Article
Engineering, Electrical & Electronic
Nyaura Mwinyi Kibinda, Xiaohu Ge
Summary: The paper proposes a user-centric cooperative transmissions-based handover scheme to reduce the handover rate in ultra-dense networks. By modeling the base station locations as the Poison point process, an analytical expression of the handover rate for the user equipment with arbitrary movement trajectory is derived. The numerical results demonstrate that the proposed scheme significantly decreases the handover rate compared to traditional methods, and the introduced GCHO-S scheme further reduces the handover cost.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2022)
Article
Chemistry, Multidisciplinary
Jun Li, Tong Gao, Bo He, Wenjing Zheng, Fei Lin
Summary: Non-orthogonal multiple access (NOMA) technology allows multiple users to share the same time-frequency resource for signal transmission, leading to improved spectral efficiency and throughput. This study focuses on user grouping and power allocation in the downlink of a multi-carrier NOMA system, with the optimization goal being the sum rate. The proposed step-by-step optimization method includes improving the user grouping approach to avoid grouping users with similar channel gains and utilizing a deep learning power allocation algorithm. The simulation results demonstrate that the deep learning power allocation method outperforms the fractional transmit power allocation and fixed power allocation methods, enhancing the system's sum rate by about 2.2% and 19%, respectively. Additionally, the power allocation methods proposed in this study achieve approximately a 10% improvement in the system's sum rate compared to the fractional transmit power allocation method used among subcarriers and between multiplexed users.
APPLIED SCIENCES-BASEL
(2023)
Article
Engineering, Electrical & Electronic
Zhenjiang Shi, Jiajia Liu, Shangwei Zhang, Nei Kato
Summary: With the rapid development of machine-type communications (MTC), there is a need for future communication architecture to provide services for both human-type communications (HTC) and MTC with unique characteristics. Ultra-dense network (UDN), which supports massive device access through dense deployment of small base stations (SBSs), is proposed as a promising solution to the challenges brought by MTC. This study investigates the joint optimization of massive access and resource management in UDN, proposing a multi-agent deep reinforcement learning based SBS state selection scheme and utilizing power-domain non-orthogonal multiple access to improve system throughput.
IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS
(2022)
Article
Chemistry, Analytical
Jie Zeng, Jiaying Sun, Yuxin Song, Jiajia Mei, Tiejun Lv, Shidong Zhou
Summary: This paper focuses on a user-centered NOMA collaboration system in an ultra-dense network and proposes two algorithms, a dynamic packet matching algorithm and an iterative algorithm based on convex functions. These algorithms improve system throughput while ensuring user quality of service.
Article
Computer Science, Hardware & Architecture
Zhong Yang, Yaru Fu, Yuanwei Liu, Yue Chen, Junshan Zhang
Summary: This article explores the utilization of artificial intelligence techniques to solve challenges in non-orthogonal multiple access-enabled fog radio access networks (NOMA-F-RANs). The architecture of NOMA-F-RANs and the potential applications of AI-driven techniques are elaborated. Case studies demonstrate the efficacy of AI-enabled methods in feature extraction and cooperative caching. Future trends of AI-driven NOMA-F-RANs, including research issues and challenges, are identified.
IEEE WIRELESS COMMUNICATIONS
(2022)
Article
Computer Science, Hardware & Architecture
Zhong Yang, Yaru Fu, Yuanwei Liu, Yue Chen, Junshan Zhang
Summary: This article discusses how artificial intelligence techniques can be used to solve the challenges in NOMA-F-RANs, including introducing the architecture and key modules, reviewing potentially applicable AI techniques, and demonstrating the effectiveness of AI methods through case studies. Future trends include identifying open research issues and challenges.
IEEE WIRELESS COMMUNICATIONS
(2022)
Article
Computer Science, Theory & Methods
Yuhan Su, Zhibin Gao, Xiaojiang Du, Mohsen Guizani
Summary: This paper proposes a solution for the joint BS clustering and resource allocation problem in a 6G heterogeneous UDN system. A user-centric BS clustering algorithm is proposed based on many-to-many matching, taking into account the constraint of system capacity. A user-centric resource allocation algorithm is also proposed based on network partitioning, which minimizes interference and achieves orthogonal allocation of resource blocks. Numerical results show that the proposed methods outperform benchmark solutions in terms of system rate, user rate, and spectral efficiency.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2023)
Article
Computer Science, Information Systems
Haiyong Zeng, Xu Zhu, Yufei Jiang, Zhongxiang Wei, Lizhen Chen
Summary: The proposed hierarchical symbiotic transmission strategy using cooperative-nonorthogonal multiple access (C-NOMA) improves system throughput and user connectivity in multi-carrier cognitive radio networks. By promoting certain secondary users as relays, both the primary and secondary networks can benefit from improved communication. Sub-carrier assignment and power allocation solutions are also presented to enhance system performance.
