OPAC - Pencarian Artikel Jurnal & Majalah Library USD
Menampilkan semua artikel (Halaman 745 dari 34166, Total: 341652 data)
Doubling Down on Wireless Capacity: A Review of Integrated Circuits, Systems, and Networks for Full Duplex
klik untuk membaca file PDF
| Pengarang | : | - |
| Nama Majalah/Jurnal | : | Proceedings of the IEEE |
| Volume / Edisi | : | 112 (No. 5) |
| Halaman | : | 405-432 |
| Abstrak | : | The relentless demand for data in our society has driven the continuous evolution of wireless technologies to enhance network capacity. While current deployments of 5G have made strides in this direction using massive multiple-input-multiple-output (MIMO) and millimeter-wave (mmWave) bands, all existing wireless systems operate in a half-duplex (HD) mode. Full-duplex (FD) wireless communication, on the other hand, enables simultaneous transmission and reception (STAR) of signals at the same frequency, offering advantages such as enhanced spectrum efficiency, improved data rates, and reduced latency. This article presents a comprehensive review of FD wireless systems, with a focus on hardware design, implementation, cross-layered considerations, and applications. The major bottleneck in achieving FD communication is the presence of self-interference (SI) signals from the transmitter (TX) to the receiver, and achieving SI cancellation (SIC) with real-time adaption is critical for FD deployment. The review starts by establishing a system-level understanding of FD wireless systems, followed by a review of the architectures of antenna interfaces and integrated RF and baseband (BB) SI cancellers, which show promise in enabling low-cost, small-form-factor, portable FD systems. We then discuss digital cancellation techniques, including digital signal processing (DSP)- and learning-based algorithms. The challenges presented by FD phased-array and MIMO systems are discussed, followed by system-level aspects, including optimization algorithms, opportunities in the higher layers of the networking protocol stack, and testbed integration. Finally, the relevance of FD systems in applications such as next-generation (xG) wireless, mmWave repeaters, radars, and noncommunication domains is highlighted. Overall, this comprehensive review provides valuable insights into the design, implementation, and applications of FD wireless systems while opening up new directions for future research. |
When Multitask Learning Meets Partial Supervision: A Computer Vision Review
| Pengarang | : | - |
| Nama Majalah/Jurnal | : | Proceedings of the IEEE |
| Volume / Edisi | : | 112 (No. 6) |
| Halaman | : | 516-543 |
| Abstrak | : | Multitask learning (MTL) aims to learn multiple tasks simultaneously while exploiting their mutual relationships. By using shared resources to simultaneously calculate multiple outputs, this learning paradigm has the potential to have lower memory requirements and inference times compared to the traditional approach of using separate methods for each task. Previous work in MTL has mainly focused on fully supervised methods, as task relationships (TRs) can not only be leveraged to lower the level of data dependency of those methods but also improve the performance. However, MTL introduces a set of challenges due to a complex optimization scheme and a higher labeling requirement. This article focuses on how MTL could be utilized under different partial supervision settings to address these challenges. First, this article analyses how MTL traditionally uses different parameter sharing techniques to transfer knowledge in between tasks. Second, it presents different challenges arising from such a multiobjective optimization (MOO) scheme. Third, it introduces how task groupings (TGs) can be achieved by analyzing TRs. Fourth, it focuses on how partially supervised methods applied to MTL can tackle the aforementioned challenges. Lastly, this article presents the available datasets, tools, and benchmarking results of such methods. The reviewed articles, categorized following this work, are available at https://github.com/Klodivio355/MTL-CV-Review. |
Exploring the Boundaries of Connected Systems: Communications for Hard-to-Reach Areas and Extreme Conditions
| Pengarang | : | Muhammad A. Imran |
| Nama Majalah/Jurnal | : | Proceedings of the IEEE |
| Volume / Edisi | : | 112 (No. 7) |
| Halaman | : | 912-945 |
