven Simon
Date: 2022-03-09 00:00:00
Tasks: Computed Tomography (CT)

Beam hardening (BH) is one of the major artifacts that severely reduces the quality of Computed Tomography (CT) imaging. In a polychromatic X-ray beam, since low-energy photons are more preferentially absorbed, the attenuation of the beam is no longer a linear function of the absorber thickness. The existing BH correction methods either require a given material, which might be unfeasible in reality, or they require a long computation time. This work aims to propose a fast and accurate BH correction method that requires no prior knowledge of the materials and corrects first and higher-order BH artifacts. In the first step, a wide sweep of the material is performed based on an experimentally measured look-up table to obtain the closest estimate of the material. Then the non-linearity effect of the BH is corrected by adding the difference between the estimated monochromatic and the polychromatic simulated projections of the segmented image. The estimated monochromatic projection is simulated by selecting the energy from the polychromatic spectrum which produces the lowest mean square error (MSE) with the acquired projection from the scanner. The polychromatic projection is estimated by minimizing the difference between the acquired projection and the weighted sum of the simulated polychromatic projections using different spectra of different filtration. To evaluate the proposed BH correction method, we have conducted extensive experiments on the real-world CT data. Compared to the state-of-the-art empirical BH correction method, the experiments show that the proposed method can highly reduce the BH artifacts without prior knowledge of the materials.
PRINCE: A Pruned AMP Integrated Deep CNN Method for Efficient Channel Estimation of Millimeter-wave and Terahertz Ultra-Massive MIMO Systems
Authors: Zhengdong Hu, Yuhang Chen, Chong Han
Date: 2022-03-09 00:00:00

Millimeter-wave (mmWave) and Terahertz (THz)-band communications exploit the abundant bandwidth to fulfill the increasing data rate demands of 6G wireless communications. To compensate for the high propagation loss with reduced hardware costs, ultra-massive multiple-input multiple-output (UM-MIMO) with a hybrid beamforming structure is a promising technology in the mmWave and THz bands. However, channel estimation (CE) is challenging for hybrid UM-MIMO systems, which requires recovering the high-dimensional channels from severely few channel observations. In this paper, a Pruned Approximate Message Passing (AMP) Integrated Deep Convolutional-neural-network (DCNN) CE (PRINCE) method is firstly proposed, which enhances the estimation accuracy of the AMP method by appending a DCNN network. Moreover, by truncating the insignificant feature maps in the convolutional layers of the DCNN network, a pruning method including training with regularization, pruning and refining procedures is developed to reduce the network scale. Simulation results show that the PRINCE achieves a good trade-off between the CE accuracy and significantly low complexity, with normalized-mean-square-error (NMSE) of $-10$ dB at signal-to-noise-ratio (SNR) as $10$ dB after eliminating $80\%$ feature maps.
Differential Chaos Shift Keying-based Wireless Power Transfer over a Frequency Selective Channel
Authors: Priyadarshi Mukherjee, Constantinos Psomas, Ioannis Krikidis
Date: 2022-03-09 00:00:00

This paper studies the performance of a differential chaos shift keying (DCSK)-based wireless power transfer (WPT) setup in a frequency selective scenario. Particularly, by taking into account the nonlinearities of the energy harvesting (EH) process and a generalized frequency selective Nakagami-m fading channel, we derive closed-form analytical expressions for the harvested energy in terms of the transmitted waveform and channel parameters. A simplified closed-form expression for the harvested energy is also obtained for a scenario, where the delay spread is negligible in comparison to the transmit symbol duration. Nontrivial design insights are provided, where it is shown how the power delay profile of the channel as well as the parameters of the transmitted waveform affect the EH performance. Our results show that a frequency selective channel is comparatively more beneficial for WPT compared to a flat fading scenario. However, a significant delay spread negatively impacts the energy transfer.
Weighted Sum Age of Information Minimization in Wireless Networks with Aerial IRS
Authors: Wanting Lyu, Yue Xiu, Songjie Yang, Phee Lep Yeoh, Yonghui Li
Date: 2022-03-09 00:00:00
Tasks: Scheduling

In this letter, we analyze a terrestrial wireless communication network assisted by an aerial intelligent reflecting surface (IRS). We consider a packet scheduling problem at the ground base station (BS) aimed at improving the information freshness by selecting packets based on their AoI. To further improve the communication quality, the trajectory of the unmanned aerial vehicle (UAV) which carries the IRS is optimized with joint active and passive beamforming design. To solve the formulated non-convex problem, we propose an iterative alternating optimization problem based on a successive convex approximation (SCA) algorithm. The simulation results shows significant performance improvement in terms of weighted sum AoI, and the SCA solution converges quickly with low computational complexity.
Millimeter-Scale Ultra-Low-Power Imaging System for Intelligent Edge Monitoring
Authors: Andrea Bejarano-Carbo, Hyochan An, Kyojin Choo, Shiyu Liu, Qirui Zhang, Dennis Sylvester, David Blaauw, Hun-Seok Kim
Date: 2022-03-09 00:00:00
Tasks: Data Compression, Event Detection, Management

Millimeter-scale embedded sensing systems have unique advantages over larger devices as they are able to capture, analyze, store, and transmit data at the source while being unobtrusive and covert. However, area-constrained systems pose several challenges, including a tight energy budget and peak power, limited data storage, costly wireless communication, and physical integration at a miniature scale. This paper proposes a novel 6.7$\times$7$\times$5mm imaging system with deep-learning and image processing capabilities for intelligent edge applications, and is demonstrated in a home-surveillance scenario. The system is implemented by vertically stacking custom ultra-low-power (ULP) ICs and uses techniques such as dynamic behavior-specific power management, hierarchical event detection, and a combination of data compression methods. It demonstrates a new image-correcting neural network that compensates for non-idealities caused by a mm-scale lens and ULP front-end. The system can store 74 frames or offload data wirelessly, consuming 49.6$\mu$W on average for an expected battery lifetime of 7 days.
A Study of Multihop mmW Aerial Backhaul Links
Authors: Mohammad Taghi Dabiri, Mazen Omar Hasna, Tamer Khattab, Khalid Qaraqe
Date: 2022-03-08 00:00:00