IEEE WIRELESS COMMUNICATIONS LETTERS
(2022)
Article
Engineering, Electrical & Electronic
Jianglong Li, Xianfu Lei, Panagiotis D. Diamantoulakis, Lisheng Fan, George K. Karagiannidis
Summary: We investigate the physical layer security of a downlink cooperative non-orthogonal multiple access system with an untrusted relay. To improve the secrecy sum rate, a friendly jammer (FJ) is used. We formulate an optimization problem to maximize the secrecy sum rate by optimizing the power allocation at both the source and the FJ, and solve it iteratively using the alternating optimization method. We also study the secrecy sum rate of the proposed system with imperfect channel state information, and validate the effectiveness of the proposed FJ based schemes through simulation results.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2022)
Article
Telecommunications
Pavlina Koleva, Vladimir Poulkov
Summary: In ultra-dense network scenarios, new mobility management approaches are needed to ensure reliable service provision, seamless connectivity, and high throughput. This paper proposes a heuristic approach for AP grouping in user-centric UDN based on metrics reflecting user density, distribution, requirements, and available resources in the APs. By representing the AP grouping process and user association as a dynamic service provision system, the proposed approach improves the performance in terms of user allocation, mobility, and service requests.
WIRELESS PERSONAL COMMUNICATIONS
(2022)
Article
Telecommunications
Guoquan Li, Zijie Hong, Yu Pang, Yongjun Xu, Zhengwen Huang
Summary: In this paper, a MIMO-NOMA system based on spatial modulation is proposed to achieve higher spectral efficiency. By investigating a resource allocation problem and employing graph theory and auxiliary variable method, an improved algorithm is proposed and demonstrated to outperform traditional methods through simulation.
DIGITAL COMMUNICATIONS AND NETWORKS
(2022)
Article
Physics, Multidisciplinary
Huanyu Li, Hui Li, Youling Zhou
Summary: This paper investigates resource optimization schemes in a marine communication scenario based on NOMA, using the weighted achievable rate (WAR) as the optimization objective, introducing an improved joint power and user allocation scheme. Experimental results show that utilizing the multi-choice knapsack algorithm combined with dynamic programming can improve WAR performance by 7.47%, while the proposed fully polynomial-time approximation algorithm can achieve 99.55% approximate optimized performance with reduced complexity.
Article
Computer Science, Information Systems
Jianbo Du, Wenhuan Liu, Guangyue Lu, Jing Jiang, Daosen Zhai, F. Richard Yu, Zhiguo Ding
Summary: The article discusses a NOMA-MEC-based Internet-of-Things network and proposes a joint optimization framework to maximize effective system capacity and total energy saving. The effective system capacity is improved by introducing NOMA from the wireless side and optimizing task offloading decisions from the IoT device side, while energy saving is maximized through computation resource allocation on the device-side and various techniques on the wireless side. The proposed joint optimization algorithm demonstrates good performance in both effective system capacity optimization and energy saving maximization through abundant simulation results.
IEEE INTERNET OF THINGS JOURNAL
(2021)
Article
Engineering, Electrical & Electronic
Mengru Wu, Qingyang Song, Lei Guo, Abbas Jamalipour
Summary: This paper proposes a novel design to maximize the sum-rate of a cooperative NOMA system by optimizing user pairing and resource allocation, while ensuring target data rates and minimum harvested energy requirements. A two-step user pairing and resource allocation algorithm is introduced to address the challenging non-convex MINLP problem, with theoretical convergence proof. The proposed algorithm outperforms existing schemes in terms of performance gains demonstrated through simulation results.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2021)
Article
Computer Science, Information Systems
Maryam Moghimi, Abolfazl Zakeri, Mohammad Reza Javan, Nader Mokari, Derrick Wing Kwan Ng
Summary: In this paper, a novel joint resource allocation and cooperative caching scheme for PD-NOMA-based HetNets is proposed. The scheme aims to minimize network cost while satisfying QoS, caching, subcarrier assignment, and power allocation constraints. Experimental results show that the proposed resource management algorithm can significantly reduce the total cost.