| Abstrak | : | Cellular communication standards have been established to ensure connectivity across most urban environments, complemented by deployment hardware and facilities tailored for city life. At the same time, numerous initiatives seek to broaden connectivity to rural and developing areas. However, with nearly half the global population still offline, there is an urgent need to drive research toward enhancing connectivity in areas and conditions that deviate from the norm. This article delves into innovative communication solutions not only for hard-to-reach and extreme environments but also introduces “hard-to-serve” areas as a crucial, yet underexplored, category within the broader spectrum of connectivity challenges. We explore the latest advancements in communication systems designed for environments subject to extreme temperatures, harsh weather, excessive dust, or even disasters such as fires. Our exploration spans the entire communication stack, covering communications on isolated islands, sparsely populated regions, mountainous terrains, and even underwater and underground settings. We highlight system architectures, hardware, materials, algorithms, and other pivotal technologies that promise to connect these challenging areas. Through case studies, we explore the application of 5G for innovative research, long range (LoRa) for audio messages and emails, LoRa wireless connections, free-space optics, communications in underwater and underground scenarios, delay-tolerant networks, satellite links, and the strategic use of shared spectrum and TV white space (TVWS) to improve mobile connectivity in secluded and remote regions. These studies also touch on prevalent challenges such as power outages, regulatory gaps, technological availability, and human resource constraints, where we introduce the concept of peri-urban hard-to-serve areas where populations might struggle with affordability or lack the skills for traditional connectivity solutions. This article provides an exhaustive summary of our research, showcasing how 6G and future networks will play a crucial role in delivering connectivity to areas that are hard-to-reach, hard-to-serve, or subject to extreme conditions (ECs). |
Green Edge AI: A Contemporary Survey
| Pengarang | : | Yuyi Mao |
| Nama Majalah/Jurnal | : | Proceedings of the IEEE |
| Volume / Edisi | : | 112 (No. 7) |
| Halaman | : | 880-911 |
| Abstrak | : | Artificial intelligence (AI) technologies have emerged as pivotal enablers across a multitude of industries, including consumer electronics, healthcare, and manufacturing, largely due to their significant resurgence over the past decade. The transformative power of AI is primarily derived from the utilization of deep neural networks (DNNs), which require extensive data for training and substantial computational resources for processing. Consequently, DNN models are typically trained and deployed on resource-rich cloud servers. However, due to potential latency issues associated with cloud communications, deep learning (DL) workflows (e.g., DNN training and inference) are increasingly being transitioned to wireless edge networks in proximity to end-user devices (EUDs). This shift is designed to support latency-sensitive applications and has given rise to a new paradigm of edge AI, which will play a critical role in upcoming sixth-generation (6G) networks to support ubiquitous AI applications. Despite its considerable potential, edge AI faces substantial challenges, mostly due to the dichotomy between the resource limitations of wireless edge networks and the resource-intensive nature of DL. Specifically, the acquisition of large-scale data, as well as the training and inference processes of DNNs, can rapidly deplete the battery energy of EUDs. This necessitates an energy-conscious approach to edge AI to ensure both optimal and sustainable performance. In this article, we present a contemporary survey on green edge AI. We commence by analyzing the principal energy consumption components of edge AI systems to identify the fundamental design principles of green edge AI. Guided by these principles, we then explore energy-efficient design methodologies for the three critical tasks in edge AI systems, including training data acquisition, edge training, and edge inference. Finally, we underscore potential future research directions to further enhance the energy efficiency (EE) of edge AI. |
A Primer on Near-Field Communications for Next-Generation Multiple Access
| Pengarang | : | Chongjun Ouyang |
| Nama Majalah/Jurnal | : | Proceedings of the IEEE |
| Volume / Edisi | : | 112 (No. 9) |
| Halaman | : | 1527-1565 |
