pwc-archive/papers-with-abstracts huggingface dataset:
Analysis of Scalable Anomalous Reflectors through Ray Tracing and Measurements
Authors: Le Hao, Sravan K. R. Vuyyuru, Sergei A. Tretyakov, Markus Rupp, Risto Valkonen
Date: 2024-07-24 00:00:00

In this study, we elaborate on the concept of scalable anomalous reflector (AR) to analyze the angular response, frequency response, and spatial scalability of a designed AR across a broad range of angles and frequencies. We utilize theoretical models and ray tracing simulations to investigate the communication performance of two different-sized scalable finite ARs, one smaller configuration with 48 x 48 array of unit cells and the other constructed by combining four smaller ARs to form a larger array with 96 x 96 unit cells. To validate the developed theoretical approach, we conducted measurements in an auditorium to evaluate the received power through an AR link at different angles and frequencies. In addition, models of scalable deflectors are implemented in the MATLAB ray tracer to simulate the measurement scenario. The results from theoretical calculations and ray tracing simulations achieve good agreement with measurement results.
Near-Field Integrated Sensing and Communication with Extremely Large-Scale Antenna Array
Authors: Haocheng Hua, Jie Xu, Rui Zhang
Date: 2024-07-24 00:00:00
Tasks: Integrated sensing and communication, ISAC

This paper studies a near-field integrated sensing and communication (ISAC) system with extremely large-scale antenna array (ELAA), in which a base station (BS) deployed with enormous number of antennas transmits wireless signals to communicate with multiple communication users (CUs) and simultaneously uses the echo signals to localize multiple point targets in the three-dimension (3D) space. To balance the performance tradeoff between communication and target localization, we design the transmit covariance matrix at the BS to optimize the localization performance while ensuring the signal-to-interference-plus-noise ratio (SINR) constraints at individual CUs. In particular, we formulate three design problems by considering different 3D localization performance metrics, including minimizing the sum Cram\'er-Rao bound (CRB), maximizing the minimum target illumination power, and maximizing the minimum target echo signal power. Although the three design problems are non-convex in general, we obtain their global optimal solutions via the technique of semi-definite relaxation (SDR). It is shown that the three problems have low-rank solution structures depending on the sensing and communication channel matrices, helping reduce the complexity of the SDR-based solutions. Interestingly, we find that in the special case with a single collocated target/CU present towards the middle of a symmetric uniform planar array (UPA), the optimal solutions to the three problems become identical to the SINR-maximization design and have a closed form, while in other cases they can be different in general. Besides, when the target/CU moves away from the transmitter/receiver, the CRB may first decrease and then increase. These two phenomena differ from those in the far-field. Numerical results show the benefits of the proposed designs for near-field ISAC, by exploiting the beam focusing capabilities of ELAA.
Wavelet-based Autoencoder and EfficientNet for Schizophrenia Detection from EEG Signals
Authors: Umesh Kumar Naik M, Shaik Rafi Ahamed
Date: 2024-07-24 00:00:00
Tasks: EEG, Transfer Learning

Schizophrenia (SZ) is a complex mental disorder that necessitates accurate and timely diagnosis for effective treatment. Traditional methods for SZ classification often struggle to capture transient EEG features and face high computational complexity. This study proposes a convolutional autoencoder (CAE) to address these challenges by reducing dimensionality and computational complexity. Additionally, we introduce a novel approach utilizing spectral scalograms (SS) combined with EfficientNet (ENB) architectures. The SS, obtained through continuous wavelet transform, reveals temporal and spectral information of EEG signals, aiding in the identification of transient features. ENB models, through transfer learning (TL), extract discriminative features and improve SZ classification accuracy. Experimental evaluation on a comprehensive dataset demonstrates the efficacy of our approach, achieving a five-fold mean cross-validation accuracy of 98.5\% using CAE with a soft voting classifier and 99\% employing SS with the ENB7 model. These results suggest the potential of our methods to enhance SZ diagnosis, surpassing traditional deep learning (DL) and TL techniques. By leveraging CAE and ENBs, this research offers a robust framework for objective SZ classification, promoting early intervention and improved patient outcomes.
Resource Allocation for 5G-UAV Based Emergency Wireless Communications
Authors: Zhuohui Yao, Wenchi Cheng, Wei zhang, Hailin Zhang
Date: 2024-07-24 00:00:00

