pwc-archive/papers-with-abstracts huggingface dataset:
Modeling and Performance Analysis of OAM-NFC Systems
Authors: Runyu Lyu, Wenchi Cheng, Wei zhang
Date: 2024-06-08 00:00:00

Due to its low energy consumption and simplicity, near field communication (NFC) has been extensively used in various short-range transmission scenarios, for example, proximity payment and NFC entrance guard. However, the low data rate of NFC limits its application in high rate demanded scenarios, such as high-resolution fingerprint identification and streaming media transmission as well as the future promising high rate indoor communications among pads, phones, and laptops. In this paper, we model and analyze the performance of the orbital angular momentum based NFC (OAM-NFC) system, which can significantly increase the capacity of NFC. We first give the OAM system model. With coils circularly equipped at the transmitter and receiver, OAM-NFC signals can be transmitted, received, and detected. Then, we develop the OAM-NFC generation and detection schemes for NFC multiplexing transmission. We also analyze the OAM-NFC channel capacity and compare it with those of single-input-single-output (SISO) as well as multi-input-multi-output (MIMO) NFC. Simulation results validate the feasibility and capacity enhancement of our proposed OAM-NFC system. How different variables, such as the transceiver misalignment, the numbers of transceiver coils, and transceiver distance, impact the OAM-NFC capacity are also analyzed.
OAM-SWIPT for IoE-Driven 6G
Authors: Runyu Lyu, Wenchi Cheng, Bazhong Shen, Zhiyuan Ren, Hailin Zhang
Date: 2024-06-08 00:00:00

Simultaneous wireless information and power transfer (SWIPT), which achieves both wireless energy transfer (WET) and information transfer, is an attractive technique for future Internet of Everything (IoE) in the sixth-generation (6G) mobile communications. With SWIPT, battery-less IoE devices can be powered while communicating with other devices. Line-of-sight (LOS) RF transmission and near-field inductive coupling based transmission are typical SWIPT scenarios, which are both LOS channels and without enough degree of freedom for high spectrum efficiency as well as high energy efficiency. Due to the orthogonal wavefronts, orbital angular momentum (OAM) can facilitate the SWIPT in LOS channels. In this article, we introduce the OAM-based SWIPT as well as discuss some basic advantages and challenges for it. After introducing the OAM-based SWIPT for IoE, we first propose an OAM-based SWIPT system model with the OAM-modes assisted dynamic power splitting (DPS). Then, four basic advantages regarding the OAM-based SWIPT are reviewed with some numerical analyses for further demonstrating the advantages. Next, four challenges regarding integrating OAM into SWIPT and possible solutions are discussed. OAM technology provides multiple orthogonal streams to increase both spectrum and energy efficiencies for SWIPT, thus creating many opportunities for future WET and SWIPT researches.
Joint Reflection and Power Splitting Optimization for RIS-assisted OAM-SWIPT
Authors: Runyu Lyu, Wenchi Cheng
Date: 2024-06-08 00:00:00

Simultaneous wireless information and power transfer (SWIPT) can enhance the spectrum and power efficiencies of wireless communications networks. Line-of-sight (LOS) transmission is a typical SWIPT scenario. However, the strong channel correlation limits the spectrum and energy efficiencies of SWIPT in the LOS channel. Due to the orthogonal wavefronts, orbital angular momentum (OAM) waves can facilitate the SWIPT in LOS channels. With the assistance of the reconfigurable intelligent surface (RIS), both the energy efficiency and capacity can be further improved for the OAM-SWIPT systems. In this paper, we model the RIS-assisted OAM-SWIPT transmission and derive the optimal reflection coefficients and power splitting ratio for it. We first give the system and channel models. Then, we propose the transmission scheme. Based on the transmission scheme, we formulate the capacity and energy harvesting (EH) trade-off problem. We solve the problem by developing an alternating optimization algorithm. Simulations validate the capacity and EH enhancements brought by the RIS for OAM-SWIPT.
Fractal OAM Generation and Detection Schemes
Authors: Runyu Lyu, Wenchi Cheng, Muyao Wang, Wei zhang
Date: 2024-06-08 00:00:00

