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IEEE Internet of Things Journal Publication Information IEEE Internet Things J. (IF 8.2) Pub Date : 2024-08-22
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FedSAP: Secure Federated Learning in SDN-IoT via DRL-Enabled Social Attribute Perception IEEE Internet Things J. (IF 8.2) Pub Date : 2024-08-22 Jiushuang Wang, Ying Liu, Weiting Zhang, Chenhao Ying, Jiawen Kang, Yikun Li
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IEEE Internet of Things Journal Information for Authors IEEE Internet Things J. (IF 8.2) Pub Date : 2024-08-22
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IEEE Internet of Things Journal Society Information IEEE Internet Things J. (IF 8.2) Pub Date : 2024-08-22
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Sparse Attention-Driven Quality Prediction for Production Process Optimization in Digital Twins IEEE Internet Things J. (IF 8.2) Pub Date : 2024-08-22 Yanlei Yin, Lihua Wang, Dinh Thai Hoang, Wenbo Wang, Dusit Niyato
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Attack Detection Using Artificial Intelligence Methods for SCADA Security IEEE Internet Things J. (IF 8.2) Pub Date : 2024-08-22 Nesibe Yalçın, Semih Çakır, Sibel Üaldı
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GNN-Empowered Effective Partial Observation MARL Method for AoI Management in Multi-UAV Network IEEE Internet Things J. (IF 8.2) Pub Date : 2024-08-22 Yuhao Pan, Xiucheng Wang, Zhiyao Xu, Nan Cheng, Wenchao Xu, Jun-jie Zhang
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Quantum Secure Authentication Scheme for Internet of Medical Things Using Blockchain IEEE Internet Things J. (IF 8.2) Pub Date : 2024-08-22 Sunil Prajapat, Pankaj Kumar, Dheeraj Kumar, Ashok Kumar Das, M. Shamim Hossain, Joel J. P. C. Rodrigues
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Digital Twin-Empowered Resource Allocation for On-Demand Collaborative Sensing IEEE Internet Things J. (IF 8.2) Pub Date : 2024-08-22 Mushu Li, Jie Gao, Conghao Zhou, Lian Zhao, Xuemin Shen
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Research on an M-ary Frequency Shift Keying With Index Modulation System for Underwater Acoustic Communication IEEE Internet Things J. (IF 8.2) Pub Date : 2024-08-22 Xiaoyu Yang, Yuehai Zhou, Junhui Yao, Feng Tong
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Guest Editorial Special Issue on Next-Generation Multiple Access for Internet of Things IEEE Internet Things J. (IF 8.2) Pub Date : 2024-08-22 Tianwei Hou, Xidong Mu, Zhiguo Ding, Octavia A. Dobre, Naofal Al-Dhahir
The rapid development of next-generation Internet of Things (IoT) applications, including integrated-sensing-and-communication (ISAC), smart grids, smart cities, intelligent transport networks, etc., enables at least tens of billions of bandwidth-thirsty IoT devices, which consume a deluge of data in the sixth-generation (6G) communication systems. In addition, future challenging heterogeneous services
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Enhanced Index-Modulation-Aided Nonorthogonal Multiple Access via Superposition Coding Rotation IEEE Internet Things J. (IF 8.2) Pub Date : 2024-08-22 Ronglan Huang, Fei Ji, Zeng Hu, Dehuan Wan, Pengcheng Xu, Yun Liu
Nonorthogonal multiple access (NOMA) has been widely recognized as a promising spectral efficiency technique for the next generation of wireless communication networks due to its ability to support multiple users in the same orthogonal resource block. In response to the increasing demands for extensive connectivity and high-volume data transmission, a novel index modulation (IM)-aided NOMA scheme has
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Augmented Multi-Agent DRL for Multi-Incentive Task Prioritization in Vehicular Crowdsensing IEEE Internet Things J. (IF 8.2) Pub Date : 2024-08-21 Piyush Singh, Bishmita Hazarika, Keshav Singh, Wan-Jen Huang, Chih-Peng Li
