Review
Computer Science, Information Systems
Daquan Feng, Lifeng Lai, Jingjing Luo, Yi Zhong, Canjian Zheng, Kai Ying
Summary: This article introduces the basic concepts and potential applications of URLLC, gives an overview of the latest research in physical layer, link layer, and network layer, and identifies some potential research topics and challenges.
SCIENCE CHINA-INFORMATION SCIENCES
(2021)
Article
Engineering, Electrical & Electronic
Chun-Hung Liu, Di-Chun Liang, Kwang-Cheng Chen, Rung-Hung Gau
Summary: This article studies how to achieve ultra-reliable and low-latency communications in a heterogeneous network by jointly employing open-loop communication and multi-cell association techniques. The proactive multi-cell association (PMCA) scheme significantly improves communication reliability and optimizes the densities of users and access points for maximum reliability. In addition, analyses of uplink and downlink delays show that extremely low latency can be achieved in a single user's virtual cell with appropriate resource allocation.
IEEE TRANSACTIONS ON COMMUNICATIONS
(2021)
Article
Computer Science, Hardware & Architecture
Mohamed Yacine Lezzar, Mustafa Mehmet-Ali
Summary: This paper develops an analytical model for optimizing the performance of URLLC systems with heterogeneous traffic, considering both Grant-Free (GF) and Grant-based (GB) transmission schemes. The study shows that utilizing 5G NR's new scalable numerology can significantly reduce GB's latency, making it suitable for URLLC use cases.
Article
Computer Science, Information Systems
Foteini Karetsi, Evangelos Papapetrou
Summary: Sliding Window RLNC is an efficient class of algorithms for reliable data transmission over unreliable links. We propose the use of two distinct windows to overcome limitations in existing schemes and experimentally show that the proposed strategy outperforms other schemes. This strategy is especially useful for current and future networks with large bandwidth-delay products.
COMPUTER COMMUNICATIONS
(2022)
Article
Engineering, Electrical & Electronic
Saeed R. Khosravirad, Harish Viswanathan, Wei Yu
Summary: This paper introduces a wireless communication protocol for industrial control systems that dynamically creates network-device cooperation based on channel quality awareness to improve system reliability and efficiency. The proposed adaptive network-device cooperation scheme shows significant improvement in spectral efficiency and system reliability compared to existing schemes in the literature, potentially reducing infrastructure costs for future private wireless networks.
IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS
(2021)
Article
Computer Science, Information Systems
Jun-Bae Seo, Waqas Tariq Toor, Hu Jin
Summary: This study investigates a two-step RA procedure for 5G New Radio systems, showing the importance of RA delay for delay-sensitive applications, and proving that the system should operate in the unsaturated region. It also examines the RA delay distribution when IoT devices use geometric probability backoff (GPB) or uniform window backoff (UWB) algorithm.
Article
Engineering, Electrical & Electronic
Mikko A. Uusitalo, Harish Viswanathan, Heli Kokkoniemi-Tarkkanen, Artjom Grudnitsky, Martti Moisio, Teemu Harkonen, Pekka Yli-Paunu, Seppo Horsmanheimo, Dragan Samardzija
Summary: 5G technology has significant potential for enabling port automation, improving flexibility, predictability, and safety in ports. By providing ultra-reliable, low-latency, and high-capacity capabilities, 5G communication networks serve as a connectivity solution for advanced technologies required for port automation. Extensive multi-cell simulations and prototype testing demonstrate the capabilities of 5G for ports.