For unforeseen natural disasters, such as earthquakes, hurricanes, and floods, etc., the traditional communication infrastructure is unavailable or seriously disrupted along with persistent secondary disasters. Under such circumstances, it is highly demanded to deploy emergency wireless communication (EWC) networks to restore connectivity in accident/incident areas. The emerging fifth-generation (5G)/beyond-5G (B5G) wireless communication system, like unmanned aerial vehicle (UAV) assisted networks and intelligent reflecting surface (IRS) based communication systems, are expected to be designed or re-farmed for supporting temporary high quality communications in post-disaster areas. However, the channel characteristics of post-disaster areas quickly change as the secondary disaster resulted topographical changes, imposing new but critical challenges for EWC networks. In this paper, we propose a novel heterogeneous $\mathcal{F}$ composite fading channel model for EWC networks which accurately models and characterizes the composite fading channel with reflectors, path-loss exponent, fading, and shadowing parameters in 5G-UAV based EWC networks. Based on the model, we develop the optimal power allocation scheme with the simple closed-form expression and the numerical results based optimal joint bandwidth-power allocation scheme. We derive the corresponding capacities and compare the energy efficiency between IRS and traditional relay based 5G-UAVs. Numerical results show that the new heterogeneous Fisher-Snedecor $\mathcal{F}$ composite fading channel adapted resource allocation schemes can achieve higher capacity and energy efficiency than those of traditional channel model adapted resource allocation schemes, thus providing better communications service for post-disaster areas.
Efffcient Sensing Parameter Estimation with Direct Clutter Mitigation in Perceptive Mobile Networks
Authors: Hang Li, Hongming Yang, Qinghua Guo, J. Andrew Zhang, Yang Xiang, Yashan Pang
Date: 2024-07-24 00:00:00
Tasks: parameter estimation

In this work, we investigate sensing parameter estimation in the presence of clutter in perceptive mobile networks (PMNs) that integrate radar sensing into mobile communications. Performing clutter suppression before sensing parameter estimation is generally desirable as the number of sensing parameters can be signiffcantly reduced. However, existing methods require high-complexity clutter mitigation and sensing parameter estimation, where clutter is ffrstly identiffed and then removed. In this correspondence, we propose a much simpler but more effective method by incorporating a clutter cancellation mechanism in formulating a sparse signal model for sensing parameter estimation. In particular, clutter mitigation is performed directly on the received signals and the unitary approximate message passing (UAMP) is leveraged to exploit the common support for sensing parameter estimation in the formulated sparse signal recovery problem. Simulation results show that, compared to state-of-theart methods, the proposed method delivers signiffcantly better performance while with substantially reduced complexity.
Multi-Frequency Resonant Circuit Based Multi-User Emergency Through-the-Earth Communication with Magnetic Induction
Authors: Zhenyu Wang, Jianyu Wang, Wenchi Cheng
Date: 2024-07-24 00:00:00

Magnetic induction (MI) is an effective technique in emergency through-the-earth communications due to the higher penetration efficiency and lower propagation loss as compared with electromagnetic wave communication. How to cancel the interference between different users and enhance the effectiveness of multi-user transmissions is imperative for the practical application of MI communication. In this paper, we use multi-frequency resonant circuit to establish multiple resonant frequencies for MI communication. The transmissions corresponding to different users operate at different resonant frequencies and multi-user interferences can be naturally mitigated. Numerical results verify our theoretical analyses and show that the proposed system can significantly enhance the performance.
Virtual Full-Duplex Wireless Communications with Zero-Interval Modulation and Sampling
Authors: Jianyu Wang, Wenchi Cheng, Wei zhang, Hailin Zhang
Date: 2024-07-24 00:00:00

In this paper, we propose a virtual full-duplex (VFD) technique with zero-interval modulation and sampling (ZIMS), where two half-duplex (HD) transceivers can simultaneously transmit signals and each transceiver can effectively receive the desired information. In ZIMS-VFD, the transceiver inserts a zero-interval for each symbol in the transmit signal and provides self-interference (SI)-free intervals for itself. Meanwhile, it samples the receive signal in the provided SI-free intervals and restores the desired symbols. Based on orthogonal frequency division multiplexing (OFDM), we formulate the system model and show the transmit signal structure. Then, we give the transceiver design for single input single output (SISO) ZIMS-VFD and extend it to multiple input multiple output (MIMO) communications. Numerical results verify our theoretical analyses and show that ZIMS-VFD can effectively increase the capacity and approach the FD without SI.
Subspace Constrained Variational Bayesian Inference for Structured Compressive Sensing with a Dynamic Grid
Authors: An Liu, Yufan Zhou, Wenkang Xu
Date: 2024-07-24 00:00:00
Tasks: Bayesian Inference, compressed sensing, Compressive Sensing