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Variable Granularity Vehicle Digital Twin Construction Scheme for DT-Assisted IoVs IEEE Internet Things J. (IF 8.2) Pub Date : 2024-08-21 Lun Tang, Zhoulin Pu, Zhangchao Cheng, Dongxu Fang, Qianbin Chen
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Empowering C-V2X Through Advanced Joint Traffic Prediction in Urban Networks IEEE Internet Things J. (IF 8.2) Pub Date : 2024-08-21 Chaojin Mao, Liang Zhao, Zhi Liu, Geyong Min, Ammar Hawbani, Keping Yu
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A Comprehensive Review on Internet of Things Applications in Power Systems IEEE Internet Things J. (IF 8.2) Pub Date : 2024-08-21 Abhilash Asit Kumar Majhi, Sanjeeb Mohanty
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Ethical Alignment Decision-Making for Connected Autonomous Vehicle in Traffic Dilemmas via Reinforcement Learning From Human Feedback IEEE Internet Things J. (IF 8.2) Pub Date : 2024-08-21 Xin Gao, Tian Luan, Xueyuan Li, Qi Liu, Zhaoyang Ma, Xiaoqiang Meng, Zirui Li
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Securing Smart Grid False Data Detectors Against White-box Evasion Attacks Without Sacrificing Accuracy IEEE Internet Things J. (IF 8.2) Pub Date : 2024-08-21 Islam Elgarhy, Mahmoud M. Badr, Mohamed Mahmoud, Mahmoud Nabil, Maazen Alsabaan, Mohamed I. Ibrahem
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Joint Task Allocation and Computation Offloading in Mobile Edge Computing With Energy Harvesting IEEE Internet Things J. (IF 8.2) Pub Date : 2024-08-21 Li Yin, Songtao Guo, Qiucen Jiang
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STAR-RIS Aided Integrated Sensing, Computing, and Communication for Internet of Robotic Things IEEE Internet Things J. (IF 8.2) Pub Date : 2024-08-21 Haochen Li, Xidong Mu, Yuanwei Liu, Yue Chen, Pan Zhiwen
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Deep Koopman Predictors for Anomaly Detection of Complex IOT Systems With Time Series Data IEEE Internet Things J. (IF 8.2) Pub Date : 2024-08-21 Liu Fu, Meng Ma, Zhi Zhai
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TimeSense: Multi-Person Device-Free Indoor Localization via RTT IEEE Internet Things J. (IF 8.2) Pub Date : 2024-08-21 Mohamed Mohsen, Hamada Rizk, Hirozumi Yamaguchi, Moustafa Youssef
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Multi-Frequency Wireless Channel Measurements and Characterization in Indoor Industrial Scenario IEEE Internet Things J. (IF 8.2) Pub Date : 2024-08-21 Yang Wang, Chenxu Wang, Xiangquan Zheng, Xinyu Hao, Xi Liao
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Supporting Ultra-Low-Power Nodes in 6TiSCH Industrial Wireless Sensor Networks IEEE Internet Things J. (IF 8.2) Pub Date : 2024-08-21 Dries Van Leemput, Jeroen Hoebeke, Eli De Poorter
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A Walkthrough of Blockchain-Based Internet of Drones Architectures IEEE Internet Things J. (IF 8.2) Pub Date : 2024-08-21 Ayushi Jain, Shivam Barke, Mehak Garg, Anvita Gupta, Bhawna Narwal, Amar Kumar Mohapatra, Deepak Kumar Sharma, Gautam Srivastava
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On Phishing URLs Detection Using Feature Extension IEEE Internet Things J. (IF 8.2) Pub Date : 2024-08-21 Daojing He, Zhihua Liu, Xin Lv, Sammy Chan, Mohsen Guizani
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Cooperative Multi-Agent Deep Reinforcement Learning Methods for UAV-Aided Mobile Edge Computing Networks IEEE Internet Things J. (IF 8.2) Pub Date : 2024-08-21 Mintae Kim, Hoon Lee, Sangwon Hwang, Mérouane Debbah, Inkyu Lee
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Distributed Deep Reinforcement Learning Based Gradient Quantization for Federated Learning Enabled Vehicle Edge Computing IEEE Internet Things J. (IF 8.2) Pub Date : 2024-08-21 Cui Zhang, Wenjun Zhang, Qiong Wu, Pingyi Fan, Qiang Fan, Jiangzhou Wang, Khaled B. Letaief
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A 11.2 pJ/bit Reconfigurable Dynamic Chaotic Encryption ASIC for IoT IEEE Internet Things J. (IF 8.2) Pub Date : 2024-08-21 Jundong Feng, Jia Ai, Fangjie Li, Junchao Wang
