{"title":"Atomic Norm Minimization-based DoA Estimation for IRS-assisted Sensing Systems","authors":"Renwang Li, Shu Sun, Meixia Tao","doi":"arxiv-2409.09982","DOIUrl":"https://doi.org/arxiv-2409.09982","url":null,"abstract":"Intelligent reflecting surface (IRS) is expected to play a pivotal role in\u0000future wireless sensing networks owing to its potential for high-resolution and\u0000high-accuracy sensing. In this work, we investigate a multi-target\u0000direction-of-arrival (DoA) estimation problem in a semi-passive IRS-assisted\u0000sensing system, where IRS reflecting elements (REs) reflect signals from the\u0000base station to targets, and IRS sensing elements (SEs) estimate DoA based on\u0000echo signals reflected by the targets. {First of all, instead of solely relying\u0000on IRS SEs for DoA estimation as done in the existing literature, this work\u0000fully exploits the DoA information embedded in both IRS REs and SEs matrices\u0000via the atomic norm minimization (ANM) scheme. Subsequently, the Cram'er-Rao\u0000bound for DoA estimation is derived, revealing an inverse proportionality to\u0000$MN^3+NM^3$ under the case of identity covariance matrix of the IRS measurement\u0000matrix and a single target, where $M$ and $N$ are the number of IRS SEs and\u0000REs, respectively. Finally, extensive numerical results substantiate the\u0000superior accuracy and resolution performance of the proposed ANM-based DoA\u0000estimation method over representative baselines.","PeriodicalId":501034,"journal":{"name":"arXiv - EE - Signal Processing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142251382","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Wavenumber-Domain Near-Field Channel Estimation: Beyond the Fresnel Bound","authors":"Xufeng Guo, Yuanbin Chen, Ying Wang, Zhaocheng Wang, Chau Yuen","doi":"arxiv-2409.10123","DOIUrl":"https://doi.org/arxiv-2409.10123","url":null,"abstract":"In the near-field context, the Fresnel approximation is typically employed to\u0000mathematically represent solvable functions of spherical waves. However, these\u0000efforts may fail to take into account the significant increase in the lower\u0000limit of the Fresnel approximation, known as the Fresnel distance. The lower\u0000bound of the Fresnel approximation imposes a constraint that becomes more\u0000pronounced as the array size grows. Beyond this constraint, the validity of the\u0000Fresnel approximation is broken. As a potential solution, the wavenumber-domain\u0000paradigm characterizes the spherical wave using a spectrum composed of a series\u0000of linear orthogonal bases. However, this approach falls short of covering the\u0000effects of the array geometry, especially when using Gaussian-mixed-model\u0000(GMM)-based von Mises-Fisher distributions to approximate all spectra. To fill\u0000this gap, this paper introduces a novel wavenumber-domain ellipse fitting\u0000(WDEF) method to tackle these challenges. Particularly, the channel is\u0000accurately estimated in the near-field region, by maximizing the closed-form\u0000likelihood function of the wavenumber-domain spectrum conditioned on the\u0000scatterers' geometric parameters. Simulation results are provided to\u0000demonstrate the robustness of the proposed scheme against both the distance and\u0000angles of arrival.","PeriodicalId":501034,"journal":{"name":"arXiv - EE - Signal Processing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142251370","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Rate-Splitting Multiple Access for Coexistence of Semantic and Bit Communications","authors":"Yuanwen Liu, Bruno Clerckx","doi":"arxiv-2409.10314","DOIUrl":"https://doi.org/arxiv-2409.10314","url":null,"abstract":"In the sixth generation (6G) of cellular networks, the demands for capacity\u0000and connectivity will increase dramatically to meet the requirements of\u0000emerging services for both humans and machines. Semantic communication has\u0000shown great potential because of its efficiency, and suitability for users who\u0000only care about the semantic meaning. But bit communication is still needed for\u0000users requiring original messages. Therefore, there will be a coexistence of\u0000semantic and bit communications in future networks. This motivates us to\u0000explore how to allocate resources in such a coexistence scenario. We\u0000investigate different uplink multiple access (MA) schemes for the coexistence\u0000of semantic users and a bit user, namely orthogonal multiple access (OMA),\u0000non-orthogonal multiple access (NOMA) and rate-splitting multiple access\u0000(RSMA). We characterize the rate regions achieved by those MA schemes. The\u0000simulation results show that RSMA always outperforms NOMA and has better\u0000performance in high semantic rate regimes compared to OMA. We find that RSMA\u0000scheme design, rate region, and power allocation are quite different in the\u0000coexistence scenario compared to the bit-only communication, primarily due to\u0000the need to consider the understandability in semantic communications.