pwc-archive/papers-with-abstracts huggingface dataset:
From Theory to Reality: A Design Framework for Integrated Communication and Computing Receivers
Authors: Kuranage Roche Rayan Ranasinghe, Kengo Ando, Giuseppe Thadeu Freitas de Abreu
Date: 2024-11-04 00:00:00

We propose a novel flexible and scalable framework to design integrated communication and computing (ICC) -- a.k.a. over-the-air computing (AirComp)-- receivers. To elaborate, while related literature so far has generally focused either on theoretical aspects of ICC or on the design of beamforming (BF) algorithms for AirComp, we propose a framework to design receivers capable of simultaneously detecting communication symbols and extracting the output of the AirComp operation, in a manner that can: a) be systematically generalized to any nomographic function, b) scaled to a massive number of user equipments (UEs) and edge devices (EDs), and c) support the multiple computation streams. For the sake of illustration, we demonstrate the proposed method under a setting consisting of the uplink from multiple single-antenna UEs/EDs simultaneously transmitting communication and computing signals to a single multiple-antenna base station (BS)/access point (AP). The receiver, which seeks to detect all communication symbols and minimize the distortion over the computing signals, requires that only a fraction of the transmit power be allocated to the latter, therefore coming close to the ideal (but unattainable) condition that computing is achieved "for free", without taking resources from the communication system. The design leverages the Gaussian belief propagation (GaBP) framework relying only on element-wise scalar operations, which allows for its use in massive settings, as demonstrated by simulation results incorporating up to 200 antennas and 200 UEs/EDs. They also demonstrate the efficacy of the proposed method under all various loading conditions, with the performance of the scheme approaching fundamental limiting bounds in the under/fully loaded cases.
Multimodal Trustworthy Semantic Communication for Audio-Visual Event Localization
Authors: Yuandi Li, Zhe Xiang, Fei Yu, Zhangshuang Guan, Hui Ji, Zhiguo Wan, Cheng Feng
Date: 2024-11-04 00:00:00
Tasks: audio-visual event localization, Semantic Communication

The exponential growth in wireless data traffic, driven by the proliferation of mobile devices and smart applications, poses significant challenges for modern communication systems. Ensuring the secure and reliable transmission of multimodal semantic information is increasingly critical, particularly for tasks like Audio-Visual Event (AVE) localization. This letter introduces MMTrustSC, a novel framework designed to address these challenges by enhancing the security and reliability of multimodal communication. MMTrustSC incorporates advanced semantic encoding techniques to safeguard data integrity and privacy. It features a two-level coding scheme that combines error-correcting codes with conventional encoders to improve the accuracy and reliability of multimodal data transmission. Additionally, MMTrustSC employs hybrid encryption, integrating both asymmetric and symmetric encryption methods, to secure semantic information and ensure its confidentiality and integrity across potentially hostile networks. Simulation results validate MMTrustSC's effectiveness, demonstrating substantial improvements in data transmission accuracy and reliability for AVE localization tasks. This framework represents a significant advancement in managing intermodal information complementarity and mitigating physical noise, thus enhancing overall system performance.
Probability of Error Analysis for NOMA Systems in Rayleigh Fading Channels: Enabling IoT in Civil Engineering
Authors: Amr Abdelbari, Bülent Bilgehan, Fadi Al-Turjman
Date: 2024-11-04 00:00:00
Tasks: Decision Making

In the realm of digital communication, understanding and mitigating the probability of error is crucial, particularly in Rayleigh fading channels where signal impairments are common. This paper presents a unified approach to derive the probability of error formulations for two-users NOMA systems operating in Rayleigh fading channels. The methodologies and findings outlined in this study are essential for IoT applications in construction and civil engineering. Specifically, the derived error probability formulations can be employed to enhance the reliability and efficiency of IoT-based monitoring systems in these sectors. By optimizing communication protocols, the proposed approach ensures accurate data transmission, thereby facilitating real-time monitoring and decision-making processes in construction sites and civil infrastructure projects.
User Activity Detection with Delay-Calibration for Asynchronous Massive Random Access
Authors: Zhichao Shao, Xiaojun Yuan, Rodrigo C. de Lamare, Yong Zhang
Date: 2024-11-04 00:00:00
Tasks: Action Detection, Activity Detection, Compressive Sensing