Orbital angular momentum (OAM) carried electromagnetic waves have the potential to improve spectrum efficiency in optical and radio-frequency communications due to the orthogonal wavefronts of different OAM modes. However, OAM beams are vortically hollow and divergent, which significantly decreases the capacity of OAM transmissions. In addition, unaligned transceivers in OAM transmissions can result in a high bit error rate (BER). The Talbot effect is a self-imaging phenomenon that can be used to generate optical or radio-frequency OAM beams with periodic repeating structures at multiples of a certain distance along the propagation direction. These periodic structures make it unnecessary for the transceiver antennas to be perfectly aligned and can also alleviate the hollow divergence of OAM beams. In this paper, we propose Talbot-effect-based fractal OAM generation and detection schemes using a uniform circular array (UCA) to significantly improve capacity and BER performance in unaligned OAM transmissions. We first provide a brief overview of fractal OAM. Then, we propose the fractal OAM beam generation and detection schemes. Numerical analysis and simulations verify the effectiveness of our proposed fractal OAM generation scheme and also demonstrate improved capacity and BER performance compared to normal OAM transmissions. We also analyze how the receive UCA radius and the distance between the UCAs impact the capacity and BER performances.
Automatic modulation classification for MIMO system based on the mutual information feature extraction
Authors: N. Ussipov, S. Akhtanov, Z. Zhanabaev, D. Turlykozhayeva, B. Karibayev, T. Namazbayev, D. Almen, A. Akhmetali, X. Tang
Date: 2024-06-08 00:00:00

Automatic Modulation Classification (AMC) is an essential technology that is widely applied into various communications scenarios. In recent years, many Machine Learning and Deep-Learning methods have been introduced into AMC, and a lot of them apply different approaches to eliminate interference in complex Multiple-Input and Multiple-Output (MIMO) signals and improve classification performance. However, in practical communication systems, the perfect elimination of MIMO signal interference is impossible, and therefore classification performance suffers. In this paper, we propose a new AMC algorithm for MIMO system based on mutual information (MI) features extraction, which does not require a large amount of training data and the elimination of MIMO signal interference. In this approach, features based on mutual information are extracted using In-Phase and Quadrature (IQ) constellation diagrams of MIMO signals, which have not been explored previously. Our method can be effective since mutual information considers the interdependencies among variables and measures how much information about one variable reduces uncertainty about another, providing a valuable perspective for extracting higher-level and interesting features from the data. The effectiveness of our method is evaluated on several model and real-world datasets, and its applicability is proven.
A Pixel-based Reconfigurable Antenna Design for Fluid Antenna Systems
Authors: Jichen Zhang, Junhui Rao, Zhaoyang Ming, Zan Li, Chi-Yuk Chiu, Kai-Kit Wong, Kin-Fai Tong, Ross Murch
Date: 2024-06-08 00:00:00

Fluid Antenna Systems (FASs) have recently been proposed for enhancing the performance of wireless communication. Previous antenna designs to meet the requirements of FAS have been based on mechanically movable or liquid antennas and therefore have limited reconfiguration speeds. In this paper, we propose a design for a pixel-based reconfigurable antenna (PRA) that meets the requirements of FAS and the required switching speed. It can provide 12 FAS ports across 1/2 wavelength and consists of an E-slot patch antenna and an upper reconfigurable pixel layer with 6 RF switches. Simulation and experimental results from a prototype operating at 2.5 GHz demonstrate that the design can meet the requirements of FAS including port correlation with matched impedance.
From Analog to Digital: Multi-Order Digital Joint Coding-Modulation for Semantic Communication
Authors: Guangyi Zhang, Pujing Yang, Yunlong Cai, Qiyu Hu, Guanding Yu
Date: 2024-06-08 00:00:00
Tasks: Dimensionality Reduction, Quantization, Semantic Communication