IEEE COMMUNICATIONS MAGAZINE
(2021)
Article
Automation & Control Systems
Haojun Huang, Wang Miao, Geyong Min, Jialin Tian, Atif Alamri
Summary: 5G networks are expected to provide cost-efficient, reliable, and flexible services for industrial productions and applications by introducing emerging network technologies like blockchain and NFV. NFV-enabled 5G paradigm for industry focuses on URLLC with service chain acceleration and dynamic spectrum sharing built on NFV, blockchain, software-defined networking, and mobile edge computing. A mathematical model is established to study transmission latency of NFV-enabled 5G systems with bursty traffic input, supporting the plan, management, and optimization of such systems for industry.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2021)
Article
Engineering, Electrical & Electronic
Shufeng Li, Mingyu Cai, Libiao Jin, Yao Sun, Hongda Wu, Ping Wang
Summary: This paper designs a non-binary polar-coded SCMA system with a free order matching strategy to address the issues of delay and reliability. By proposing a new decoding method and detection algorithm, as well as optimizing the update method of the algorithm, the system achieves better BER performance and lower complexity.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2022)
Article
Computer Science, Hardware & Architecture
Tobias Kallehauge, Anders E. Kalor, Pablo Ramirez-Espinosa, Maxime Guillaud, Petar Popovski
Summary: This article presents a feasible framework that utilizes spatial consistency of channel statistics to achieve high reliability for Ultra-Reliable Low-Latency Communications (URLLC). By utilizing statistical radio maps, the propagation conditions can be predicted and communication parameters can be selected, while also enabling the selection of transmission rates that achieve the target level of reliability.
IEEE WIRELESS COMMUNICATIONS
(2023)
Article
Computer Science, Information Systems
Adeeb Salh, Lukman Audah, Nor Shahida Mohd Shah, Abdulraqeb Alhammadi, Qazwan Abdullah, Yun Hee Kim, Samir Ahmed Al-Gailani, Shipun A. Hamzah, Bashar Ali F. Esmail, Akram A. Almohammedi
Summary: The 6G wireless communication network is a promising technique that offers a fully data-driven network for optimizing end-to-end behavior and handling big volumes of real-time data. It enables ultra-reliable and low latency communication, enhancing information transmission to around 1 Tb/s with a 0.1 millisecond latency. Further improvements in 6G can be made by incorporating artificial intelligence and deep learning to create an effective data-driven AI system for intelligent devices and networks.
Article
Computer Science, Artificial Intelligence
Sanjay Bhardwaj, Dong-Seong Kim
Summary: The research proposes a node identification algorithm based on dragonfly swarms, mapping bio-natural systems and legacy communication into metrics of latency and reliability for URLLC. Experimental results demonstrate that this algorithm has a significant impact on improving latency, reliability, packet loss rate, and throughput.
NEURAL COMPUTING & APPLICATIONS
(2021)
Article
Engineering, Electrical & Electronic
Alessandro Brighente, Jafar Mohammadi, Paolo Baracca, Silvio Mandelli, Stefano Tomasin
Summary: In this paper, a interference prediction method is proposed to enhance link adaptation for ultra reliable low latency communications (URLLC) in networks beyond the fifth generation (b5G). A kernel based probability density estimation algorithm is developed to provide statistical analysis and a low complexity version suitable for practical scenarios. The proposed scheme is validated by comparison with state-of-the-art solutions.
IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS
(2022)
Article
Telecommunications
Yuli Yang
Summary: This research proposes a novel transmission strategy using permutations to improve the throughput of wireless networks. By dividing the application layer data into two parts and processing them differently, network congestion is alleviated, resulting in lower latency and fewer dropped packets.
IEEE COMMUNICATIONS LETTERS
(2021)
Article
Computer Science, Information Systems
Laszlo Toka
Summary: The article proposes extending traditional cloud computing infrastructure with compute resources deployed close to end users, integrated with carrier networks to meet the demands of novel applications. Emphasis is on integration and providing a powerful resource provisioning platform. A novel topology clustering method is introduced to schedule applications across a worldwide scale of edge clusters.
JOURNAL OF GRID COMPUTING
(2021)
Article
Computer Science, Information Systems
Mojtaba Vaezi, Amin Azari, Saeed R. Khosravirad, Mahyar Shirvanimoghaddam, M. Mahdi Azari, Danai Chasaki, Petar Popovski
Summary: This paper provides a comprehensive survey on existing and emerging communication solutions for serving IoT applications in the context of cellular, wide-area, as well as non-terrestrial networks. The solutions include grant-free access and channel coding for short-packet communications, non-orthogonal multiple access, and on-device intelligence. It also discusses the potential of using emerging deep learning and federated learning techniques for enhancing the efficiency and security of IoT communication.