We investigate the problem of recovering a structured sparse signal from a linear observation model with an uncertain dynamic grid in the sensing matrix. The state-of-the-art expectation maximization based compressed sensing (EM-CS) methods, such as turbo compressed sensing (Turbo-CS) and turbo variational Bayesian inference (Turbo-VBI), have a relatively slow convergence speed due to the double-loop iterations between the E-step and M-step. Moreover, each inner iteration in the E-step involves a high-dimensional matrix inverse in general, which is unacceptable for problems with large signal dimensions or real-time calculation requirements. Although there are some attempts to avoid the high-dimensional matrix inverse by majorization minimization, the convergence speed and accuracy are often sacrificed. To better address this problem, we propose an alternating estimation framework based on a novel subspace constrained VBI (SC-VBI) method, in which the high-dimensional matrix inverse is replaced by a low-dimensional subspace constrained matrix inverse (with the dimension equal to the sparsity level). We further prove the convergence of the SC-VBI to a stationary solution of the Kullback-Leibler divergence minimization problem. Simulations demonstrate that the proposed SC-VBI algorithm can achieve a much better tradeoff between complexity per iteration, convergence speed, and performance compared to the state-of-the-art algorithms.
Joint Active and Passive Beamforming Design for IRS-aided MIMO ISAC Based on Sensing Mutual Information
Authors: Jin Li, Gui Zhou, Tantao Gong, Nan Liu, Rui Zhang
Date: 2024-07-23 00:00:00
Tasks: Integrated sensing and communication, ISAC

In this paper, we investigate the intelligent reflecting surface (IRS)/reconfigurable intelligent surface (RIS)-aided integrated sensing and communication (ISAC) system based on sensing mutual information (MI). Specifically, the base station (BS) perceives the sensing target via the reflected sensing signal by the IRS, while communicating with the users simultaneously. Our aim is to maximize the sensing MI, subject to the quality of service (QoS) constraints for all communication users, the transmit power constraint at the BS, and the unit-modulus constraint on the IRS's passive reflection. We solve this problem under two cases: one simplified case assuming a line-of-sight (LoS) channel between the BS and IRS and no clutter interference to sensing, and the other generalized case considering the Rician fading channel of the BS-IRS link and the presence of clutter interference to sensing. For the first case, we prove that the dedicated sensing beamformer is unnecessary for improving sensing MI and develop a low-complexity iterative algorithm to jointly optimize the BS and IRS active/passive beamformers. Then, for the second case, we propose an alternative iterative algorithm, which can also be applied to the first case, to solve the beamforming design problem under the general setup. Numerical results are provided to validate the performance of the proposed algorithms, as compared to various benchmark schemes.
Multi-Beam Symbol-Level Secure Communication for Hybrid Near- and Far-Field Communications
Authors: Wensheng Deng, Bin Qiu, Wenchi Cheng
Date: 2024-07-23 00:00:00

This paper introduces a multi-beam secure communication scheme for mixed near-field and far-field (hNF) scenarios, primarily designed to address the challenges faced by sixth-generation (6G) networks in simultaneously managing near-field and far-field communications. This method significantly reduces the signal quality at eavesdroppers(Eves) while ensuring high-quality reception for legitimate users, effectively enhancing communication security. At the transmitter, this study employs multi-beam symbol-level directional modulation to ensure secure and reliable transmission in a mixed eavesdropping environment. Given the uncertainty about eavesdropper information, the transmission beamforming vectors are specially designed to meet specific symbol-level constraints, thereby ensuring effective reception for legitimate users. Experimental and simulation results demonstrate the effectiveness of our approach in improving secrecy performance, reducing transmission power, and enhancing energy efficiency, offering a practical solution to the security challenges faced by future wireless networks.
Performance Limits for Signals of Opportunity-Based Navigation
Authors: Francesco Zanirato, Francesco Ardizzon, Laura Crosara, Alessio Curzio, Luca Canzian, Stefano Tomasin, Nicola Laurenti
Date: 2024-07-23 00:00:00

