pwc-archive/papers-with-abstracts huggingface dataset:
CDMA and Non-Uniform Multiplexing: Dynamic Range in MIMO Radar Waveforms
Authors: Aitor Correas-Serrano, Nikita Petrov, Maria Gonzalez-Huici, Alexander Yarovoy
Date: 2024-08-26 00:00:00

This paper presents a performance comparison of various MIMO radar multiplexing approaches where the increasing number of transmitters adversely affects the dynamic range of the resultant MIMO system. The investigated multiplexing techniques are code-division multiplexing in phase-coded frequency-modulated continuous wave (FMCW) and phase-modulated continuous wave (PMCW) radar. Additionally, random fast/slow time multiplexing in time and frequency is considered for frequency-modulated continuous wave and orthogonal frequency-division multiplexing (OFDM) radars. The comparative analysis is conducted through simulations, evaluating the scalability with the number of transmitters and addressing other pertinent implementation concerns. The findings provide insights into the trade-offs associated with each approach, aiding in selecting suitable MIMO radar multiplexing strategies for practical applications.
Securing FC-RIS and UAV Empowered Multiuser Communications Against a Randomly Flying Eavesdropper
Authors: Shuying Lin, Yulong Zou, Yuhan Jiang, Libao Yang, Zhe Cui, Le-Nam Tran
Date: 2024-08-26 00:00:00
Tasks: Scheduling

This paper investigates a wireless network consisting of an unmanned aerial vehicle (UAV) base station (BS), a fully-connected reconfigurable intelligent surface (FC-RIS), and multiple users, where the downlink signal can simultaneously be captured by an aerial eavesdropper at a random location. To improve the physical-layer security (PLS) of the considered downlink multiuser communications, we propose the fully-connected reconfigurable intelligent surface aided round-robin scheduling (FCR-RS) and the FC-RIS and ground channel state information (CSI) aided proportional fair scheduling (FCR-GCSI-PFS) schemes. Thereafter, we derive closed-form expressions of the zero secrecy rate probability (ZSRP). Numerical results not only validate the closed-form ZSRP analysis, but also verify that the proposed GCSI-PFS scheme obtains the same performance gain as the full-CSI-aided PFS in FC-RIS-aided communications. Furthermore, optimizing the hovering altitude remarkably enhances the PLS of the FC-RIS and UAV empowered multiuser communications.
Deep Learning Autoencoders for Reducing PAPR in Coherent Optical Systems
Authors: Omar Alnaseri, Ibtesam R. K. Al-Saedi, Yassine Himeur, Hongxiang Li
Date: 2024-08-26 00:00:00
Tasks: Decoder, Deep Learning

This paper presents an innovative approach to mitigating the peak-to-average power ratio (PAPR). The proposed method uses a deep learning model called autoencoders (AEs) to simplify the process and avoid the complex calculations of traditional methods such as selective mapping (SLM). Unlike SLM, our approach does not need side information about the PAPR distribution. Through simulations of coherent optical orthogonal frequency division multiplexing (CO-OFDM) systems, the AE-based model offers substantial enhancements in both PAPR reduction and bit error rate (BER) performance when compared to conventional techniques. An error-free transmission can be acheived with a reduction in PAPR exceeding 10 dB compared to the original signal and a 1 dB advantage over SLM. In particular, the AE model achieves the best BER performance of \(2 \times 10^{-6}\) at 44 dB OSNR, surpassing traditional methods. Furthermore, the model demonstrates robustness against noise and nonlinear distortions, making it appropriate for optical channels experiencing diverse levels of impairment. This innovative technique has the potential to revolutionize next-generation optical communication systems by enabling efficient and reliable data transmission.
Integrated Sensing, Communication, and Powering over Multi-antenna OFDM Systems
Authors: Yilong Chen, Chao Hu, Zixiang Ren, Han Hu, Jie Xu, Lexi Xu, Lei Liu, Shuguang Cui
Date: 2024-08-26 00:00:00
Tasks: Scheduling

