{"title":"A State-of-the-Art Survey on Full-Duplex Network Design","authors":"Yonghwi Kim;Hyung-Joo Moon;Hanju Yoo;Byoungnam Kim;Kai-Kit Wong;Chan-Byoung Chae","doi":"10.1109/JPROC.2024.3363218","DOIUrl":"10.1109/JPROC.2024.3363218","url":null,"abstract":"Full-duplex (FD) technology is gaining popularity for integration into a wide range of wireless networks due to its demonstrated potential in recent studies. In contrast to half-duplex (HD) technology, the implementation of FD in networks necessitates considering internode interference (INI) from various network perspectives. When deploying FD technology in networks, several critical factors must be taken into account. These include self-interference (SI) and the requisite SI cancellation (SIC) processes, as well as the selection of multiple user equipment (UE) per time slot. In addition, INI, including cross-link interference (CLI) and intercell interference (ICI), becomes a crucial issue during concurrent uplink (UL) and downlink (DL) transmission and reception, similar to SI. Since most INIs are challenging to eliminate, a comprehensive investigation that covers radio resource control (RRC), medium access control (MAC), and the physical (PHY) layer is essential in the context of FD network design, rather than focusing on individual network layers and types. This article covers state-of-the-art studies, including protocols and documents from the third-generation partnership project (3GPP) for FD, MAC protocol, user scheduling, and CLI handling. The methods are also compared through a network-level system simulation based on 3-D ray tracing.","PeriodicalId":20556,"journal":{"name":"Proceedings of the IEEE","volume":"112 5","pages":"463-486"},"PeriodicalIF":23.2,"publicationDate":"2024-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139988432","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"When Robotics Meets Wireless Communications: An Introductory Tutorial","authors":"Daniel Bonilla Licea;Mounir Ghogho;Martin Saska","doi":"10.1109/JPROC.2024.3380373","DOIUrl":"10.1109/JPROC.2024.3380373","url":null,"abstract":"The importance of ground mobile robots (MRs) and unmanned aerial vehicles (UAVs) within the research community, industry, and society is growing fast. Nowadays, many of these agents are equipped with communication systems that are, in some cases, essential to successfully achieve certain tasks. In this context, we have begun to witness the development of a new interdisciplinary research field at the intersection of robotics and communications. This research field has been boosted by the intention of integrating UAVs within the 5G and 6G communication networks and will undoubtedly lead to many important applications in the near future. Nevertheless, one of the main obstacles to the development of this research area is that most researchers address these problems by oversimplifying either the robotics or the communications aspects. Doing so impedes the ability to reach the full potential of this new interdisciplinary research area. In this tutorial, we present some of the modeling tools necessary to address problems involving both robotics and communication from an interdisciplinary perspective. As an illustrative example of such problems, we focus on the issue of communication-aware trajectory planning in this tutorial.","PeriodicalId":20556,"journal":{"name":"Proceedings of the IEEE","volume":"112 2","pages":"140-177"},"PeriodicalIF":20.6,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140340589","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Scanning the Issue","authors":"","doi":"10.1109/JPROC.2024.3381483","DOIUrl":"https://doi.org/10.1109/JPROC.2024.3381483","url":null,"abstract":"Gustav Fechner’s 1860 delineation of psychophysics, the measurement of sensation in relation to its stimulus, is widely considered to be the advent of modern psychological science. In psychophysics, a researcher parametrically varies some aspects of a stimulus and measures the resulting changes in a human subject’s experience of that stimulus; doing so gives insight to the determining relationship between a sensation and the physical input that evoked it. This approach is used heavily in perceptual domains, including signal detection, threshold measurement, and ideal observer analysis. Scientific fields, such as vision science, have always leaned heavily on the methods and procedures of psychophysics, but there is now growing appreciation of them by machine learning researchers, sparked by widening overlap between biological and artificial perception. Machine perception that is guided by behavioral measurements, as opposed to guidance restricted to arbitrarily assigned human labels, has significant potential to fuel further progress in artificial intelligence.","PeriodicalId":20556,"journal":{"name":"Proceedings of the IEEE","volume":"112 2","pages":"86-87"},"PeriodicalIF":20.6,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10496399","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140544085","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Future Special Issues/Special Sections of the Proceedings","authors":"","doi":"10.1109/JPROC.2024.3380213","DOIUrl":"https://doi.org/10.1109/JPROC.2024.3380213","url":null,"abstract":"","PeriodicalId":20556,"journal":{"name":"Proceedings of the IEEE","volume":"112 2","pages":"178-178"},"PeriodicalIF":20.6,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10496410","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140544282","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Proceedings of the IEEE: Stay Informed. Become Inspired.","authors":"","doi":"10.1109/JPROC.2024.3380217","DOIUrl":"https://doi.org/10.1109/JPROC.2024.3380217","url":null,"abstract":"","PeriodicalId":20556,"journal":{"name":"Proceedings of the IEEE","volume":"112 2","pages":"C4-C4"},"PeriodicalIF":20.6,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10496382","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140544283","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Justin Dulay;Sonia Poltoratski;Till S. Hartmann;Samuel E. Anthony;Walter J. Scheirer