The main contribution of this paper is to analyze a long networked flying platform (NFP)-based millimeter wave (mmWave) backhaul link that is offered as a cost effective and easy to deploy solution to connect a disaster or remote area to the nearest core network. For this aim, we characterize the backhaul channel as a function of realistic physical parameters such as heights and distances of obstacles along the route, flight altitude and the intensity of NFPs' vibrations, the real 3D antenna pattern provided by 3GPP, etc. For the characterized channel, we derive an analytical closed-form expression for the outage probability. Finally, using the obtained results, we provide a fast algorithm for the optimal parameter design of the considered system that minimizes the cost.
Long mmWave Backhaul Connectivity Using Fixed-Wing UAVs
Authors: Mohammad Taghi Dabiri, Mazen Omar Hasna, Nizar Zorba, Tamer Khattab
Date: 2022-03-08 00:00:00

This paper discusses the analysis of a fixed-wing unmanned aerial vehicle (UAV)-based millimeter wave (mmWave) backhaul link, that is offered as a cost-effective and easy deploy the solution to connect a disaster or remote area to the nearest core network. We present the optimal design of a relay system based on fixed-wing UAV, taking into account the actual channel parameters such as the UAV vibrations, tracking error, real 3GPP antenna pattern, UAV's height, flight path, and the effect of physical obstacles. The performance of the considered system is evaluated in terms of outage probability and the channel capacity while taking into account the impact of the system parameters such as optimal selection of UAV flight path and antenna patterns.
Intelligent resonance tracking of a microwave plasmonic resonator for compact wireless sensors
Authors: Xuanru Zhang, Jia Wen Zhu, Tie Jun Cui
Date: 2022-03-03 00:00:00

Plasmonic sensing has been in the spotlight for decades, the concept and applications of which have been generalized to spoof surface plasmons (SSPs) in the microwave band. Here, we report a compact and wireless sensor within a printed circuit board size of 18 mm * 12 mm, tracking the resonance frequency shift of a microwave plasmonic resonator via a software-defined scheme. The microwave plasmonic resonator yields a deep-subwavelength size, enhanced sensitivity, and a good electromagnetic compatibility performance. The software-defined resonance tracking scheme minimalizes the hardware circuit and the consumed spectrum resources, and makes the detection intelligently adaptive to the target resonance, with a signal-to-noise ratio of 69 dB and a data rate of 2272 measuring points per second. The sensor has been validated via acetone vapor concentration sensing, while its applications can be widely extended by replacing the transducer materials. This approach provides compact, sensitive, accurate and intelligent solutions for resonant sensors in the Internet of things (IoT).
Sub-THz Channel Measurements at 158 GHz and 300 GHz in a Street Canyon Environment
Authors: Wilhelm Keusgen, Alper Schultze, Michael Peter, Taro Eichler
Date: 2022-03-02 00:00:00

This paper presents first results of a channel measurement campaign performed in an urban micro (UMi) street canyon scenario at 158 GHz and 300 GHz.
Observations on the Angular Statistics of the Indoor Sub-THz Radio Channel at 158 GHz
Authors: Alper Schultze, Wilhelm Keusgen, Michael Peter, Taro Eichler
Date: 2022-03-02 00:00:00

This paper presents selected results from a channel measurement campaign conducted in a shopping mall scenario at 158 GHz. The focus is on the statistical analysis of the collected measurement data in terms of directional channel gain. Although most power is received from the line-of-sight (LOS) direction, significant multipaths arrive from all measured azimuth directions. The median of the sorted directional channel gain can be approximated by a linear curve showing an offset of about 10 dB with respect to the LOS direction.
A preparative mass spectrometer to deposit intact large native protein complexes
Authors: Paul Fremdling, Tim K. Esser, Bodhisattwa Saha, Alexander Makarov, Kyle Fort, Maria Reinhardt-Szyba, Joseph Gault, Stephan Rauschenbach
Date: 2022-03-09 00:00:00

Electrospray ion-beam deposition (ES-IBD) is a versatile tool to study structure and reactivity of molecules from small metal clusters to large protein assemblies. It brings molecules gently into the gas phase where they can be accurately manipulated and purified, followed by controlled deposition onto various substrates. In combination with imaging techniques, direct structural information of well-defined molecules can be obtained, which is essential to test and interpret results from indirect mass spectrometry techniques. To date, ion-beam deposition experiments are limited to a small number of custom instruments worldwide, and there are no commercial alternatives. Here we present a module that adds ion-beam deposition capabilities to a popular commercial MS platform (Thermo Scientific$^{\mathrm{TM}}$ Q Exactive$^{\mathrm{TM}}$ UHMR). This combination significantly reduces the overhead associated with custom instruments, while benefiting from established high performance and reliability. We present current performance characteristics including beam intensity, landing-energy control, and deposition spot size for a broad range of molecules. In combination with atomic force microscopy (AFM) and transmission electron microscopy (TEM), we distinguish near-native from unfolded proteins and show retention of native shape of protein assemblies after dehydration and deposition. Further, we use an enzymatic assay to quantify activity of an non-covalent protein complex after deposition an a dry surface. Together, these results indicate a great potential of ES-IBD for applications in structural biology, but also outline the challenges that need to be solved for it to reach its full potential.