IEEE TRANSACTIONS ON MOBILE COMPUTING
(2022)
Article
Computer Science, Artificial Intelligence
Naili Luo, Yulong Ye, Wu Lin, Qiuzhen Lin, Victor C. M. Leung
Summary: A novel multimodal multiobjective memetic algorithm is proposed in this paper, which preserves more global and local Pareto optimal solution sets using a local detection mechanism and a clustering-based selection strategy. Experimental results demonstrate the superior performance of the proposed algorithm.
Article
Computer Science, Theory & Methods
Dan Xia, Chun Jiang, Jiafu Wan, Jiong Jin, Victor C. M. Leung, Miguel Martinez-Garcia
Summary: This article provides a survey on heterogeneous networks in smart factories, focusing on access control, fusion, and management in the context of expanding IIoT connectivity. It explores the challenges posed by the contradiction between high QoS requirements and limited network bandwidth in smart factory networks, and discusses existing and future network technologies that can address these challenges. Additionally, it analyzes current network fusion architecture and identifies areas for improvement.
ACM COMPUTING SURVEYS
(2023)
Article
Telecommunications
Shao-Di Wang, Hui-Ming Wang, Wenjie Wang, Victor C. M. Leung
Summary: In 5G new radio, unencrypted synchronization signal blocks can be detected by an intelligent adversary to obtain the full physical cell identity (PCI) and launch targeted jamming on the physical broadcast channel (PBCH). This can cause failure in decoding the master information block (MIB) and severe denial of services for users trying to access the PCI cell. This letter proposes a method to detect PBCH intelligent jamming at the user side by using the principal direction of PBCH demodulation reference signal space, which is significantly impacted in low mobility scenarios when PBCH-IJ occurs. Numerical results confirm the effectiveness of the detection method.
IEEE COMMUNICATIONS LETTERS
(2023)
Article
Engineering, Electrical & Electronic
Shihao Shen, Yuanming Ren, Yanli Ju, Xiaofei Wang, Wenyu Wang, Victor C. M. Leung
Summary: In this paper, a multi-tier edge-cloud computing framework called EdgeMatrix is proposed to maximize system throughput and guarantee different SLA priorities. The framework uses the NMAC algorithm to redefine physical resources and a multi-task mechanism for matching requests and services. Experimental results show that EdgeMatrix outperforms the closest baseline by 36.7% in terms of throughput while still ensuring SLA priorities.
IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS
(2023)
Article
Computer Science, Information Systems
M. S. Syam, Sheng Luo, Yue Ling Che, Kaishun Wu, Victor C. M. Leung
Summary: This article proposes an energy-efficient intelligent reflecting surface (IRS)-aided wireless-powered industrial Internet-of-Things network by optimizing the energy beamforming, information receiving beamforming, phase shift of IRS, and energy/information transfer time.
IEEE SYSTEMS JOURNAL
(2023)
Article
Engineering, Electrical & Electronic
Wenyu Zhang, Sherali Zeadally, Huan Zhou, Haijun Zhang, Ning Wang, Victor C. M. Leung
Summary: Edge computing is a widely-used approach for providing low-latency computation services. This study proposes a novel Logistic function-based model for estimating service reliability probability in edge computing scenarios with stochastic resource demands. An alternative optimization algorithm is proposed to solve the average service reliability maximization problem by jointly optimizing service quality ratios and resource allocations. Simulation results show that the proposed method achieves similar performance as a convex optimization algorithm, but with lower complexity, and improves service reliability compared to a baseline weighted allocation method.
IEEE TRANSACTIONS ON COMMUNICATIONS
(2023)
Article
Biochemical Research Methods
Yang-Han Wu, Yu-An Huang, Jian-Qiang Li, Zhu-Hong You, Peng-Wei Hu, Lun Hu, Victor C. M. Leung, Zhi-Hua Du
Summary: The interaction between transcription factors and target genes is a vital part of the human gene regulation network. However, many of these interactions have unconfirmed types. This research presents a graph-based prediction model called KGE-TGI, trained on a specially constructed knowledge graph, that relies on topology information rather than gene expression data. The proposed method achieved high AUC values in link prediction and link type classification tasks, outperforming existing methods and demonstrating the importance of incorporating knowledge information.
PLOS COMPUTATIONAL BIOLOGY
(2023)
Article
Computer Science, Information Systems
Fei Chen, Duming Luo, Jianqiang Li, Victor C. M. Leung, Shiqi Li, Junfeng Fan
Summary: With the increasing adoption of Internet of Things (IoT) applications, IoT security has become a critical issue. This study analyzes the security of an IoT security chip that has obtained Arm Platform Security Architecture (PSA) Level 2 certification and finds that it suffers from encryption key leakage.