This paper considers a multi-functional orthogonal frequency division multiplexing (OFDM) system with integrated sensing, communication, and powering (ISCAP), in which a multi-antenna base station (BS) transmits OFDM signals to simultaneously deliver information to multiple information receivers (IRs), provide energy supply to multiple energy receivers (ERs), and sense potential targets based on the echo signals. To facilitate ISCAP, the BS employs the joint transmit beamforming design by sending dedicated sensing/energy beams jointly with information beams. Furthermore, we consider the beam scanning for sensing, in which the joint beams scan in different directions over time to sense potential targets. In order to ensure the sensing beam scanning performance and meet the communication and powering requirements, it is essential to properly schedule IRs and ERs and design the resource allocation over time, frequency, and space. More specifically, we optimize the joint transmit beamforming over multiple OFDM symbols and subcarriers, with the objective of minimizing the average beampattern matching error of beam scanning for sensing, subject to the constraints on the average communication rates at IRs and the average harvested power at ERs. We find converged high-quality solutions to the formulated problem by proposing efficient iterative algorithms based on advanced optimization techniques. We also develop various heuristic designs based on the principles of zero-forcing (ZF) beamforming, round-robin user scheduling, and time switching, respectively. Numerical results show that our proposed algorithms adaptively generate information and sensing/energy beams at each time-frequency slot to match the scheduled IRs/ERs with the desired scanning beam, significantly outperforming the heuristic designs.
An RIS-enabled Time Reversal Scheme for Multipath Near-Field Channels
Authors: Andreas Nicolaides, Constantinos Psomas, Ioannis Krikidis
Date: 2024-08-26 00:00:00

Time reversal (TR) is a promising technique that exploits multipaths for achieving energy focusing in high-frequency wideband communications. In this letter, we focus on a TR scheme facilitated by a reconfigurable intelligent surface (RIS) which, due to the higher frequency and large array aperture, operates in the near-field region. The proposed scheme enriches the propagation environment for the TR in such weak scattering conditions and does not need channel knowledge for the RIS configuration. Specifically, the RIS is employed to create multiple virtual propagation paths that are required to efficiently apply the TR. We derive a performance bound for the proposed scheme under near-field modeling through the received signal-to-noise ratio (SNR) and we examine how various system design parameters affect the performance. We observe that a linear RIS topology maximizes the number of resolvable paths. It is also demonstrated that the proposed scheme improves the SNR, while for a large number of elements it can outperform the conventional passive beamforming at the RIS.
5G-NR PRACH Detection Performance Optimization in Context of Intra/Inter-Cell Interference
Authors: Desire Guel, Pegdwindé Justin Kouraogo, Boureima Zerbo, Elie Jephte Yaro
Date: 2024-08-26 00:00:00
Tasks: Management

The ever-evolving landscape of wireless communication technologies has led to the development of 5G-NR (5G New Radio) networks promising higher data rates and lower latency. However, with these advancements come challenges in managing intra-cell and inter-cell interference, particularly during the random-access procedure. This article aims to explore the impact of UE (User Equipment) and cell configuration parameters on interference and establish improved interference management strategies. To assess the effectiveness of these strategies, Key Performance Indicators (KPIs) such as Correct Detection Rate (CDR) will be considered. Additionally, the Matched Filtering (MF)-Based PRACH (Physical Random-Access CHannel) detection algorithm will be studied to evaluate the PRACH performance. The findings underscore the critical role of interference management and the configuration of User Equipment (UE)/Cell parameters in ensuring the robustness and reliability of the NR-PRACH performance in 5G NR networks. Optimizing these configurations can lead to improved network performance and enhanced communication quality.
UAV-Enabled Integrated Sensing and Communication in Maritime Emergency Networks
Authors: Bohan Li, Jiahao Liu, Junsheng Mu, Pei Xiao, Sheng Chen
Date: 2024-08-26 00:00:00
Tasks: Integrated sensing and communication, ISAC, Position