This work considers an uplink asynchronous massive random access scenario in which a large number of users asynchronously access a base station equipped with multiple receive antennas. The objective is to alleviate the problem of massive collision due to the limited number of orthogonal preambles of an access scheme in which user activity detection is performed. We propose a user activity detection with delay-calibration (UAD-DC) algorithm and investigate the benefits of oversampling for the estimation of continuous time delays at the receiver. The proposed algorithm iteratively estimates time delays and detects active users by noting that the collided users can be identified through accurate estimation of time delays. Due to the sporadic user activity patterns, the user activity detection problem can be formulated as a compressive sensing (CS) problem, which can be solved by a modified Turbo-CS algorithm under the consideration of correlated noise samples resulting from oversampling. A sliding-window technique is applied in the proposed algorithm to reduce the overall computational complexity. Moreover, we propose a new design of the pulse shaping filter by minimizing the Bayesian Cram\'er-Rao bound of the detection problem under the constraint of limited spectral bandwidth. Numerical results demonstrate the efficacy of the proposed algorithm in terms of the normalized mean squared error of the estimated channel, the probability of misdetection and the successful detection ratio.
Target Handover in Distributed Integrated Sensing and Communication
Authors: Yu Ge, Ossi Kaltiokallio, Hui Chen, Jukka Talvitie, Yuxuan Xia, Giyyarpuram Madhusudan, Guillaume Larue, Lennart Svensson, Mikko Valkama, Henk Wymeersch
Date: 2024-11-04 00:00:00
Tasks: Integrated sensing and communication, ISAC

The concept of 6G distributed integrated sensing and communications (DISAC) builds upon the functionality of integrated sensing and communications (ISAC) by integrating distributed architectures, significantly enhancing both sensing and communication coverage and performance. In 6G DISAC systems, tracking target trajectories requires base stations (BSs) to hand over their tracked targets to neighboring BSs. Determining what information to share, where, how, and when is critical to effective handover. This paper addresses the target handover challenge in DISAC systems and introduces a method enabling BSs to share essential target trajectory information at appropriate time steps, facilitating seamless handovers to other BSs. The target tracking problem is tackled using the standard trajectory Poisson multi-Bernoulli mixture (TPMBM) filter, enhanced with the proposed handover algorithm. Simulation results confirm the effectiveness of the implemented tracking solution.
Near-Field Localization With Coprime Array
Authors: Hongqiang Cheng, Changsheng You, Cong Zhou
Date: 2024-11-03 00:00:00

Large-aperture coprime arrays (CAs) are expected to achieve higher sensing resolution than conventional dense arrays (DAs), yet with lower hardware and energy cost. However, existing CA far-field localization methods cannot be directly applied to near-field scenarios due to channel model mismatch. To address this issue, in this paper, we propose an efficient near-field localization method for CAs. Specifically, we first construct an effective covariance matrix, which allows to decouple the target angle-and-range estimation. Then, a customized two-phase multiple signal classification (MUSIC) algorithm for CAs is proposed, which first detects all possible targets' angles by using an angular-domain MUSIC algorithm, followed by the second phase to resolve the true targets' angles and ranges by devising a range-domain MUSIC algorithm. Finally, we show that the proposed method is able to locate more targets than the subarray-based method as well as achieve lower root mean square error (RMSE) than DAs.
Unlocking FAS-RIS Security Analysis with Block-Correlation Model
Authors: Jianchao Zheng, Xiazhi Lai, Tuo Wu, Maged Elkashlan, Daniel Benevides da Costa, Chau Yuen, Fumiyuki Adachi
Date: 2024-11-03 00:00:00
Tasks: Position

In this letter, we investigate the security of fluid antenna system (FAS)-reconfigurable intelligent surfaces (RIS) communication systems. The base station (BS) employs a single fixed-position antenna, while both the legitimate receiver and the eavesdropper are equipped with fluid antennas. By utilizing the block-correlation model and the central limit theorem (CLT), we derive approximate expressions for the average secrecy capacity and secrecy outage probability (SOP). Our analysis, validated by simulation results, demonstrates the effectiveness of the block-correlation model in accurately assessing the security performance. Moreover, simulation results reveal that FAS-RIS system significantly outperforms other systems in terms of security, further underscoring its potential in secure communication applications.
Paving the Way to 6G: Outage Probability Analysis for FAS-ARIS Systems
Authors: Jianchao Zheng, Xiazhi Lai, Junteng Yao, Jie Tang, Yijin Pan, Tuo Wu, Chau Yuen
Date: 2024-11-03 00:00:00
Tasks: Position