\u0000Interestingly, in contrast to bit-only communications where RSMA is capacity\u0000achieving without any need for time sharing, in the coexistence scenario, time\u0000sharing helps enlarging RSMA rate region.","PeriodicalId":501034,"journal":{"name":"arXiv - EE - Signal Processing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142251374","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Xi Wang, Xin Liu, Songming Zhu, Zhanwen Li, Lina Gao
{"title":"Self-Updating Vehicle Monitoring Framework Employing Distributed Acoustic Sensing towards Real-World Settings","authors":"Xi Wang, Xin Liu, Songming Zhu, Zhanwen Li, Lina Gao","doi":"arxiv-2409.10259","DOIUrl":"https://doi.org/arxiv-2409.10259","url":null,"abstract":"The recent emergence of Distributed Acoustic Sensing (DAS) technology has\u0000facilitated the effective capture of traffic-induced seismic data. The\u0000traffic-induced seismic wave is a prominent contributor to urban vibrations and\u0000contain crucial information to advance urban exploration and governance.\u0000However, identifying vehicular movements within massive noisy data poses a\u0000significant challenge. In this study, we introduce a real-time semi-supervised\u0000vehicle monitoring framework tailored to urban settings. It requires only a\u0000small fraction of manual labels for initial training and exploits unlabeled\u0000data for model improvement. Additionally, the framework can autonomously adapt\u0000to newly collected unlabeled data. Before DAS data undergo object detection as\u0000two-dimensional images to preserve spatial information, we leveraged\u0000comprehensive one-dimensional signal preprocessing to mitigate noise.\u0000Furthermore, we propose a novel prior loss that incorporates the shapes of\u0000vehicular traces to track a single vehicle with varying speeds. To evaluate our\u0000model, we conducted experiments with seismic data from the Stanford 2 DAS\u0000Array. The results showed that our model outperformed the baseline model\u0000Efficient Teacher and its supervised counterpart, YOLO (You Only Look Once), in\u0000both accuracy and robustness. With only 35 labeled images, our model surpassed\u0000YOLO's mAP 0.5:0.95 criterion by 18% and showed a 7% increase over Efficient\u0000Teacher. We conducted comparative experiments with multiple update strategies\u0000for self-updating and identified an optimal approach. This approach surpasses\u0000the performance of non-overfitting training conducted with all data in a single\u0000pass.","PeriodicalId":501034,"journal":{"name":"arXiv - EE - Signal Processing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142251378","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Joint Beamforming and Illumination Pattern Design for Beam-Hopping LEO Satellite Communications","authors":"Jing Wang, Chenhao Qi, Shui Yu, Shiwen Mao","doi":"arxiv-2409.10127","DOIUrl":"https://doi.org/arxiv-2409.10127","url":null,"abstract":"Since hybrid beamforming (HBF) can approach the performance of fully-digital\u0000beamforming (FDBF) with much lower hardware complexity, we investigate the HBF\u0000design for beam-hopping (BH) low earth orbit (LEO) satellite communications\u0000(SatComs). Aiming at maximizing the sum-rate of totally illuminated beam\u0000positions during the whole BH period, we consider joint beamforming and\u0000illumination pattern design subject to the HBF constraints and sum-rate\u0000requirements. To address the non-convexity of the HBF constraints, we\u0000temporarily replace the HBF constraints with the FDBF constraints. Then we\u0000propose an FDBF and illumination pattern random search (FDBF-IPRS) scheme to\u0000optimize illumination patterns and fully-digital beamformers using constrained\u0000random search and fractional programming methods. To further reduce the\u0000computational complexity, we propose an FDBF and illumination pattern\u0000alternating optimization (FDBF-IPAO) scheme, where we relax the integer\u0000illumination pattern to continuous variables and after finishing all the\u0000iterations we quantize the continuous variables into integer ones. Based on the\u0000fully-digital beamformers designed by the FDBF-IPRS or FDBF-IPAO scheme, we\u0000propose an HBF alternating minimization algorithm to design the hybrid\u0000beamformers. Simulation results show that the proposed schemes can achieve\u0000satisfactory sum-rate performance for BH LEO SatComs.","PeriodicalId":501034,"journal":{"name":"arXiv - EE - Signal Processing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142251379","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Charbel Bou Chaaya, Abanoub M. Girgis, Mehdi Bennis
