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The Road to Next-Generation Multiple Access: A 50-Year Tutorial Review
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| Pengarang | : | - |
| Nama Majalah/Jurnal | : | Proceedings of the IEEE |
| Volume / Edisi | : | 112 (No. 9) |
| Halaman | : | 1100-1148 |
| Abstrak | : | The evolution of wireless communications has been significantly influenced by remarkable advancements in multiple access (MA) technologies over the past five decades, shaping the landscape of modern connectivity. Within this context, a comprehensive tutorial review is presented, focusing on representative MA techniques developed over the past 50 years. The following areas are explored: 1) the foundational principles and information-theoretic capacity limits of power-domain nonorthogonal multiple access (NOMA) are characterized, along with its extension to multiple-input multiple-output (MIMO)-NOMA; 2) several MA transmission schemes exploiting the spatial domain are investigated, encompassing both conventional space-division multiple access (SDMA)/MIMO-NOMA systems and near-field MA systems utilizing spherical-wave propagation models; 3) application of NOMA to integrated sensing and communications (ISAC) systems is studied. This includes an introduction to typical NOMA-based downlink (DL)/uplink (UL) ISAC frameworks, followed by an evaluation of their performance limits using a mutual information (MI)-based analytical framework; and 4) major issues and research opportunities associated with the integration of MA with other emerging technologies are identified to facilitate MA in the next-generation networks, i.e., next-generation multiple access (NGMA). Throughout this article, promising directions are highlighted to inspire future research endeavors in the realm of MA and NGMA. |
Domain Generalization for Medical Image Analysis
| Pengarang | : | - |
| Nama Majalah/Jurnal | : | Proceedings of the IEEE |
| Volume / Edisi | : | 112 (No. 10) |
| Halaman | : | 1583-1609 |
| Abstrak | : | Medical image analysis (MedIA) has become an essential tool in medicine and healthcare, aiding in disease diagnosis, prognosis, and treatment planning, and recent successes in deep learning (DL) have made significant contributions to its advances. However, deploying DL models for MedIA in real-world situations remains challenging due to their failure to generalize across the distributional gap between training and testing samples—a problem known as domain shift. Researchers have dedicated their efforts to developing various DL methods to adapt and perform robustly on unknown and out-of-distribution (OOD) data distributions. This article comprehensively reviews domain generalization (DG) studies specifically tailored for MedIA. We provide a holistic view of how DG techniques interact within the broader MedIA system, going beyond methodologies to consider the operational implications on the entire MedIA workflow. Specifically, we categorize DG methods into data-level, feature-level, model-level, and analysis-level methods. We show how those methods can be used in various stages of the MedIA workflow with DL equipped from data acquisition to model prediction and analysis. Furthermore, we critically analyze the strengths and weaknesses of various methods, unveiling future research opportunities. |
Next-Generation Multiple Access
| Pengarang | : | - |
| Nama Majalah/Jurnal | : | Proceedings of the IEEE |
| Volume / Edisi | : | 112 (No. 9) |
| Halaman | : | 1095-1099 |
| Abstrak | : | The pressure to develop new network architectures and multiple access technologies is driven by increasing demands on network performance, number of devices, network traffic, and use cases. Recent advances in open radio access networks (RANs) with open interfaces and software-defined network functionalities allow adaptability in terms of medium access control and physical layer, but also flexibility in terms of network architectures. The aim of this tutorial is to provide a comprehensive overview of the current set of network architectures for wireless access together with next-generation multiple access technologies. It starts with the classical models for multiple access channel (MAC), broadcast channel (BC), and interference channel (IC) from network information theory and derives the fundamental results on capacity regions and their coding and signal processing schemes. Extensions to multicarrier, multiantenna, and multicell scenarios are discussed. The evolution from orthogonal to spatial-division multiple access (SDMA), nonorthogonal multiple access (NOMA), and rate splitting multiple access (RSMA) techniques and their performance guarantees are carefully explained. Recent advances toward multiconnectivity, cloud-RAN (C-RAN), and cell-free multiple access (CFMA) are explained. The data rate benefits of an anecdotal open RAN network are developed and the corresponding user data rates are calculated. Massive random and grant-free access schemes are also discussed. The tutorial concludes with a list of open research questions. |