{"title":"Informing Machine Perception With Psychophysics","authors":"Justin Dulay;Sonia Poltoratski;Till S. Hartmann;Samuel E. Anthony;Walter J. Scheirer","doi":"10.1109/JPROC.2024.3380905","DOIUrl":"https://doi.org/10.1109/JPROC.2024.3380905","url":null,"abstract":"Gustav Fechner’s 1860 delineation of psychophysics, the measurement of sensation in relation to its stimulus, is widely considered to be the advent of modern psychological science. In psychophysics, a researcher parametrically varies some aspects of a stimulus and measures the resulting changes in a human subject’s experience of that stimulus; doing so gives insight into the determining relationship between a sensation and the physical input that evoked it. This approach is used heavily in perceptual domains, including signal detection, threshold measurement, and ideal observer analysis. Scientific fields, such as vision science, have always leaned heavily on the methods and procedures of psychophysics, but there is now growing appreciation of them by machine learning researchers, sparked by widening overlap between biological and artificial perception \u0000<xref>[1]</xref>\u0000, \u0000<xref>[2]</xref>\u0000, \u0000<xref>[3]</xref>\u0000, \u0000<xref>[4]</xref>\u0000, \u0000<xref>[5]</xref>\u0000. Machine perception that is guided by behavioral measurements, as opposed to guidance restricted to arbitrarily assigned human labels, has significant potential to fuel further progress in artificial intelligence (AI).","PeriodicalId":20556,"journal":{"name":"Proceedings of the IEEE","volume":"112 2","pages":"88-96"},"PeriodicalIF":20.6,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140544317","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
He Zhang;Bang Wu;Xingliang Yuan;Shirui Pan;Hanghang Tong;Jian Pei
{"title":"Trustworthy Graph Neural Networks: Aspects, Methods, and Trends","authors":"He Zhang;Bang Wu;Xingliang Yuan;Shirui Pan;Hanghang Tong;Jian Pei","doi":"10.1109/JPROC.2024.3369017","DOIUrl":"10.1109/JPROC.2024.3369017","url":null,"abstract":"Graph neural networks (GNNs) have emerged as a series of competent graph learning methods for diverse real-world scenarios, ranging from daily applications such as recommendation systems and question answering to cutting-edge technologies such as drug discovery in life sciences and n-body simulation in astrophysics. However, task performance is not the only requirement for GNNs. Performance-oriented GNNs have exhibited potential adverse effects, such as vulnerability to adversarial attacks, unexplainable discrimination against disadvantaged groups, or excessive resource consumption in edge computing environments. To avoid these unintentional harms, it is necessary to build competent GNNs characterized by trustworthiness. To this end, we propose a comprehensive roadmap to build trustworthy GNNs from the view of the various computing technologies involved. In this survey, we introduce basic concepts and comprehensively summarize existing efforts for trustworthy GNNs from six aspects, including robustness, explainability, privacy, fairness, accountability, and environmental well-being. In addition, we highlight the intricate cross-aspect relations between the above six aspects of trustworthy GNNs. Finally, we present a thorough overview of trending directions for facilitating the research and industrialization of trustworthy GNNs.","PeriodicalId":20556,"journal":{"name":"Proceedings of the IEEE","volume":"112 2","pages":"97-139"},"PeriodicalIF":20.6,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140188884","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"IEEE Women in Engineering","authors":"","doi":"10.1109/JPROC.2024.3384829","DOIUrl":"https://doi.org/10.1109/JPROC.2024.3384829","url":null,"abstract":"","PeriodicalId":20556,"journal":{"name":"Proceedings of the IEEE","volume":"112 2","pages":"179-179"},"PeriodicalIF":20.6,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10496430","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140544155","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"IEEE Membership","authors":"","doi":"10.1109/JPROC.2024.3380215","DOIUrl":"https://doi.org/10.1109/JPROC.2024.3380215","url":null,"abstract":"","PeriodicalId":20556,"journal":{"name":"Proceedings of the IEEE","volume":"112 2","pages":"C3-C3"},"PeriodicalIF":20.6,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10496406","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140544302","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"IEEE Foundation","authors":"","doi":"10.1109/JPROC.2024.3384831","DOIUrl":"https://doi.org/10.1109/JPROC.2024.3384831","url":null,"abstract":"","PeriodicalId":20556,"journal":{"name":"Proceedings of the IEEE","volume":"112 2","pages":"180-180"},"PeriodicalIF":20.6,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10496419","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140544153","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}