With line-of-sight mode deployment and fast response, unmanned aerial vehicle (UAV), equipped with the cutting-edge integrated sensing and communication (ISAC) technique, is poised to deliver high-quality communication and sensing services in maritime emergency scenarios. In practice, however, the real-time transmission of ISAC signals at the UAV side cannot be realized unless the reliable wireless fronthaul link between the terrestrial base station and UAV are available. This paper proposes a multicarrier-division duplex based joint fronthaul-access scheme, where mutually orthogonal subcarrier sets are leveraged to simultaneously support four types of fronthaul/access transmissions. In order to maximize the end-to-end communication rate while maintaining an adequate sensing quality-of-service (QoS) in such a complex scheme, the UAV trajectory, subcarrier assignment and power allocation are jointly optimized. The overall optimization process is designed in two stages. As the emergency area is usually far away from the coast, the optimal initial operating position for the UAV is first found. Once the UAV passes the initial operating position, the UAV's trajectory and resource allocation are optimized during the mission period to maximize the end-to-end communication rate under the constraint of minimum sensing QoS. Simulation results demonstrate the effectiveness of the proposed scheme in dealing with the joint fronthaul-access optimization problem in maritime ISAC networks, offering the advantages over benchmark schemes.
Diversity and Multiplexing for Continuous Aperture Array (CAPA)-Based Communications
Authors: Chongjun Ouyang, Zhaolin Wang, Xingqi Zhang, Yuanwei Liu
Date: 2024-08-25 00:00:00
Tasks: Diversity

A general fading model for multipath channels between two non-parallel continuous-aperture arrays (CAPAs) is proposed. Building on this model, the performance of diversity and multiplexing achieved by CAPAs over fading channels is analyzed. i) For multiple-input single-output (MISO) and single-input multiple-output (SIMO) channels, Landau's eigenvalue theorem is applied to analyze the autocorrelation of the spatial response. Closed-form expressions are derived for the outage probability (OP) and ergodic channel capacity (ECC). Asymptotic analyses in the high signal-to-noise ratio (SNR) regime are conducted to reveal the maximal achievable diversity and multiplexing gains. The diversity-multiplexing trade-off (DMT) is characterized, along with the array gain within the DMT framework. ii) For multiple-input multiple-output (MIMO) channels, a wavenumber-domain-based transmission framework is proposed to leverage the spatial degrees of freedom offered by CAPAs. Asymptotic approximations for the OP and ECC are derived, and the DMT is explored. The performance of CAPAs is further compared with that of conventional spatially-discrete arrays (SPDAs). Analytical and numerical results demonstrate that: i) CAPAs achieve a lower OP and higher ECC than SPDAs; ii) CAPAs achieve the same DMT as SPDAs with antenna spacing no larger than half a wavelength while attaining a higher array gain; and iii) CAPAs outperform SPDAs with antenna spacing greater than half a wavelength in terms of DMT.
Chirp Group Delay based Onset Detection in Instruments with Fast Attack
Authors: S. Johanan Joysingh, P. Vijayalakshmi, T. Nagarajan
Date: 2024-08-25 00:00:00
Tasks: Onset Detection

The onset of a musical note is the earliest time at which a note can be reliably detected. Detection of these musical onsets pose challenges in the presence of ornamentation such as vibrato, bending, and if the attack of the note transient is slower. The legacy systems such as spectral difference or flux and complex domain functions suffer from the addition of false positives due to ornamentation posing as viable onsets. We propose that this can be solved by appropriately improving the resolution of the onset strength signal (OSS) and smoothening it to increase true positives and decrease false positives, respectively. An appropriate peak picking algorithm that works well in unison with the OSS generated is also desired. Since onset detection is a low-level process upon which many other tasks are built, computational complexity must also be reduced. We propose an onset detection alogrithm that is a combination of short-time spectral average-based OSS estimation, chirp group delay-based smoothening, and valley-peak distance-based peak picking. This algorithm performs on par with the state-of-the-art, superflux and convolutional neural networks-based onset detection, with an average F1 score of 0.88, across three datasets. Subsets from the IDMT-SMT-Guitar, Guitarset, and Musicnet datasets that fit the scope of the work, are used for evaluation. It is also found that the proposed algorithm is computationally 300\% more efficient than superflux. The positive effects of smoothening an OSS, in determining the onset locations, is established by refining the OSS produced by legacy algorithms, where consistent improvement in onset detection performance is observed. To provide insights into the performance of the proposed algorithms when different ornamentation styles are present in the recording, three levels of results are computed, by selecting different subsets of the IDMT dataset.
DebriSense: Terahertz-based Integrated Sensing and Communications (ISAC) for Debris Detection and Classification in the Internet of Space (IoS)
Authors: Haofan Dong, Ozgur B. Akan
Date: 2024-08-24 00:00:00
Tasks: ISAC, Management