In this paper, we pave the way to six-generation (6G) by investigating the outage probability (OP) of fluid antenna system (FAS)-active reconfigurable intelligent surface (ARIS) communication systems. We consider a FAS-ARIS setup consisting of a base station (BS) with a single fixed-position antenna and a receiver equipped with a fluid antenna (FA). Utilizing the block-correlation model, we derive a closed-form expression for the OP. Our analysis, supported by numerical results, confirms the accuracy and effectiveness of the derivation. Furthermore, the results demonstrate that the FAS-ARIS system significantly outperforms other configurations in terms of OP, highlighting its potential to enhance communication performance and reliability in future 6G networks.
Deep Reinforcement Learning for Trajectory and Phase Shift Optimization of Aerial RIS in CoMP-NOMA Networks
Authors: Muhammad Umer, Muhammad Ahmed Mohsin, Aamir Mahmood, Kapal Dev, Haejoon Jung, Mikael Gidlund, Syed Ali Hassan
Date: 2024-11-02 00:00:00
Tasks: Deep Reinforcement Learning

This paper explores the potential of aerial reconfigurable intelligent surfaces (ARIS) to enhance coordinated multi-point non-orthogonal multiple access (CoMP-NOMA) networks. We consider a system model where a UAV-mounted RIS assists in serving multiple users through NOMA while coordinating with multiple base stations. The optimization of UAV trajectory, RIS phase shifts, and NOMA power control constitutes a complex problem due to the hybrid nature of the parameters, involving both continuous and discrete values. To tackle this challenge, we propose a novel framework utilizing the multi-output proximal policy optimization (MO-PPO) algorithm. MO-PPO effectively handles the diverse nature of these optimization parameters, and through extensive simulations, we demonstrate its effectiveness in achieving near-optimal performance and adapting to dynamic environments. Our findings highlight the benefits of integrating ARIS in CoMP-NOMA networks for improved spectral efficiency and coverage in future wireless networks.
Measurement-based Characterization of ISAC Channels with Distributed Beamforming at Dual mmWave Bands and with Human Body Scattering and Blockage
Authors: Yang Miao, Minseok Kim, Naoya Suzuki, Chechia Kang, Junichi Takada
Date: 2024-11-02 00:00:00
Tasks: Integrated sensing and communication, ISAC

In this paper, we introduce our millimeter-wave (mmWave) radio channel measurement for integrated sensing and communication (ISAC) scenarios with distributed links at dual bands in an indoor cavity; we also characterize the channel in delay and azimuth-angular domains for the scenarios with the presence of 1 person with varying locations and facing orientations. In our setting of distributed links with two transmitters and two receivers where each transceiver operates at two bands, we can measure two links whose each transmitter faces to one receiver and thus capable of line-of-sight (LOS) communication; these two links have crossing Fresnel zones. We have another two links capable of capturing the reflectivity from the target presenting in the test area (as well as the background). The numerical results in this paper focus on analyzing the channel with the presence of one person. It is evident that not only the human location, but also the human facing orientation, shall be taken into account when modeling the ISAC channel.
Fundamental Trade-offs in Quantized Hybrid Radar Fusion: A CRB-Rate Perspective
Authors: Akhileswar Chowdary, Ahmad Bazzi, Roberto Bomfin, Marwa Chafii
Date: 2024-11-01 00:00:00
Tasks: Integrated sensing and communication, ISAC, Quantization