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Reinforcement Learning-Based Multi-Lane Cooperative Control for On-Ramp Merging in Mixed-Autonomy Traffic IEEE Internet Things J. (IF 8.2) Pub Date : 2024-08-21 Lin Liu, Xiaoxuan Li, Yongfu Li, Jingxiang Li, Zhongyang Liu
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IoT-Driven Deep Learning for Enhanced Industrial Production Forecasting IEEE Internet Things J. (IF 8.2) Pub Date : 2024-08-21 Gabriel Augusto David, Paulo Monteiro de Carvalho Monson, Cristiano Soares, Pedro de Oliveira Conceição, Paulo Roberto de Aguiar, Alessandro Simeone
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A Case for Ultra-Wideband Concurrent Transmissions in Wireless Control IEEE Internet Things J. (IF 8.2) Pub Date : 2024-08-21 Matteo Trobinger, Gian Pietro Picco
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AEFL: Anonymous and Efficient Federated Learning in Vehicle Road Cooperation Systems With Augmented Intelligence of Things IEEE Internet Things J. (IF 8.2) Pub Date : 2024-08-20 Xiaoding Wang, Jiadong Li, Hui Lin, Cheng Dai, Sahil Garg, Georges Kaddoum
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Lightweight Deep Learning for Missing Data Imputation in Wastewater Treatment With Variational Residual Auto-Encoder IEEE Internet Things J. (IF 8.2) Pub Date : 2024-08-20 Wen Zhang, Rui Li, Pei Quan, Jiang Chang, Yongsheng Bai, Bojun Su
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ADS-Bpois: Poisoning Attacks against Deep Learning-Based Air Traffic ADS-B Unsupervised Anomaly Detection Models IEEE Internet Things J. (IF 8.2) Pub Date : 2024-08-20 Peng Luo, Buhong Wang, Jiwei Tian, Yong Yang
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Cost-Effective Dynamic Alliance Pricing Mechanism Based on Distributed Edge-Intelligence IEEE Internet Things J. (IF 8.2) Pub Date : 2024-08-19 Zhihan Cao, Xi Zheng, Jianxiong Guo, Weijia Jia, Youke Wu, Tian Wang
In beyond 5G (B5G) Internet-of-Thing (IoT) system based on edge intelligence, pay-for-use demand has become a consensus, and the pricing of IoT services has attracted the attention of academia and industry. The pricing method based on non-cooperative game allows edge service providers to compete fairly, effectively preventing edge nodes from malicious bidding. However, since only one winner can make
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Provably Secure Anti-Phishing Scheme for Medical Information in Smart Healthcare IEEE Internet Things J. (IF 8.2) Pub Date : 2024-08-19 Shuangshuang Liu, Zhi Wang, Saru Kumari, Jianhui Lv, Chien-Ming Chen
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eNut: A Sensing System to Measure the Acquisition of Foraging Proficiency in Wild Tree Squirrels IEEE Internet Things J. (IF 8.2) Pub Date : 2024-08-19 Mihir S. Chauhan, Avikam Chauhan, Myriam Bayen, Fangyu Wu, Fahd A. Althukair, Michael T. Kaiser, Lucia F. Jacobs
We present a three-part sensing system to measure the acquisition of foraging proficiency in wild tree squirrels. The first component is the eNut: a 3Dprinted enclosure in the size and shape of a large food item, such as a walnut. The eNut contains an inertial measurement unit (IMU), consisting of an accelerometer and a gyroscope, along with a capsule containing a food reward (e.g. chopped nuts), motivating
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TEMP:Cost-Aware Two-Stage Energy Management for Electrical Vehicles Empowered by Blockchain IEEE Internet Things J. (IF 8.2) Pub Date : 2024-08-19 Ting Cai, Xiang Li, Yifei Wang, You Zhang, Zhiwei Ye, Qiyi He, Xiaoli Li, Yuquan Zhang, Patrick C. K. Hung
Developing effective platforms for economic energy management is considered a pivotal issue in the field of Electric Vehicles (EVs). To implement a cost-effective Energy Management Platform (EMP), developers must overcome two major challenges. The first challenge lies in the environmental dynamic nature such as EV location, energy price fluctuations, storage levels, and parking availability at charging