Recent studies in joint source-channel coding (JSCC) have fostered a fresh paradigm in end-to-end semantic communication. Despite notable performance achievements, present initiatives in building semantic communication systems primarily hinge on the transmission of continuous channel symbols, thus presenting challenges in compatibility with established digital systems. In this paper, we introduce a novel approach to address this challenge by developing a multi-order digital joint coding-modulation (MDJCM) scheme for semantic communications. Initially, we construct a digital semantic communication system by integrating a multi-order modulation/demodulation module into a nonlinear transform source-channel coding (NTSCC) framework. Recognizing the non-differentiable nature of modulation/demodulation, we propose a novel substitution training strategy. Herein, we treat modulation/demodulation as a constrained quantization process and introduce scaling operations alongside manually crafted noise to approximate this process. As a result, employing this approximation in training semantic communication systems can be deployed in practical modulation/demodulation scenarios with superior performance. Additionally, we demonstrate the equivalence by analyzing the involved probability distribution. Moreover, to further upgrade the performance, we develop a hierarchical dimension-reduction strategy to provide a gradual information extraction process. Extensive experimental evaluations demonstrate the superiority of our proposed method over existing digital and non-digital JSCC techniques.
Harnessing Multimodal Sensing for Multi-user Beamforming in mmWave Systems
Authors: Kartik Patel, Robert W. Heath Jr
Date: 2024-06-07 00:00:00
Tasks: Sensor Fusion

Sensor-aided beamforming reduces the overheads associated with beam training in millimeter-wave (mmWave) multi-input-multi-output (MIMO) communication systems. Most prior work, though, neglects the challenges associated with establishing multi-user (MU) communication links in mmWave MIMO systems. In this paper, we propose a new framework for sensor-aided beam training in MU mmWave MIMO system. We leverage the beamspace representation of the channel that contains only the angles-of-departure (AoDs) of the channel's significant multipath components. We show that a deep neural network (DNN)-based multimodal sensor fusion framework can estimate the beamspace representation of the channel using sensor data. To aid the DNN training, we introduce a novel supervised soft-contrastive loss (SSCL) function that leverages the inherent similarity between channels to extract similar features from the sensor data for similar channels. Finally, we design an MU beamforming strategy that uses the estimated beamspaces of the channels to select analog precoders for all users in a way that prevents transmission to multiple users over the same directions. Compared to the baseline, our approach achieves more than 4$\times$ improvement in the median sum-spectral efficiency (SE) at 42 dBm equivalent isotropic radiated power (EIRP) with 4 active users. This demonstrates that sensor data can provide more channel information than previously explored, with significant implications for machine learning (ML)-based communication and sensing systems.
Holographic Intelligence Surface Assisted Integrated Sensing and Communication
Authors: Zhuoyang Liu, Yuchen Zhang, Haiyang Zhang, Feng Xu, Yonina C. Eldar
Date: 2024-06-07 00:00:00
Tasks: Integrated sensing and communication, ISAC

Traditional discrete-array-based systems fail to exploit interactions between closely spaced antennas, resulting in inadequate utilization of the aperture resource. In this paper, we propose a holographic intelligence surface (HIS) assisted integrated sensing and communication (HISAC) system, wherein both the transmitter and receiver are fabricated using a continuous-aperture array. A continuous-discrete transformation of the HIS pattern based on the Fourier transform is proposed, converting the continuous pattern design into a discrete beamforming design. We formulate a joint transmit-receive beamforming optimization problem for the HISAC system, aiming to balance the performance of multi-target sensing while fulfilling the performance requirement of multi-user communication. To solve the non-convex problem with coupled variables, an alternating optimization-based algorithm is proposed to optimize the HISAC transmit-receive beamforming in an alternate manner. Specifically, the transmit beamforming design is solved by decoupling into a series of feasibility-checking sub-problems while the receive beamforming is determined by the Rayleigh quotient-based method. Simulation results demonstrate the superiority of the proposed HISAC system over traditional discrete-array-based ISAC systems, achieving significantly higher sensing performance while guaranteeing predetermined communication performance.
Fast-Fading Channel and Power Optimization of the Magnetic Inductive Cellular Network
Authors: Honglei Ma, Erwu Liu, Zhijun Fang, Rui Wang, Yongbin Gao, Wenjun Yu, Dongming Zhang
Date: 2024-06-07 00:00:00
Tasks: Q-Learning