The proliferation of Low Earth Orbit (LEO) satellite constellations has intensified the challenge of space debris management. This paper introduces DebriSense-THz, a novel Terahertz-Enabled Debris Sensing system for LEO satellites that leverages Integrated Sensing and Communications (ISAC) technology. We present a comprehensive THz channel model for LEO environments, incorporating debris interactions such as reflection, scattering, and diffraction. The DebriSense-THz architecture employs machine learning techniques for debris detection and classification using Channel State Information (CSI) features. Performance evaluation across different frequencies (30 GHz-5 THz), MIMO configurations, debris densities, and SNR levels demonstrates significant improvements in debris detection and classification accuracy (95-99% at 5 THz compared to 62-81% at 30 GHz). Higher SNR configurations enhance sensing performance, particularly at higher frequencies. The system shows robust performance across various debris densities and MIMO size in the THz range, with a noted trade-off between communication reliability and sensing accuracy at lower frequencies. DebriSense-THz represents a significant advance in space situational awareness, paving the way for more effective debris mitigation strategies in increasingly congested LEO environments.
Performance Analysis of Photon-Limited Free-Space Optical Communications with Practical Photon-Counting Receivers
Authors: Chen Wang, Zhiyong Xu, Jingyuan Wang, Jianhua Li, Weifeng Mou, Huatao Zhu, Jiyong Zhao, Yang Su, Yimin Wang, Ailin Qi
Date: 2024-08-24 00:00:00

The non-perfect factors of practical photon-counting receiver are recognized as a significant challenge for long-distance photon-limited free-space optical (FSO) communication systems. This paper presents a comprehensive analytical framework for modeling the statistical properties of time-gated single-photon avalanche diode (TG-SPAD) based photon-counting receivers in presence of dead time, non-photon-number-resolving and afterpulsing effect. Drawing upon the non-Markovian characteristic of afterpulsing effect, we formulate a closed-form approximation for the probability mass function (PMF) of photon counts, when high-order pulse amplitude modulation (PAM) is used. Unlike the photon counts from a perfect photon-counting receiver, which adhere to a Poisson arrival process, the photon counts from a practical TG-SPAD based receiver are instead approximated by a binomial distribution. Additionally, by employing the maximum likelihood (ML) criterion, we derive a refined closed-form formula for determining the threshold in high-order PAM, thereby facilitating the development of an analytical model for the symbol error rate (SER). Utilizing this analytical SER model, the system performance is investigated. The numerical results underscore the crucial need to suppress background radiation below the tolerated threshold and to maintain a sufficient number of gates in order to achieve a target SER.
FAS-RIS Communication: Model, Analysis, and Optimization
Authors: Junteng Yao, Jianchao Zheng, Tuo Wu, Ming Jin, Chau Yuen, Kai-Kit Wong, Fumiyuki Adachi
Date: 2024-08-24 00:00:00
Tasks: model

This correspondence investigates the novel fluid antenna system (FAS) technology, combining with reconfigurable intelligent surface (RIS) for wireless communications, where a base station (BS) communicates with a FAS-enabled user with the assistance of a RIS. To analyze this technology, we derive the outage probability based on the block-diagonal matrix approximation (BDMA) model. With this, we obtain the upper bound, lower bound, and asymptotic approximation of the outage probability to gain more insights. Moreover, we design the phase shift matrix of the RIS in order to minimize the system outage probability. Simulation results confirm the accuracy of our approximations and that the proposed schemes outperform benchmarks significantly.
FAS-RIS: A Block-Correlation Model Analysis
Authors: Xiazhi Lai, Junteng Yao, Kangda Zhi, Tuo Wu, David Morales-Jimenez, Kai-Kit Wong
Date: 2024-08-24 00:00:00
Tasks: model

In this correspondence, we analyze the performance of a reconfigurable intelligent surface (RIS)-aided communication system that involves a fluid antenna system (FAS)-enabled receiver. By applying the central limit theorem (CLT), we derive approximate expressions for the system outage probability when the RIS has a large number of elements. Also, we adopt the block-correlation channel model to simplify the outage probability expressions, reducing the computational complexity and shedding light on the impact of the number of ports. Numerical results validate the effectiveness of our analysis, especially in scenarios with a large number of RIS elements.
Prototype of Secure Wire-Line Telephone
Authors: Lifeng Lin, Zijian Zhou, Peihe Jiang, Sanjun Liu, Lai Wei, Bingli Jiao
Date: 2024-08-24 00:00:00