Unleashing GPT on the Metaverse: Savior or Destroyer
| Pengarang | : | - |
| Nama Majalah/Jurnal | : | Proceedings of the IEEE |
| Volume / Edisi | : | 112 (No. 10) |
| Halaman | : | 1572-1582 |
| Abstrak | : | Incorporating artificial intelligence (AI) technology, particularly large language models (LLMs), is becoming increasingly vital for developing immersive and interactive metaverse experiences. GPT, a representative LLM developed by OpenAI, is leading LLM development and gaining attention for its potential in building the metaverse. This article delves into the pros and cons of utilizing GPT for metaverse-based education, entertainment, personalization, and support. Dynamic and personalized experiences are possible with this technology, but there are also legitimate privacy, bias, and ethical issues to consider. This article aims to help readers understand the possible influence of GPT, according to its unique technological advantages, on the metaverse and how it may be used to effectively create a more immersive and engaging virtual environment by evaluating these opportunities and obstacles. |
Corrections to Brain-Inspired Computing: A Systematic Survey and Future Trends
| Pengarang | : | Thomas Prince |
| Nama Majalah/Jurnal | : | Proceedings of the IEEE |
| Volume / Edisi | : | 112 (No. 12) |
| Halaman | : | 1850-1850 |
| Abstrak | : | Presents corrections to the paper, (Corrections to “Brain-Inspired Computing: A Systematic Survey and Future Trends”). |
Cross Modal Retrieval A Systematic Review of Methods and Future Directions
| Pengarang | : | - |
| Nama Majalah/Jurnal | : | Proceedings of the IEEE |
| Volume / Edisi | : | 112 (No. 11) |
| Halaman | : | 1716-1754 |
| Abstrak | : | With the exponential surge in diverse multimodal data, traditional unimodal retrieval methods struggle to meet the needs of users seeking access to data across various modalities. To address this, cross-modal retrieval has emerged, enabling interaction across modalities, facilitating semantic matching, and leveraging complementarity and consistency between heterogeneous data. Although prior literature has reviewed the field of cross-modal retrieval, it suffers from numerous deficiencies in terms of timeliness, taxonomy, and comprehensiveness. This article conducts a comprehensive review of cross-modal retrieval’s evolution, spanning from shallow statistical analysis techniques to vision-language pretraining (VLP) models. Commencing with a comprehensive taxonomy grounded in machine learning paradigms, mechanisms, and models, this article delves deeply into the principles and architectures underpinning existing cross-modal retrieval methods. Furthermore, it offers an overview of widely used benchmarks, metrics, and performances. Lastly, this article probes the prospects and challenges that confront contemporary cross-modal retrieval, while engaging in a discourse on potential directions for further progress in the field. To facilitate the ongoing research on cross-modal retrieval, we develop a user-friendly toolbox and an open-source repository at https://cross-modal-retrieval.github.io. |
Hairpin Windings: Twists and Bends of a Technological Breakthrough
| Pengarang | : | - |
| Nama Majalah/Jurnal | : | Proceedings of the IEEE |
| Volume / Edisi | : | 112 (No. 12) |
| Halaman | : | 1831-1849 |
| Abstrak | : | Magnetic windings, in general, and small drives, in particular, are typically associated with thin round copper wires. This group of small drives includes electrical machines for automotive applications, ranging from ancillary units to traction machines for both hybrid electric vehicle (HEV) and battery electric vehicle (BEV) [1], [2]. Wire-wound machines can refer to well-established techniques for widely automatic manufacturing except for traction machines with distributed windings, which still contain manual steps in most assembly lines, particularly after the insertion process [3]. Machines typically wind the loops of continuous wires on a bobbin with a linear or flyer-winding technique outside the stator and pull them from one side of the stator to the other into the slots. The overhang on both ends of the stator, the so-called end turns, forms automatically from the continuous loops. |
Building Resilient Web 3.0 Infrastructure With Quantum Information Technologies and Blockchain An Ambilateral View
| Pengarang | : | Xiaoxu Ren,Nikolas Kristiyanto, SJ,Nurfindarti, Erti |
| Nama Majalah/Jurnal | : | Proceedings of the IEEE |
| Volume / Edisi | : | 112 (No. 11) |
| Halaman | : | 1686-1715 |