| Abstrak | : | Multiple-antenna technologies are advancing toward the development of extremely large aperture arrays and the utilization of extremely high frequencies, driving the progress of next-generation multiple access (NGMA). This evolution is accompanied by the emergence of near-field communications (NFCs), characterized by spherical-wave propagation, which introduces additional range dimensions to the channel and enhances system throughput. In this context, a tutorial-based primer on NFC is presented, emphasizing its applications in multiuser communications and multiple access (MA). The following areas are investigated: 1) the commonly used near-field channel models are reviewed along with their simplifications under various near-field conditions; 2) building upon these models, the information-theoretic capacity limits of NFC-MA are analyzed, including the derivation of the sum-rate capacity and capacity region, and their upper limits for both downlink and uplink scenarios; and 3) a detailed investigation of near-field multiuser beamforming design is presented, offering low-complexity and effective NFC-MA design methodologies in both the spatial and wavenumber (angular) domains. Throughout these investigations, near-field MA is compared with its far-field counterpart to highlight its superiority and flexibility in terms of interference management, thereby laying the groundwork for achieving NGMA. |
Multiple Access Techniques for Intelligent and Multifunctional 6G: Tutorial, Survey, and Outlook
| Pengarang | : | - |
| Nama Majalah/Jurnal | : | Proceedings of the IEEE |
| Volume / Edisi | : | 112 (No. 7) |
| Halaman | : | 832-879 |
| Abstrak | : | Multiple access (MA) is a crucial part of any wireless system and refers to techniques that make use of the resource dimensions (e.g., time, frequency, power, antenna, code, and message) to serve multiple users/devices/machines/ services, ideally in the most efficient way. Given the increasing need of multifunctional wireless networks for integrated communications, sensing, localization, and computing, coupled with the surge of machine learning (ML)/artificial intelligence (AI) in wireless networks, MA techniques are expected to experience a paradigm shift in 6G and beyond. In this article, we provide a tutorial, survey, and outlook on past, emerging, and future MA techniques and pay particular attention to how wireless network intelligence and multifunctionality will lead to a rethinking of those techniques. This article starts with an overview of orthogonal, physical-layer multicasting, space domain, power domain (PD), rate-splitting, code-domain MAs, MAs in other domains, and random access (RA), and highlights the importance of conducting research in universal MA (UMA) to shrink instead of grow the knowledge tree of MA schemes by providing a unified understanding of MA schemes across all resource dimensions. It then jumps into rethinking MA schemes in the era of wireless network intelligence, covering AI for MA such as AI-empowered resource allocation, optimization, channel estimation, and receiver designs, for different MA schemes, and MA for AI such as federated learning (FL)/edge intelligence and over-the-air computation (AirComp). We then discuss MA for network multifunctionality and the interplay between MA and integrated sensing, localization, and communications, covering MA for joint sensing and communications, multimodal sensing-aided communications, multimodal sensing and digital twin-assisted communications, and communication-aided sensing/localization systems. We finish with studying MA for emerging intelligent applications such as semantic communications (SeComs), virtual reality (VR), and smart radio and reconfigurable intelligent surfaces (RISs), before presenting a roadmap toward 6G standardization. Throughout the text, we also point out numerous directions that are promising for future research. |
Ultradense Cell-Free Massive MIMO for 6G: Technical Overview and Open Questions
| Pengarang | : | Marta R. Stoeckel |
| Nama Majalah/Jurnal | : | Proceedings of the IEEE |
| Volume / Edisi | : | 112 (No. 7) |
| Halaman | : | 805-831 |
| Abstrak | : | Ultradense cell-free massive multiple-input–multiple-output (CF-MMIMO) has emerged as a promising technology expected to meet the future ubiquitous connectivity requirements and ever-growing data traffic demands in sixth generation (6G). This article provides a contemporary overview of ultradense CF-MMIMO networks and addresses important unresolved questions on their future deployment. We first present a comprehensive survey of state-of-the-art research on CF-MMIMO and ultradense networks. Then, we discuss the key challenges of CF-MMIMO under ultradense scenarios such as low-complexity architecture and processing, low-complexity/scalable resource allocation, fronthaul limitation, massive access, synchronization, and channel acquisition. Finally, we answer key open questions, considering different design comparisons and discussing suitable methods dealing with the key challenges of ultradense CF-MMIMO. The discussion aims to provide a valuable roadmap for interesting future research directions in this area, facilitating the development of CF-MMIMO for 6G. |