This paper presents a secure wire-line telephone system that employs physical layer security (PLS) to protect against wiretapping. The system generates artificial noise (AN) in both transmission directions and uses a telephone hybrid circuit to effectively suppress the AN for the purpose of secure communication. Furthermore, we analyze the secrecy capacity of the system and evaluate its performance through theoretical analysis and practical experiments. The results demonstrate that the proposed system can significantly enhance communication security while preserving the integrity of legitimate signals. The results also validate that the proposed system is a robust and effective solution for securing wire-line telephone communications.
Beam Profiling and Beamforming Modeling for mmWave NextG Networks
Authors: Efat Samir Fathalla, Sahar Zargarzadeh, Chunsheng Xin, Hongyi Wu, Peng Jiang, Joao F. Santos, Jacek Kibilda, Aloizio Pereira da
Date: 2024-08-23 00:00:00
Tasks: Scheduling

This paper presents an experimental study on mmWave beam profiling on a mmWave testbed, and develops a machine learning model for beamforming based on the experiment data. The datasets we have obtained from the beam profiling and the machine learning model for beamforming are valuable for a broad set of network design problems, such as network topology optimization, user equipment association, power allocation, and beam scheduling, in complex and dynamic mmWave networks. We have used two commercial-grade mmWave testbeds with operational frequencies on the 27 Ghz and 71 GHz, respectively, for beam profiling. The obtained datasets were used to train the machine learning model to estimate the received downlink signal power, and data rate at the receivers (user equipment with different geographical locations in the range of a transmitter (base station). The results have shown high prediction accuracy with low mean square error (loss), indicating the model's ability to estimate the received signal power or data rate at each individual receiver covered by a beam. The dataset and the machine learning-based beamforming model can assist researchers in optimizing various network design problems for mmWave networks.
3D Photon Counting CT Image Super-Resolution Using Conditional Diffusion Model
Authors: Chuang Niu, Christopher Wiedeman, Mengzhou Li, Jonathan S Maltz, Ge Wang
Date: 2024-08-22 00:00:00
Tasks: Denoising, Image Super-Resolution, Super-Resolution

This study aims to improve photon counting CT (PCCT) image resolution using denoising diffusion probabilistic models (DDPM). Although DDPMs have shown superior performance when applied to various computer vision tasks, their effectiveness has yet to be translated to high dimensional CT super-resolution. To train DDPMs in a conditional sampling manner, we first leverage CatSim to simulate realistic lower resolution PCCT images from high-resolution CT scans. Since maximizing DDPM performance is time-consuming for both inference and training, especially on high-dimensional PCCT data, we explore both 2D and 3D networks for conditional DDPM and apply methods to accelerate training. In particular, we decompose the 3D task into efficient 2D DDPMs and design a joint 2D inference in the reverse diffusion process that synergizes 2D results of all three dimensions to make the final 3D prediction. Experimental results show that our DDPM achieves improved results versus baseline reference models in recovering high-frequency structures, suggesting that a framework based on realistic simulation and DDPM shows promise for improving PCCT resolution.
Option Pricing with Stochastic Volatility, Equity Premium, and Interest Rates
Authors: Nicole Hao, Echo Li, Diep Luong-Le
Date: 2024-08-27 00:00:00

This paper presents a new model for options pricing. The Black-Scholes-Merton (BSM) model plays an important role in financial options pricing. However, the BSM model assumes that the risk-free interest rate, volatility, and equity premium are constant, which is unrealistic in the real market. To address this, our paper considers the time-varying characteristics of those parameters. Our model integrates elements of the BSM model, the Heston (1993) model for stochastic variance, the Vasicek model (1977) for stochastic interest rates, and the Campbell and Viceira model (1999, 2001) for stochastic equity premium. We derive a linear second-order parabolic PDE and extend our model to encompass fixed-strike Asian options, yielding a new PDE. In the absence of closed-form solutions for any options from our new model, we utilize finite difference methods to approximate prices for European call and up-and-out barrier options, and outline the numerical implementation for fixed-strike Asian call options.