{"title":"Learning Latent Wireless Dynamics from Channel State Information","authors":"Charbel Bou Chaaya, Abanoub M. Girgis, Mehdi Bennis","doi":"arxiv-2409.10045","DOIUrl":"https://doi.org/arxiv-2409.10045","url":null,"abstract":"In this work, we propose a novel data-driven machine learning (ML) technique\u0000to model and predict the dynamics of the wireless propagation environment in\u0000latent space. Leveraging the idea of channel charting, which learns compressed\u0000representations of high-dimensional channel state information (CSI), we\u0000incorporate a predictive component to capture the dynamics of the wireless\u0000system. Hence, we jointly learn a channel encoder that maps the estimated CSI\u0000to an appropriate latent space, and a predictor that models the relationships\u0000between such representations. Accordingly, our problem boils down to training a\u0000joint-embedding predictive architecture (JEPA) that simulates the latent\u0000dynamics of a wireless network from CSI. We present numerical evaluations on\u0000measured data and show that the proposed JEPA displays a two-fold increase in\u0000accuracy over benchmarks, for longer look-ahead prediction tasks.","PeriodicalId":501034,"journal":{"name":"arXiv - EE - Signal Processing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142251381","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Emo-DPO: Controllable Emotional Speech Synthesis through Direct Preference Optimization","authors":"Xiaoxue Gao, Chen Zhang, Yiming Chen, Huayun Zhang, Nancy F. Chen","doi":"arxiv-2409.10157","DOIUrl":"https://doi.org/arxiv-2409.10157","url":null,"abstract":"Current emotional text-to-speech (TTS) models predominantly conduct\u0000supervised training to learn the conversion from text and desired emotion to\u0000its emotional speech, focusing on a single emotion per text-speech pair. These\u0000models only learn the correct emotional outputs without fully comprehending\u0000other emotion characteristics, which limits their capabilities of capturing the\u0000nuances between different emotions. We propose a controllable Emo-DPO approach,\u0000which employs direct preference optimization to differentiate subtle emotional\u0000nuances between emotions through optimizing towards preferred emotions over\u0000less preferred emotional ones. Instead of relying on traditional neural\u0000architectures used in existing emotional TTS models, we propose utilizing the\u0000emotion-aware LLM-TTS neural architecture to leverage LLMs' in-context learning\u0000and instruction-following capabilities. Comprehensive experiments confirm that\u0000our proposed method outperforms the existing baselines.","PeriodicalId":501034,"journal":{"name":"arXiv - EE - Signal Processing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142251429","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Self-supervised Multimodal Speech Representations for the Assessment of Schizophrenia Symptoms","authors":"Gowtham Premananth, Carol Espy-Wilson","doi":"arxiv-2409.09733","DOIUrl":"https://doi.org/arxiv-2409.09733","url":null,"abstract":"Multimodal schizophrenia assessment systems have gained traction over the\u0000last few years. This work introduces a schizophrenia assessment system to\u0000discern between prominent symptom classes of schizophrenia and predict an\u0000overall schizophrenia severity score. We develop a Vector Quantized Variational\u0000Auto-Encoder (VQ-VAE) based Multimodal Representation Learning (MRL) model to\u0000produce task-agnostic speech representations from vocal Tract Variables (TVs)\u0000and Facial Action Units (FAUs). These representations are then used in a\u0000Multi-Task Learning (MTL) based downstream prediction model to obtain class\u0000labels and an overall severity score. The proposed framework outperforms the\u0000previous works on the multi-class classification task across all evaluation\u0000metrics (Weighted F1 score, AUC-ROC score, and Weighted Accuracy).\u0000Additionally, it estimates the schizophrenia severity score, a task not\u0000addressed by earlier approaches.","PeriodicalId":501034,"journal":{"name":"arXiv - EE - Signal Processing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142251383","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Brandon T. HuntMontana Technological University, Hussein MoradiIdaho National Laboratory, Behrouz Farhang-BoroujenyThe University of Utah