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Verifiable Strong Privacy-Preserving Any-hop Reachability Query on Blockchain-Assisted Cloud IEEE Internet Things J. (IF 8.2) Pub Date : 2024-08-19 Jingjuan Yu, Yuwei Duan, Ping Luo, Shundong Li
Any-hop (k-hop) reachability query is one fundamental operation in graph data analysis and its performance affects the efficiency of various tasks in social Internet of Things. As graph data scale increases, data is often outsourced to cloud servers. To protect the privacy of graph data, it is necessary to encrypt the data before outsourcing. Existing schemes can only support privacy-preserving 2-hop
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Dynamic Energy-Efficient Computation Offloading in NOMA-Enabled Air-Ground Integrated Edge Computing IEEE Internet Things J. (IF 8.2) Pub Date : 2024-08-19 Heng Li, Ying Chen, Kaixin Li, Yaozong Yang, Jiwei Huang
With the swift progress of Internet of Things (IoT) technologies, the number of IoT devices has grown exponentially, leading to an increasing demand for computational power and system stability. Mobile Edge Computing (MEC) is a powerful solution that allows IoT devices to offload data to the edge for computing. In situations involving disasters or complex terrains, establishing ground-based stations
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Physics-Enhanced Graph Neural Networks For Soft Sensing in Industrial Internet of Things IEEE Internet Things J. (IF 8.2) Pub Date : 2024-08-19 Keivan Faghih Niresi, Hugo Bissig, Henri Baumann, Olga Fink
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Localization of False Data Injection Attacks in Smart Grids With Renewable Energy Integration via Spatiotemporal Network IEEE Internet Things J. (IF 8.2) Pub Date : 2024-08-19 Yang Yu, Chensheng Liu, Luolin Xiong, Yang Tang, Feng Qian
The precise localization of False Data Injection Attacks (FDIA) is vital to ensure the stable operation of smart grids. However, the intermittency and uncertainty of renewable energy can lead to confusion with unknown FDIA. As a result, previous works encountered difficulties in extracting distinguishable spatiotemporal features to construct accurate behavior models, thereby affecting the effectiveness
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Enabling Efficient Vehicle-Road Cooperation through AIoT: A Deep Learning Approach to Computational Offloading IEEE Internet Things J. (IF 8.2) Pub Date : 2024-08-19 Xin Wang, Madini O. Alassafi, Fawaz E. Alsaadi, Xingsi Xue, Longhao Zou, Zhonghua Liu
The integration of Artificial Intelligence with the Internet of Things (AIoT) significantly enhances the functionality of Vehicle-Road Cooperation (VRC) systems by enabling smarter, real-time decision-making and resource optimization across interconnected vehicular networks. To tackle the challenges associated with resource constraints, this study introduces a method where vehicle users can offload
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Efficient Motion Control for Heterogeneous Autonomous Vehicle Platoon Using Multilayer Predictive Control Framework IEEE Internet Things J. (IF 8.2) Pub Date : 2024-08-19 Guodong Du, Yuan Zou, Xudong Zhang, Jie Fan, Wenjing Sun, Zirui Li
Autonomous driving technology and platooning driving technology are important directions for the development of intelligent and connected vehicles. Aiming at the motion control problem of autonomous vehicle platoon, this paper proposes a multilayer predictive control framework (MPCF) based on heuristic learning agent and improved distributed model. Firstly, the leading autonomous vehicle and following
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DT-LNS: Digital Twin-Based Low-Risk Network Slicing Using Safe Reinforcement Learning IEEE Internet Things J. (IF 8.2) Pub Date : 2024-08-19 Jin Li, Min Zhang, Qi Zhang, Danshi Wang