| Abstrak | : | Web 3.0 pursues the establishment of decentralized ecosystems through blockchain technologies, driving digital transformation in commerce and governance. With consensus algorithms and smart contracts grounded in cryptographic technologies, Web 3.0 enables secure and transparent digital services, such as digital identity, asset management, decentralized autonomous organizations (DAOs), and decentralized finance (DeFi), fostering integration between digital and physical economies. As quantum devices rapidly advance, Web 3.0 is being developed in parallel with the deployment of quantum cloud computing and quantum Internet. In this regard, quantum computing first disrupts the original cryptographic systems that protect data security while reshaping modern cryptography with enhanced quantum computing and communication capabilities. This article provides a comprehensive overview of blockchain-based Web 3.0, examining its quantum and postquantum advancements from two key perspectives. On the one hand, postquantum migration methods and quantum-resistant signatures offer robust solutions to safeguard blockchain against quantum threats. On the other hand, quantum and postquantum encryption and verification algorithms boost blockchain performance, creating a decentralized, secure, and value-driven system. Additionally, we outline potential applications of quantum blockchain and offer guidance for implementation within the Web 3.0 ecosystem. Finally, we discuss future directions for developing a provably secure and decentralized digital ecosystem. |
Learning Power Flow Models and Constraints From Time Synchronized Measurements
| Pengarang | : | - |
| Nama Majalah/Jurnal | : | Proceedings of the IEEE |
| Volume / Edisi | : | 112 (No. 12) |
| Halaman | : | 1799-1830 |
| Abstrak | : | Key operational and protection functions of power systems (e.g., optimal power flow scheduling and control, state estimation (SE), protection, and fault location) rely on the availability of models to represent the system’s behavior under different operating conditions. Power system models require knowledge of the components’ electrical parameters and the system topology. However, these data may be inaccurate for several reasons (e.g., inaccurate information of components datasheets and/or outdated topological information). The deployment of time synchronization in phasor measurement units (PMUs) and remote terminal units (RTUs) enables the collection of large datasets of synchronized measurements to infer power system models and learn associated power flow constraints. Within this context, this article presents a comprehensive review of measurement-based estimation methods for power flow models using time-synchronized measurements. It begins by exploring advancements in time dissemination technologies and the characterization of uncertainties in PMUs and instrument transformers (ITs), along with their implications for parameter estimation. This article then examines the power system parameter estimation problem, highlighting key techniques and methodologies. In the following, this article focuses on measurement models for state-independent power flow model estimation, including line parameters, admittance matrices, topology, and joint state-parameter estimation. Finally, this article discusses recent approaches for estimating state-dependent power flow models, with particular reference to linearized power flow approximations because of their large use in control applications. |
Semantic Communication A Survey on Research Landscape Challenges and Future Directions
| Pengarang | : | - |
| Nama Majalah/Jurnal | : | Proceedings of the IEEE |
| Volume / Edisi | : | 112 (No. 11) |
| Halaman | : | 1649-1685 |
| Abstrak | : | Amid the global rollout of fifth-generation (5G) services, researchers in academia, industry, and national laboratories have been developing proposals for the sixth-generation (6G), whose materialization is fraught with many fundamental challenges. To alleviate these challenges, a deep learning (DL)-enabled semantic communication (SemCom) has emerged as a promising 6G technology enabler, which embodies a paradigm shift that can change the status quo viewpoint that wireless connectivity is an opaque data pipe carrying messages whose context-dependent meanings have been ignored. Since 6G is also critical for the materialization of major SemCom use cases, the paradigms of 6G for SemCom and SemCom for 6G call for a tighter integration of 6G and SemCom. For this purpose, this comprehensive article provides the fundamentals of semantic information, semantic representation, and semantic entropy; details the state-of-the-art SemCom research landscape; presents the major SemCom trends and use cases; discusses current SemCom theories; exposes the fundamental and major challenges of SemCom; and offers future research directions for SemCom. We hope this article stimulates many lines of research on SemCom theories, algorithms, and implementation. |