{"title":"Multicarrier Spread Spectrum Communications with Noncontiguous Subcarrier Bands for HF Skywave Links","authors":"Brandon T. HuntMontana Technological University, Hussein MoradiIdaho National Laboratory, Behrouz Farhang-BoroujenyThe University of Utah","doi":"arxiv-2409.09723","DOIUrl":"https://doi.org/arxiv-2409.09723","url":null,"abstract":"Growing traffic over the high-frequency (HF) band poses significant\u0000challenges to establishing robust communication links. While existing\u0000spread-spectrum HF transceivers are, to some degree, robust against harsh HF\u0000channel conditions, their performance significantly degrades in the presence of\u0000strong co-channel interference. To improve performance in congested channel\u0000conditions, we propose a filter-bank based multicarrier spread-spectrum\u0000waveform with noncontiguous subcarrier bands. The use of noncontiguous\u0000subcarriers allows the system to at once leverage the robustness of a wideband\u0000system while retaining the frequency agility of a narrowband system. In this\u0000study, we explore differences between contiguous and noncontiguous systems by\u0000considering their respective peak-to-average power ratios (PAPRs) and\u0000matched-filter responses. Additionally, we develop a modified filter-bank\u0000receiver structure to facilitate both efficient signal processing and\u0000noncontiguous channel estimation. We conclude by presenting simulated and\u0000over-the-air results of the noncontiguous waveform, demonstrating both its\u0000robustness in harsh HF channels and its enhanced performance in congested\u0000spectral conditions.","PeriodicalId":501034,"journal":{"name":"arXiv - EE - Signal Processing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142251377","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Mohammadali Mohammadi, Zahra Mobini, Hien Quoc Ngo, Michail Matthaiou
{"title":"Ten Years of Research Advances in Full-Duplex Massive MIMO","authors":"Mohammadali Mohammadi, Zahra Mobini, Hien Quoc Ngo, Michail Matthaiou","doi":"arxiv-2409.09732","DOIUrl":"https://doi.org/arxiv-2409.09732","url":null,"abstract":"We present an overview of ongoing research endeavors focused on in-band\u0000full-duplex (IBFD) massive multiple-input multiple-output (MIMO) systems and\u0000their applications. In response to the unprecedented demands for mobile traffic\u0000in concurrent and upcoming wireless networks, a paradigm shift from\u0000conventional cellular networks to distributed communication systems becomes\u0000imperative. Cell-free massive MIMO (CF-mMIMO) emerges as a practical and\u0000scalable implementation of distributed/network MIMO systems, serving as a\u0000crucial physical layer technology for the advancement of next-generation\u0000wireless networks. This architecture inherits benefits from co-located massive\u0000MIMO and distributed systems and provides the flexibility for integration with\u0000the IBFD technology. We delineate the evolutionary trajectory of cellular\u0000networks, transitioning from conventional half-duplex multi-user MIMO networks\u0000to IBFD CF-mMIMO. The discussion extends further to the emerging paradigm of\u0000network-assisted IBFD CF-mMIMO (NAFD CF-mMIMO), serving as an energy-efficient\u0000prototype for asymmetric uplink and downlink communication services. This novel\u0000approach finds applications in dual-functionality scenarios, including\u0000simultaneous wireless power and information transmission, wireless\u0000surveillance, and integrated sensing and communications. We highlight various\u0000current use case applications, discuss open challenges, and outline future\u0000research directions aimed at fully realizing the potential of NAFD CF-mMIMO\u0000systems to meet the evolving demands of future wireless networks.","PeriodicalId":501034,"journal":{"name":"arXiv - EE - Signal Processing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142251418","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}