Multiple Access in the Era of Distributed Computing and Edge Intelligence
| Pengarang | : | - |
| Nama Majalah/Jurnal | : | Proceedings of the IEEE |
| Volume / Edisi | : | 112 (No. 9) |
| Halaman | : | 1497-1526 |
| Abstrak | : | This article focuses on the latest research and innovations in fundamental next-generation multiple access (NGMA) techniques and the coexistence with other key technologies for the sixth generation (6G) of wireless networks. In more detail, we first examine multiaccess edge computing (MEC), which is critical to meeting the growing demand for data processing and computational capacity at the edge of the network, as well as network slicing. We then explore over-the-air (OTA) computing, which is considered to be an approach that provides fast and efficient computation of various functions. We also explore semantic communications, identified as an effective way to improve communication systems by focusing on the exchange of meaningful information, thus minimizing unnecessary data and increasing efficiency. The interrelationship between machine learning (ML) and multiple access technologies is also reviewed, with an emphasis on federated learning (FL), federated distillation (FD), split learning (SL), reinforcement learning (RL), and the development of ML-based multiple access protocols. Finally, the concept of digital twinning and its role in network management is discussed, highlighting how virtual replication of physical networks can lead to improvements in network efficiency and reliability. |
Wireless Information and Energy Transfer in the Era of 6G Communications
| Pengarang | : | - |
| Nama Majalah/Jurnal | : | Proceedings of the IEEE |
| Volume / Edisi | : | 112 (No. 7) |
| Halaman | : | 764-804 |
| Abstrak | : | Wireless information and energy transfer (WIET) represents an emerging paradigm that employs controllable transmission of radio frequency signals for the dual purpose of data communication and wireless charging. As such, WIET is widely regarded as an enabler of envisioned sixth-generation (6G) use cases that rely on energy-sustainable Internet-of-Things (IoT) networks, such as smart cities and smart grids. Meeting the quality-of-service demands of WIET, in terms of both data transfer and power delivery, requires effective codesign of the information and energy signals. In this article, we present the main principles and design aspects of WIET, focusing on its integration in 6G networks. First, we discuss how conventional communication notions, such as resource allocation and waveform design, need to be revisited in the context of WIET. Next, we consider various candidate 6G technologies that can boost WIET efficiency, namely, holographic multiple-input multiple-output, near-field beamforming, terahertz communication, intelligent reflecting surfaces (IRSs), and reconfigurable (fluid) antenna arrays. We introduce respective WIET design methods, analyze the promising performance gains of these WIET systems, and discuss challenges, open issues, and future research directions. Finally, a near-field energy beamforming scheme and a power-based IRS beamforming algorithm are experimentally validated using a wireless energy transfer testbed. The vision of WIET in communication systems has been gaining momentum in recent years, with constant progress with respect to theoretical and also practical aspects. The comprehensive overview of the state of the art of WIET presented in this article highlights the potential of WIET systems and their overall benefits in 6G networks. |
Next-Generation Multiple Access for Integrated Sensing and Communications
| Pengarang | : | Yaxi Liu |
| Nama Majalah/Jurnal | : | Proceedings of the IEEE |
| Volume / Edisi | : | 112 (No. 9) |
| Halaman | : | 1467-1496 |
| Abstrak | : | Integrated sensing and communications (ISAC) has received considerable attention from both industry and academia. By sharing the spectrum and hardware platform, ISAC significantly reduces costs and improves spectral, energy, and hardware efficiencies. To support the large number of communication users (CUs) and sensing targets (STs), the design of multiple access (MA) is a fundamental issue in ISAC. MA techniques in ISAC are expected to avoid mutual interference between sensing and communicating functions under the critical constraints of both functions. In this article, we present an overview on approaches of MA for ISAC, from orthogonal transmission strategies to nonorthogonal ones, realized in time, frequency, code, spatial, delay-Doppler, power, and/or multiple domains. We discuss their individual implementation schemes and corresponding resource allocation strategies, as well as highlight future research opportunities. |