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Generalized High-Precision and Wide-Angle DOA Estimation Method Based on Space-Time-Coding Digital Metasurfaces IEEE Internet Things J. (IF 8.2) Pub Date : 2024-08-19 Qun Yan Zhou, Jun Yan Dai, Zuqi Fang, Lijie Wu, Zhen Jie Qi, Si Ran Wang, Rui Zhe Jiang, Qiang Cheng, Tie Jun Cui
Direction of arrival (DOA) estimation is essential in building the wireless electromagnetic (EM) environment. However, the conventional DOA estimation methods have been criticized for their hardware complexity, high cost, and low energy efficiency. Recently, metasurface-based methods have emerged as promising alternatives that offer cost-effective solutions. Nevertheless, the existing studies have
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Prob-CS: A Probabilistic Cuckoo Sketch for Accurate Network Traffic Measurement IEEE Internet Things J. (IF 8.2) Pub Date : 2024-08-19 Chao Wang, Xu Li, Jiuzhen Zeng, Weimin Yin, Ping Zhou
For Internet of Things (IoT) networks and devices, the network traffic measurement owns security significance. It usually focuses on the frequency estimation and top-k flows detection, two basic measurement tasks where the sketch has been widely used as the outline data structure. Existing measurement schemes make tradeoffs between efficiency, accuracy and speed. Some of them, such as the recently
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Unsourced Multiple Access for Mission-Critical Control Systems in Industrial Internet of Things IEEE Internet Things J. (IF 8.2) Pub Date : 2024-08-08 Jingze Che, Zhaoyang Zhang, Yuqing Tian, Zhaohui Yang, Ming Liu, Zhiji Deng, Xiaoming Chen
In mission-critical Industrial Internet of Things (IIoT), multiple sensors make independent observations at different locations and then transmit them to the base station (BS) to obtain a global system state vector. Uploading observation information to the BS by active sensors is a multiple access process. As the task is to complete state estimation instead of maximizing the physical-layer capacity
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Performance Analysis of NOMA-Based VLC System in Different IoT Network Environments IEEE Internet Things J. (IF 8.2) Pub Date : 2024-07-22 Lisu Yu, Xinxin Lv, Mingli Zhang, Chaoliang Liu, Yuhao Wang, Zhenghai Wang
This article analyses the performance of a power-domain nonorthogonal multiple access (PD-NOMA)-based visible light communication (VLC) system in the Internet of Things (IoT) network. It specifically investigates the various VLC system channel models in indoor and outdoor IoT network settings. To enhance the existing analysis of the PD-NOMA-based VLC system performance, this study first analyses the
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Access Point Cooperation Strategies for Coded Random Access in Cell-Free Massive MIMO IEEE Internet Things J. (IF 8.2) Pub Date : 2024-07-15 Enrico Testi, Velio Tralli, Enrico Paolini
In this article, grant-free uplink communication from a large number of machine-type devices in cell-free massive MIMO networks is explored. A novel approach that leverages coded random access (CRA), on the device side, with combining of signals received at properly selected access points (APs) and cooperative successive interference cancelation (SIC), on the network side, is presented. Initially,
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Securing Federated Diffusion Model With Dynamic Quantization for Generative AI Services in Multiple-Access Artificial Intelligence of Things IEEE Internet Things J. (IF 8.2) Pub Date : 2024-07-11 Jiayi He, Bingkun Lai, Jiawen Kang, Hongyang Du, Jiangtian Nie, Tao Zhang, Yanli Yuan, Weiting Zhang, Dusit Niyato, Abbas Jamalipour
Generative diffusion models (GDMs) have emerged as potent tools for generating high-quality, creative content across various media, including audio, images, videos, and 3-D models. Their application in artificial intelligence-generated content (AIGC) marks a pivotal advancement in the evolution from the Internet of Things (IoT) to the Artificial Intelligence of Things (AIoT). Considering the inherent