While recent advancements have highlighted the role of low-resolution analog-to-digital converters (ADCs) in integrated sensing and communication (ISAC) systems, the specific impact of ADC resolution on hybrid radar fusion (HRF), where we fuse monostatic and bistatic sensing systems remains relatively unexplored. The uplink (UL) paths in HRF, comprising both direct and reflected signals within the same frequency band, pose unique challenges, particularly given that the reflected signal is often significantly weaker than the direct path, making HRF systems susceptible to ADC resolution. To investigate the influence of quantization and ADC resolution on HRF, we employ the quantized Cram\'er-Rao bound (CRB) as a metric for sensing accuracy. This work derives the quantized CRB specifically for HRF systems and the quantized communication rate. We extend our analysis to obtain lower bounds on the Fisher Information Matrix (FIM) and UL communication rate, which we use to characterize quantized HRF systems. Using these derived bounds, we analyze the quantized HRF system through the lens of CRB-rate boundaries. We obtain the CRB-rate boundary through two optimization problems, where each solution point represents a trade-off boundary between the sensing accuracy and the communication rate. Extensive simulations illustrate the influence of ADC resolution, dynamic range (DR), and various system parameters on the CRB-rate boundary of HRF systems. These results offer critical insights into the design of efficient and high-performance HRF systems.
Joint Beamforming for Multi-target Detection and Multi-user Communication in ISAC Systems
Authors: Zongyao Zhao, Zhenyu Liu, Rui Jiang, Zhongyi Li, Xiao-Ping Zhang, Xinke Tang, Yuhan Dong
Date: 2024-11-01 00:00:00
Tasks: Integrated sensing and communication, ISAC

Detecting weak targets is one of the main challenges for integrated sensing and communication (ISAC) systems. Sensing and communication suffer from a performance trade-off in ISAC systems. As the communication demand increases, sensing ability, especially weak target detection performance, will inevitably reduce. Traditional approaches fail to address this issue. In this paper, we develop a joint beamforming scheme and formulate it as a max-min problem to maximize the detection probability of the weakest target under the constraint of the signal-to-interference-plus-noise ratio (SINR) of multi-user communication. An alternating optimization (AO) algorithm is developed for solving the complicated non-convex problem to obtain the joint beamformer. The proposed scheme can direct the transmit energy toward the multiple targets properly to ensure robust multi-target detection performance. Numerical results show that the proposed beamforming scheme can effectively increase the detection probability of the weakest target compared to baseline approaches while ensuring communication performance.
Edge centrality and the total variation of graph distributional signals
Authors: Feng Ji
Date: 2024-11-01 00:00:00
Tasks: Relation

This short note is a supplement to [1], in which the total variation of graph distributional signals is introduced and studied. We introduce a different formulation of total variation and relate it to the notion of edge centrality. The relation provides a different perspective of total variation and may facilitate its computation.
Power Source Allocation for RIS-aided Integrating Sensing, Communication, and Power Transfer Systems Based on NOMA
Authors: Yue Xiu, Yang Zhao, Chenfei Xie, Fatma Benkhelifa, Songjie Yang, Wanting Lyu, Chadi Assi, Ning Wei
Date: 2024-11-01 00:00:00

This paper proposes a novel communication system framework based on a reconfigurable intelligent surface (RIS)-aided integrated sensing, communication, and power transmission (ISCPT) communication system. RIS is used to improve transmission efficiency and sensing accuracy. In addition, non-orthogonal multiple access (NOMA) technology is incorporated in RIS-aided ISCPT systems to boost the spectrum utilization efficiency of RIS-aided ISCPT systems. We consider the power minimization problem of the RIS-aided ISCPT-NOMA system. Power minimization is achieved by jointly optimizing the RIS phase shift, decoding order, power splitting (PS) factor, and transmit beamforming while satisfying quality of service (QoS), radar target sensing accuracy, and energy harvesting constraints. Since the objective function and constraints in the optimization problem are non-convex, the problem is an NP-hard problem. To solve the non-convex problem, this paper proposes a block coordinate descent (BCD) algorithm. Specifically, the non-convex problem is divided into four sub-problems: i.e. the transmit beamforming, RIS phase shift, decoding order and PS factor optimization subproblems. We employ semidefinite relaxation (SDR) and successive convex approximation (SCA) techniques to address the transmit beamforming optimization sub-problem. Subsequently, we leverage the alternating direction method of multipliers (ADMM) algorithm to solve the RIS phase shift optimization problem. As for the decoding order optimization, we provide a closed-form expression. For the PS factor optimization problem, the SCA algorithm is proposed. Simulation results illustrate the effectiveness of our proposed algorithm and highlight the balanced performance achieved across sensing, communication, and power transfer.
Parameter Estimation on Homogeneous Spaces
Authors: Shiraz Khan, Gregory S. Chirikjian
Date: 2024-10-31 00:00:00
Tasks: parameter estimation