The cellular network of magnetic Induction (MI) communication holds promise in long-distance underground environments. In the traditional MI communication, there is no fast-fading channel since the MI channel is treated as a quasi-static channel. However, for the vehicle (mobile) MI (VMI) communication, the unpredictable antenna vibration brings the remarkable fast-fading. As such fast-fading cannot be modeled by the central limit theorem, it differs radically from other wireless fast-fading channels. Unfortunately, few studies focus on this phenomenon. In this paper, using a novel space modeling based on the electromagnetic field theorem, we propose a 3-dimension model of the VMI antenna vibration. By proposing ``conjugate pseudo-piecewise functions'' and boundary $p(x)$ distribution, we derive the cumulative distribution function (CDF), probability density function (PDF) and the expectation of the VMI fast-fading channel. We also theoretically analyze the effects of the VMI fast-fading on the network throughput, including the VMI outage probability which can be ignored in the traditional MI channel study. We draw several intriguing conclusions different from those in wireless fast-fading studies. For instance, the fast-fading brings more uniformly distributed channel coefficients. Finally, we propose the power control algorithm using the non-cooperative game and multiagent Q-learning methods to optimize the throughput of the cellular VMI network. Simulations validate the derivation and the proposed algorithm.
A Simple Channel Independent Beamforming Scheme With Parallel Uniform Circular Array
Authors: Haiyue Jing, Wenchi Cheng, Xiang-Gen Xia
Date: 2024-06-07 00:00:00

In this letter, we consider a uniform circular array (UCA)-based line-of-sight multiple-input-multiple-output system, where the transmit and receive UCAs are parallel but non-coaxial with each other. We propose a simple channel-independent beamforming scheme with fast symbol-wise maximum likelihood detection.
Bifurcations and multistability in empirical mutualistic networks
Authors: Andrus Giraldo, Deok-Sun Lee
Date: 2024-06-11 00:00:00
Tasks: Management

Individual species may experience diverse outcomes, from prosperity to extinction, in an ecological community subject to external and internal variations. Despite the wealth of theoretical results derived from random matrix ensembles, a theoretical framework still remains to be developed to understand species-level dynamical heterogeneity within a given community, hampering real-world ecosystems' theoretical assessment and management. Here, we consider empirical plant-pollinator mutualistic networks, additionally including all-to-all intragroup competition, where species abundance evolves under a Lotka-Volterra-type equation. Setting the strengths of competition and mutualism to be uniform, we investigate how individual species persist or go extinct under varying the interaction strengths. By employing bifurcation theory in tandem with numerical continuation, we elucidate transcritical bifurcations underlying species extinction and demonstrate that the Hopf bifurcation of unfeasible equilibria and degenerate transcritical bifurcations give rise to multistability, i.e., the coexistence of multiple attracting feasible equilibria. These bifurcations allow us to partition the parameter space into different regimes, each with distinct sets of extinct species, offering insights into how interspecific interactions generate one or multiple extinction scenarios within an ecological network.
The Price of Cognition and Replicator Equations in Parallel Neural Networks
Authors: Armen Bagdasaryan, Antonios Kalampakas, Mansoor Saburov
Date: 2024-06-10 00:00:00
Tasks: Novel Concepts

In this paper, we are aiming to propose a novel mathematical model that studies the dynamics of synaptic damage in terms of concentrations of toxic neuropeptides/neurotransmitters during neurotransmission processes. Our primary objective is to employ Wardrop's first and second principles within a neural network of the brain. In order to comprehensively incorporate Wardrop's first and second principles into the neural network of the brain, we introduce two novel concepts: \textit{neuropeptide's (neurotransmitter's) equilibrium} and \textit{synapses optimum}. The \textit{neuropeptide/neurotransmitter equilibrium} refers to \textit{a distribution of toxic neuropeptides/neurotransmitters that leads to uniform damage across all synaptic links}. Meanwhile, \textit{synapses optimum} is \textit{the most desirable distribution of toxic neuropeptides/neurotransmitters that minimizes the cumulative damage experienced by all synapses}. In the context of a neural network within the brain, an analogue of the price of anarchy is \textit{the price of cognition} which is \textit{the most unfavorable ratio between the overall impairment caused by toxic neuropeptide's (neurotransmitter's) equilibrium in comparison to the optimal state of synapses (synapses optimum)}. To put it differently, \textit{the price of cognition} measures \textit{the loss of cognitive ability resulting from increased concentrations of toxic neuropeptides/neurotransmitters}. Additionally, a replicator equation is proposed within this framework that leads to the establishment of the synapses optimum during the neurotransmission process.
Macroscopic Market Making Games via Multidimensional Decoupling Field
Authors: Ivan Guo, Shijia Jin
Date: 2024-06-09 00:00:00
Tasks: Dimensionality Reduction