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Joint Optimization of User Scheduling, Rate Allocation, and Beamforming for RSMA Finite Blocklength Transmission IEEE Internet Things J. (IF 8.2) Pub Date : 2024-07-09 Jianyue Zhu, Haijia Jin, Yutong He, Fang Fang, Wei Huang, Zhizhong Zhang
The forthcoming wireless network promises revolutionary advancements with significantly higher peak data rates, reduced latency, and vastly improved reliability. Among pivotal technologies, the design of novel multiple access schemes, particularly rate-splitting multiple access (RSMA), holds significant importance. In this article, we focus on the joint optimization of user scheduling, rate allocation
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Active Detection and Channel Estimation Schemes for Massive Random Access in User-Centric Cell-Free Massive MIMO System IEEE Internet Things J. (IF 8.2) Pub Date : 2024-07-04 Yanfeng Hu, Qingtian Wang, Dongming Wang, Xinjiang Xia, Xiaohu You
The demand for higher transmission efficiency and denser user access has been put forth by the next generation of wireless communication systems. To cater to the future communication development, this article focuses on massive random access schemes under the user-centric cell-free massive multiple-input-multiple-output (MIMO) architecture. For uplink transmission, a data frame structure is designed
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Performance Analysis of HARQ-Enabled IRS-NOMA Downlink Systems IEEE Internet Things J. (IF 8.2) Pub Date : 2024-06-27 Bin Dai, Xinwei Yue, Zhen Mei, Francis C. M. Lau, Yulong Zou, Tian Li
In this article, we explore the application of hybrid automatic repeat request (HARQ) within the intelligent reflection surface-assisted nonorthogonal multiple access (IRS-NOMA) system. We investigate the closed-form expressions for the outage probability of multiple users in the HARQ-assisted IRS-NOMA system, considering scenarios with perfect successive interference cancellation (pSIC) and imperfect
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Nonorthogonal Multiple Access With Guessing Random Additive Noise Decoding-Aided Macrosymbol (GRAND-AM) IEEE Internet Things J. (IF 8.2) Pub Date : 2024-06-24 Kathleen Yang, Muriel Médard, Ken R. Duffy
We propose guessing random additive noise decoding-aided macrosymbols (GRAND-AMs) as a nonorthogonal multiple access (NOMA) method that can detect, error correct, and decode multiple users with imperfect channel estimation, asynchronous transmission, and interference, which are all topics of concern for Internet of Things. GRAND-AM is a NOMA method that uses both joint multiuser detection and joint
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Near-Field Communications for DMA-NOMA Networks IEEE Internet Things J. (IF 8.2) Pub Date : 2024-06-21 Zheng Zhang, Yuanwei Liu, Zhaolin Wang, Jian Chen, Dong In Kim
A novel near-field transmission framework is proposed for dynamic metasurface antenna (DMA)-enabled nonorthogonal multiple access (NOMA) networks. The base station (BS) exploits the hybrid beamforming to communicate with multiple near users (NUs) and far users (FUs) using the NOMA principle. Based on this framework, two novel beamforming schemes are proposed. 1) For the case of the grouped users distributed
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Performance Analysis of NOMA-Enabled Active RIS-Aided MIMO Heterogeneous IoT Networks With Integrated Sensing and Communication IEEE Internet Things J. (IF 8.2) Pub Date : 2024-06-19 Abhinav Singh Parihar, Keshav Singh, Vimal Bhatia, Chih-Peng Li, Trung Q. Duong
With the imminent arrival of 6G communication, the relevance of advanced technologies, such as multi-input-multioutput (MIMO), nonorthogonal multiple access (NOMA), reconfigurable intelligent surfaces (RISs), and integrated sensing and communication (ISAC), has become prominent for plethora of Internet of Things (IoT) applications. However, integrating ISAC into a MIMO heterogeneous network (HetNets)