This paper investigates the potential of non-terrestrial and terrestrial signals of opportunity (SOOP) for navigation applications. Non-terrestrial SOOP analysis employs modified Cram\`er-Rao lower bound (MCRLB) to establish a relationship between SOOP characteristics and the accuracy of ranging information. This approach evaluates hybrid navigation module performance without direct signal simulation. The MCRLB is computed for ranging accuracy, considering factors like propagation delay, frequency offset, phase offset, and angle-of-arrival (AOA), across diverse non-terrestrial SOOP candidates. Additionally, Geometric Dilution of Precision (GDOP) and low earth orbit (LEO) SOOP availability are assessed. Validation involves comparing MCRLB predictions with actual ranging measurements obtained in a realistic simulated scenario. Furthermore, a qualitative evaluation examines terrestrial SOOP, considering signal availability, accuracy attainability, and infrastructure demands.
Neural field equations with time-periodic external inputs and some applications to visual processing
Authors: Maria Virginia Bolelli, Dario Prandi
Date: 2024-07-24 00:00:00

The aim of this work is to present a mathematical framework for the study of flickering inputs in visual processing tasks. When combined with geometric patterns, these inputs influence and induce interesting psychophysical phenomena, such as the MacKay and the Billock-Tsou effects, where the subjects perceive specific afterimages typically modulated by the flickering frequency. Due to the symmetry-breaking structure of the inputs, classical bifurcation theory and multi-scale analysis techniques are not very effective in our context. We thus take an approach based on the input-output framework of control theory for Amari-type neural fields. This allows us to prove that, when driven by periodic inputs, the dynamics converge to a periodic state. Moreover, we study under which assumptions these nonlinear dynamics can be effectively linearised, and in this case we present a precise approximation of the integral kernel for short-range excitatory and long-range inhibitory neuronal interactions. Finally, for inputs concentrated at the center of the visual field with a flickering background, we directly relate the width of the illusory contours appearing in the afterimage with both the flickering frequency and the strength of the inhibition.
Equilibrium control theory for Kihlstrom-Mirman preferences in continuous time
Authors: Luca De Gennaro Aquino, Sascha Desmettre, Yevhen Havrylenko, Mogens Steffensen
Date: 2024-07-23 00:00:00