Building on the macroscopic market making framework as a control problem, this paper investigates its extension to stochastic games. In the context of price competition, each agent is benchmarked against the best quote offered by the others. We begin with the linear case. While constructing the solution directly, the \textit{ordering property} and the dimension reduction in the equilibrium are revealed. For the non-linear case, we extend the decoupling approach by introducing a multidimensional \textit{characteristic equation} to analyse the well-posedness of the forward-backward stochastic differential equations. Properties of the coefficients in this characteristic equation are derived using tools from non-smooth analysis. Several new well-posedness results are presented.
Probabilistic models and statistics for electronic financial markets in the digital age
Authors: Markus Bibinger
Date: 2024-06-11 00:00:00

The scope of this manuscript is to review some recent developments in statistics for discretely observed semimartingales which are motivated by applications for financial markets. Our journey through this area stops to take closer looks at a few selected topics discussing recent literature. We moreover highlight and explain the important role played by some classical concepts of probability and statistics. We focus on three main aspects: Testing for jumps; rough fractional stochastic volatility; and limit order microstructure noise. We review jump tests based on extreme value theory and complement the literature proposing new statistical methods. They are based on asymptotic theory of order statistics and the R\'{e}nyi representation. The second stage of our journey visits a recent strand of research showing that volatility is rough. We further investigate this and establish a minimax lower bound exploring frontiers to what extent the regularity of latent volatility can be recovered in a more general framework. Finally, we discuss a stochastic boundary model with one-sided microstructure noise for high-frequency limit order prices and its probabilistic and statistical foundation.
pVACview: an interactive visualization tool for efficient neoantigen prioritization and selection
Authors: Huiming Xia, My Hoang, Evelyn Schmidt, Susanna Kiwala, Joshua McMichael, Zachary L. Skidmore, Bryan Fisk, Jonathan J. Song, Jasreet Hundal, Thomas Mooney, Jason R. Walker, S. Peter Goedegebuure, Christopher A. Miller, William E. Gillanders, Obi L. Griffith, Malachi Griffith
Date: 2024-06-11 00:00:00
Tasks: Navigate

Neoantigen targeting therapies including personalized vaccines have shown promise in the treatment of cancers. Accurate identification/prioritization of neoantigens is highly relevant to designing clinical trials, predicting treatment response, and understanding mechanisms of resistance. With the advent of massively parallel sequencing technologies, it is now possible to predict neoantigens based on patient-specific variant information. However, numerous factors must be considered when prioritizing neoantigens for use in personalized therapies. Complexities such as alternative transcript annotations, various binding, presentation and immunogenicity prediction algorithms, and variable peptide lengths/registers all potentially impact the neoantigen selection process. While computational tools generate numerous algorithmic predictions for neoantigen characterization, results from these pipelines are difficult to navigate and require extensive knowledge of the underlying tools for accurate interpretation. Due to the intricate nature and number of salient neoantigen features, presenting all relevant information to facilitate candidate selection for downstream applications is a difficult challenge that current tools fail to address. We have created pVACview, the first interactive tool designed to aid in the prioritization and selection of neoantigen candidates for personalized neoantigen therapies. pVACview has a user-friendly and intuitive interface where users can upload, explore, select and export their neoantigen candidates. The tool allows users to visualize candidates using variant, transcript and peptide information. pVACview will allow researchers to analyze and prioritize neoantigen candidates with greater efficiency and accuracy in basic and translational settings. The application is available as part of the pVACtools pipeline at pvactools.org and as an online server at pvacview.org.