The Fisher Information Metric (FIM) and the associated Cram\'er-Rao Bound (CRB) are fundamental tools in statistical signal processing, which inform the efficient design of experiments and algorithms for estimating the underlying parameters. In this article, we investigate these concepts for the case where the parameters lie on a homogeneous space. Unlike the existing Fisher-Rao theory for general Riemannian manifolds, our focus is to leverage the group-theoretic structure of homogeneous spaces, which is often much easier to work with than their Riemannian structure. The FIM is characterized by identifying the homogeneous space with a coset space, the group-theoretic CRB and its corollaries are presented, and its relationship to the Riemannian CRB is clarified. The application of our theory is illustrated using two examples from engineering: (i) estimation of the pose of a robot and (ii) sensor network localization. In particular, these examples demonstrate that homogeneous spaces provide a natural framework for studying statistical models that are invariant with respect to a group of symmetries.
A Novel Acoustic Wearable for Assessment of Tendon Health and Loading Condition
Authors: Amirhossein Yazdkhasti, Hendrik De Klerk, Andreea Renata Lucaciu, Rana Moeinzad, Hamid Ghaednia, Joseph H. Schwab
Date: 2024-10-31 00:00:00

The current methods of assessing tendon health such as clinical examination, imaging techniques, and implanted pressure sensors, are often based on a subjective assessment or are not accurate enough, are extremely expensive, or are limited to relatively large damage such as partial or gross tear of the tendon and cannot accurately assess and monitor smaller damages such as micro tears or strains. This study proposes an acoustic-based wearable capable of estimating tendon load and predicting damage severity in both deep and superficial tendons. Our device consists of an array of acoustic transducers positioned around the targeted body area in the form of a cuff. One of the transducers generates an acoustic wave, which is capable of penetrating deep into the body. As these waves propagate through different tissues, they are influenced by the mechanical and geometrical properties of each tissue. The rest of the transducers are used to measure the propagated waves. The results suggest that the proposed wearable offers a promising alternative to existing superficial tendon monitoring wearable devices by improving the domain of reach. The proposed wearable shows robust performance in estimating the force applied to the tendon. It also can effectively be used to compare the health condition of two tendons and predict the type of damage.
CRB Optimization using a Parametric Scattering Model for Extended Targets in ISAC Systems
Authors: Rang Liu, A. Lee Swindlehurst, Ming Li
Date: 2024-10-31 00:00:00
Tasks: Integrated sensing and communication, ISAC, parameter estimation

This paper presents a novel parametric scattering model (PSM) for sensing extended targets in integrated sensing and communication (ISAC) systems. The PSM addresses the limitations of traditional models by efficiently capturing the target's angular characteristics through a compact set of key parameters, including the central angle and angular spread, enabling efficient optimization. Based on the PSM, we first derive the Cramer-Rao Bound (CRB) for parameter estimation and then propose a beamforming design algorithm to minimize the CRB while meeting both communication signal-to-interference-plus-noise ratio (SINR) and power constraints. By integrating the PSM into the beamforming optimization process, the proposed framework achieves superior CRB performance while balancing the tradeoff between sensing accuracy and communication quality. Simulation results demonstrate that the PSM-based approach consistently outperforms traditional unstructured and discrete scattering models, particularly in resource-limited scenarios, highlighting its practical applicability and scalability.
Interaction between harvesting intervention and birth perturbation in an age-structured model
Authors: Haiyan Xu, Zhigui Lin, Carlos Alberto Santos
Date: 2024-11-05 00:00:00

An age-structured fish model with birth and harvesting pulses is established, where birth pulses are responsible for increasing the amount of fish due to the constant multiple placement of juveniles, and harvesting pulses describe the decrease of fish due to fishing activities. The principal eigenvalue as a threshold value depending on the harvesting and birth intensity is firstly investigated by three different ways. The asymptotic behavior of the population is fully investigated and sufficient conditions for the species to be extinct or persist are given. Numerical simulations suggest that interaction between negative harvesting intervention and positive birth perturbation decides extinction and persistence of the species. It is also shown that perturbation timing plays an important role.