In intertemporal settings, the multiattribute utility theory of Kihlstrom and Mirman suggests the application of a concave transform of the lifetime utility index. This construction, while allowing time and risk attitudes to be separated, leads to dynamically inconsistent preferences. We address this issue in a game-theoretic sense by formalizing an equilibrium control theory for continuous-time Markov processes. In these terms, we describe the equilibrium strategy and value function as the solution of an extended Hamilton-Jacobi-Bellman system of partial differential equations. We verify that (the solution of) this system is a sufficient condition for an equilibrium and examine some of its novel features. A consumption-investment problem for an agent with CRRA-CES utility showcases our approach.
The need to implement FAIR principles in biomolecular simulations
Authors: Rommie Amaro, Johan Åqvist, Ivet Bahar, Federica Battistini, Adam Bellaiche, Daniel Beltran, Philip C. Biggin, Massimiliano Bonomi, Gregory R. Bowman, Richard Bryce, Giovanni Bussi, Paolo Carloni, David Case, Andrea Cavalli, Chie-En A. Chang, Thomas E. Cheatham III, Margaret S. Cheung, Cris Chipot, Lillian T. Chong, Preeti Choudhary, Gerardo Andres Cisneros, Cecilia Clementi, Rosana Collepardo-Guevara, Peter Coveney, Roberto Covino, T. Daniel Crawford, Matteo Dal Peraro, Bert de Groot, Lucie Delemotte, Marco De Vivo, Jonathan Essex, Franca Fraternali, Jiali Gao, Josep Lluís Gelpí, Francesco Luigi Gervasio, Fernando Danilo Gonzalez-Nilo, Helmut Grubmüller, Marina Guenza, Horacio V. Guzman, Sarah Harris, Teresa Head-Gordon, Rigoberto Hernandez, Adam Hospital, Niu Huang, Xuhui Huang, Gerhard Hummer, Javier Iglesias-Fernández, Jan H. Jensen, Shantenu Jha, Wanting Jiao, William L. Jorgensen, Shina Caroline Lynn Kamerlin, Syma Khalid, Charles Laughton, Michael Levitt, Vittorio Limongelli, Erik Lindahl, Kresten Lindorff-Larsen, Sharon Loverde, Magnus Lundborg, Yun Lyna Luo, Francisco Javier Luque, Charlotte I. Lynch, Alexander MacKerell, Alessandra Magistrato, Siewert J. Marrink, Hugh Martin, J. Andrew McCammon, Kenneth Merz, Vicent Moliner, Adrian Mulholland, Sohail Murad, Athi N. Naganathan, Shikha Nangia, Frank Noe, Agnes Noy, Julianna Oláh, Megan O'Mara, Mary Jo Ondrechen, José N. Onuchic, Alexey Onufriev, Silvia Osuna, Anna R. Panchenko, Sergio Pantano, Carol Parish, Michele Parrinello, Alberto Perez, Tomas Perez-Acle, Juan R. Perilla, B. Montgomery Pettitt, Adriana Pietropalo, Jean-Philip Piquemal, Adolfo Poma, Matej Praprotnik, Maria J. Ramos, Pengyu Ren, Nathalie Reuter, Adrian Roitberg, Edina Rosta, Carme Rovira, Benoit Roux, Ursula Röthlisberger, Karissa Y. Sanbonmatsu, Tamar Schlick, Alexey K. Shaytan, Carlos Simmerling, Jeremy C. Smith, Yuji Sugita, Katarzyna Świderek, Makoto Taiji, Peng Tao, D. Peter Tieleman, Irina G. Tikhonova, Julian Tirado-Rives, Inaki Tunón, Marc W. Van Der Kamp, David van der Spoel, Sameer Velankar, Gregory A. Voth, Rebecca Wade, Ariel Warshel, Valerie Vaissier Welborn, Stacey Wetmore, Travis J. Wheeler, Chung F. Wong, Lee-Wei Yang, Martin Zacharias, Modesto Orozco
Date: 2024-07-23 00:00:00

This letter illustrates the opinion of the molecular dynamics (MD) community on the need to adopt a new FAIR paradigm for the use of molecular simulations. It highlights the necessity of a collaborative effort to create, establish, and sustain a database that allows findability, accessibility, interoperability, and reusability of molecular dynamics simulation data. Such a development would democratize the field and significantly improve the impact of MD simulations on life science research. This will transform our working paradigm, pushing the field to a new frontier. We invite you to support our initiative at the MDDB community (https://mddbr.eu/community/) Now published as: Amaro, R.E., et al. The need to implement FAIR principles in biomolecular simulations. Nat Methods (2025) https://doi.org/10.1038/s41592-025-02635-0
Assessment of scoring functions for computational models of protein-protein interfaces
Authors: Jacob Sumner, Grace Meng, Naomi Brandt, Alex T. Grigas, Andrés Córdoba, Mark D. Shattuck, Corey S. O'Hern
Date: 2024-07-23 00:00:00

A goal of computational studies of protein-protein interfaces (PPIs) is to predict the binding site between two monomers that form a heterodimer. The simplest version of this problem is to rigidly re-dock the bound forms of the monomers, which involves generating computational models of the heterodimer and then scoring them to determine the most native-like models. Scoring functions have been assessed previously using rank- and classification-based metrics, however, these methods are sensitive to the number and quality of models in the scoring function training set. We assess the accuracy of seven PPI scoring functions by comparing their scores to a measure of structural similarity to the x-ray crystal structure (i.e. the DockQ score) for a non-redundant set of heterodimers from the Protein Data Bank. For each heterodimer, we generate re-docked models uniformly sampled over DockQ and calculate the Spearman correlation between the PPI scores and DockQ. For some targets, the scores and DockQ are highly correlated; however, for many targets, there are weak correlations. Several physical features can explain the difference between difficult- and easy-to-score targets. For example, strong correlations exist between the score and DockQ for targets with highly intertwined monomers and many interface contacts. We also develop a new score based on only three physical features that matches or exceeds the performance of current PPI scoring functions. These results emphasize that PPI prediction can be improved by focusing on correlations between the PPI score and DockQ and incorporating more discriminating physical features into PPI scoring functions.