IEEE COMMUNICATIONS SURVEYS AND TUTORIALS
(2022)
Article
Computer Science, Information Systems
Weiyu Ju, Dong Yuan, Wei Bao, Liming Ge, Bing Bing Zhou
Summary: We present a novel online decision-making solution that dynamically finds the optimal path of a given decision tree based on contextual bandits analysis. By applying contextual bandits to each decision node, we propose the Dynamic Path Identifier (DPI) algorithm to maximize the accumulated outcome. Numerical evaluations are provided to complement the theoretical analysis.
WORLD WIDE WEB-INTERNET AND WEB INFORMATION SYSTEMS
(2023)
Article
Telecommunications
Wen Jun Lim, Rana Abbas, Yonghui Li, Branka Vucetic, Mahyar Shirvanimoghaddam
Summary: This article introduces the design and analysis of analog fountain codes in a multiple access channel. By proposing different encoding and decoding schemes and evaluating their performance, the optimal parameters of AFC codes are found, improving the transmission efficiency of the multiple access scenario.
IEEE COMMUNICATIONS LETTERS
(2022)
Article
Telecommunications
Mahyar Shirvanimoghaddam, Ayoob Salari, Yifeng Gao, Aradhika Guha
Summary: This letter discusses the issue of communication errors in federated learning (FL). By modeling the connection between devices and the central node using a packet erasure channel, the authors prove that the FL algorithm can still converge to the same global parameter even in the presence of communication errors. They also find that in the case of a uniformly distributed dataset, an FL algorithm that only uses fresh updates may converge faster than one that uses past local updates.
IEEE COMMUNICATIONS LETTERS
(2022)
Article
Telecommunications
Muhammad Basit Shahab, Sarah J. Johnson, Mahyar Shirvanimoghaddam, Mischa Dohler
Summary: This article proposes a simple and efficient strategy for grant-free PD-NOMA by introducing special activity indicator symbols for early collision detection, which helps the base station identify successful transmissions and collisions before processing actual data.
TRANSACTIONS ON EMERGING TELECOMMUNICATIONS TECHNOLOGIES
(2022)
Article
Computer Science, Information Systems
Shizhe Zang, Wei Bao, Phee Lep Yeoh, Branka Vucetic, Yonghui Li
Summary: This paper proposes a smart online aggregated reservation (SOAR) framework to help MEC brokers minimize the cost of reserving resources for multiple users. The framework includes a task aggregation algorithm to improve plan utilization and plan reservation algorithms to determine when to reserve which plans. Trace-driven simulations verify the cost advantage of the SOAR framework.
IEEE TRANSACTIONS ON MOBILE COMPUTING
(2023)
Article
Computer Science, Theory & Methods
Zhengjie Yang, Wei Bao, Dong Yuan, Nguyen H. Tran, Albert Y. Zomaya
Summary: Federated learning (FL) is a fast-developing technique that trains a global model based on a distributed dataset. This study proposes FedNAG, a FL model that employs Nesterov Accelerated Gradient (NAG), and compares it with conventional FL methods. Experimental results show that FedNAG improves learning accuracy and reduces training time under various settings.
IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS
(2022)
Article
Engineering, Electrical & Electronic
Peng Wang, Yonghui Li, Zihuai Lin, Mahyar Shirvanimoghaddam, Ok-Sun Park, Giyoon Park, Branka Vucetic
Summary: In this paper, the maximum likelihood (ML) decoding performance of the RMA scheme in an AWGN channel with BPSK modulation is investigated. For the first time, the ensemble weight distribution of the RMA scheme is derived. An upper bound on the decoding error performance of the RMA scheme under ML decoding in an AWGN channel with BPSK modulation is also derived. The continuous genetic algorithm is then used to optimize the parameters of the RMA scheme, with simulation results showing the tightness of the derived bound and the superiority of the optimized degree distribution.
IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS
(2023)
Letter
Pathology
Xiao Feng, Wei Bao, Zhen Yue, Jiandong Wang, Qunli Shi
PATHOLOGY INTERNATIONAL
(2023)
Article
Computer Science, Hardware & Architecture
Peng Cao, Tai Yang, Kai Wang, Wei Bao, Hao Yan
Summary: This article introduces a learning-based method for predicting path timing for multiple unknown corners at low voltage. It utilizes long short-term memory (LSTM) to exploit circuit topology correlation with timing and a multigate mixture-of-experts (MMoE) network to capture correlation among all analysis corners.
IEEE DESIGN & TEST
(2023)
Article
Telecommunications
Fatemeh Ghanami, Saleheh Poursheikhali, Mahyar Shirvanimoghaddam
Summary: In this letter, a dynamic re-transmission strategy is proposed for the two-user uplink non-orthogonal multiple access scenario with hybrid automatic repeat request (HARQ) and multiple re-transmissions. The proposed scheme assigns different tasks to high-power and low-power users when receiving negative acknowledgments (NACKs) from the base station (BS). By utilizing a Markov model, the dynamics of the proposed scheme and the conventional scheme are analyzed, and optimal power splitting ratios are found to minimize packet error rates (PERs) for both users. Simulation results demonstrate that the proposed dynamic approach significantly improves the PER of the low-power user with minimal impact on the high-power user's PER.
IEEE COMMUNICATIONS LETTERS
(2023)
Article
Engineering, Electrical & Electronic
Chentao Yue, Vera Miloslavskaya, Mahyar Shirvanimoghaddam, Branka Vucetic, Yonghui Li
Summary: This article reviews the potential channel decoding techniques for ultra-reliable low-latency communications (URLLC), focusing on error-rate performance and computational complexity for structured and random short codes. The article provides a comprehensive comparison of different candidate decoding techniques and makes recommendations for decoder selections and potential research directions.
IEEE COMMUNICATIONS MAGAZINE
(2023)
Article
Engineering, Electrical & Electronic
Chentao Yue, Mahyar Shirvanimoghaddam, Alva Kosasih, Giyoon Park, Ok-Sun Park, Wibowo Hardjawana, Branka Vucetic, Yonghui Li
Summary: This paper proposes a density evolution (DE) framework for analyzing the iterative joint decoding (JD) in non-orthogonal multiple access (NOMA) systems using ordered-statistics decoding (OSD) for short block codes. The density-transform feature of the soft-output OSD (SOSD) is investigated through deriving the density of the extrinsic log-likelihood ratio (LLR) with known priori LLR densities. The DE framework characterizes the density-transform features of nodes over bipartite graphs (BGs) under binary phase shift keying (BPSK) transmission, accurately tracking the evolution of LLRs during iterative decoding, especially at moderate-to-high SNRs.
IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS
(2023)
Article
Chemistry, Multidisciplinary
Fan Huang, Nan Yang, Huaming Chen, Wei Bao, Dong Yuan
Summary: With the widespread use of end devices, online multi-label learning has become popular due to the huge and rapidly updated data generated by users using the Internet of Things devices. However, in many scenarios, the geographically distributed user data are difficult to centralize for training machine learning models. To overcome this issue, we propose a distributed approach for multi-label classification, which trains the models in distributed computing nodes without sharing the source data from each node. Our experiments show that our algorithm outperforms the centralized online multi-label classification algorithm in F1 score, but there is minimal difference in Hamming loss.
APPLIED SCIENCES-BASEL
(2023)
Article
Computer Science, Artificial Intelligence
Xiuwen Gong, Dong Yuan, Wei Bao
Summary: There are two strategies to deal with ambiguity in partial label learning, one is to treat all candidate labels equally as the ground-truth label, and the other is to utilize the underlying structure of the data for disambiguation. This article proposes an effective paradigm called DML-PLL, which aims to learn a discriminative distance metric and iteratively identify the ground-truth label in partial label learning.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2023)