TSINGHUA SCIENCE AND TECHNOLOGY
(2023)
Article
Computer Science, Information Systems
Xiuhua Li, Zhenghui Xu, Fang Fang, Qilin Fan, Xiaofei Wang, Victor C. M. Leung
Summary: In this paper, we investigate task offloading for DL-empowered ASA in mobile edge-cloud computing networks to minimize the total time for processing ASA tasks, thereby providing an agile service response. We propose a low-complexity and distributed offloading framework based on certain network constraints to solve the formulated complex problem. Evaluation results demonstrate the effectiveness of the proposed framework on reducing the total time and improving the satisfaction rate of users.
IEEE TRANSACTIONS ON CLOUD COMPUTING
(2023)
Article
Engineering, Electrical & Electronic
Yuhang Wang, Ying He, F. Richard Yu, Qiuzhen Lin, Victor C. M. Leung
Summary: With the rapid development of intelligent transportation systems, there is an increasing demand for low-latency and high-bandwidth vehicular services. This paper uses multiple UAVs as a supplement to ground networks to relieve communication pressure and models the scenario as a collaborative multi-agent system. The proposed method considers vehicle safety as a priority and uses multi-agent reinforcement learning and attention mechanism to optimize resource allocation.
IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS
(2023)
Article
Automation & Control Systems
Xunfeng Wu, Qiuzhen Lin, Jianqiang Li, Kay Chen Tan, Victor C. M. Leung
Summary: In this article, an ensemble surrogate-based coevolutionary optimizer is proposed to solve large-scale optimization problems. By training local surrogate models and using feature selection to construct a selective ensemble surrogate, the optimizer approximates the target problem. With two populations solving the target problem and a simplified auxiliary problem collaboratively, the coevolutionary optimizer can leverage the search experience from the auxiliary problem to help solve the target problem.
IEEE TRANSACTIONS ON CYBERNETICS
(2023)
Article
Computer Science, Information Systems
Jin Zhang, Yuyan Dai, Jie Chen, Chengwen Luo, Bo Wei, Victor C. M. Leung, Jianqiang Li
Summary: This paper proposes SIDA, a self-supervised imbalanced domain adaptation framework, for sound enhancement and WiFi sensing, which serves as a generic time series domain adaptation solution for IoT systems. SIDA enhances lung sounds and performs human sensing by separately learning the representation and mapping relations of time series signals in minority and majority domains. Experimental results demonstrate that SIDA achieves significant improvements on imbalanced datasets.
PROCEEDINGS OF THE ACM ON INTERACTIVE MOBILE WEARABLE AND UBIQUITOUS TECHNOLOGIES-IMWUT
(2023)
Article
Engineering, Electrical & Electronic
Adebola Olutayo, Yanjie Dong, Julian Cheng, Jonathan F. Holzman, Victor C. M. Leung
Summary: This study analyzes the performance of wireless powered wireless systems, where wireless devices scavenge energy from downlink sources and use it for communication in the uplink. Two new models are proposed to account for the nonlinear circuitry of energy harvesters and their functioning over multiple line-of-sight and non-line-of-sight channels. The Beaulieu-Xie fading model is introduced to characterize the diversity of these channels. Performance analyses demonstrate a good fit between the proposed models and measured data, with respect to average harvested energy and transmission outage probability.
IEEE OPEN JOURNAL OF THE COMMUNICATIONS SOCIETY
(2023)
Article
Engineering, Multidisciplinary
Ge Fan, Chaoyun Zhang, Junyang Chen, Paul Li, Yingjie Li, Victor C. M. Leung
Summary: Existing recommendation methods that train independent modules for each rating information may lead to sub-optimal results due to the lack of collaborative learning. We propose a collective model that can learn each sub-score simultaneously to predict users' overall rating, reducing the dependence on specific criterion and improving prediction quality. Experimental results show up to 13.14% lower prediction error compared to baseline approaches.
IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING
(2023)
Article
Engineering, Multidisciplinary
Chenyang Wang, Ruibin Li, Xiaofei Wang, Tarik Taleb, Song Guo, Yuxia Sun, Victor C. M. Leung
Summary: This paper proposes a neighborhood-aware caching (NAC) framework to improve the performance of edge caching systems in heterogeneous scenarios by leveraging perimeter information and attention mechanism.
IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING
(2023)
