Article
Computer Science, Information Systems
Kaveh Ahmadi, Mona Ghassemian, Massimo Condoluci, Mischa Dohler
Summary: This research proposes a signalling mechanism for next-generation communication systems, which improves communication efficiency through the decoupling of downlink and uplink connections, and demonstrates significant improvements in uplink performance.
Article
Engineering, Electrical & Electronic
Tingting Liu, Haibo Zhou, Jun Li, Feng Shu, Zhu Han
Summary: Thanks to the support of 5G/B5G technologies, introducing federated learning (FL) into vehicular networks can fulfill the increasing demands for artificial intelligence applications and address privacy concerns. However, due to intermittent connectivity and mobility, distributed clients (vehicles) often face challenges in terms of FL execution time and learning performance in a 5G/B5G vehicular network. To address this, client selection schemes in the uplink-downlink decoupled 5G/B5G networks are proposed to optimize parameters and enhance global learning performance. A low-complexity algorithm for client selection is suggested to improve energy efficiency. Numerical results demonstrate the effectiveness of the proposed method in guaranteeing FL execution time and meeting learning performance requirements while enhancing energy efficiency in the vehicular FL system.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2023)
Article
Computer Science, Information Systems
Bachir Lahad, Marc Ibrahim, Samer Lahoud, Kinda Khawam, Steven Martin
Summary: This article proposes dynamic time-division duplexing (TDD) and downlink and uplink decoupled access (DUDA) to address the highly variant traffic in downlink (DL) and uplink (UL) in heterogeneous networks (HetNets). A statistical model based on geometric probability approach is analytically investigated for multiple small cells deployment, considering different cell associations strategies in TDD and DUDA. The derived expressions for capacity and interference are used to measure decoupling gain and identify interferer small cell locations where decoupled mode maintains higher gain in both DL and UL. Monte-Carlo simulations validate the accuracy of the statistical model.
IEEE TRANSACTIONS ON MOBILE COMPUTING
(2021)
Article
Engineering, Electrical & Electronic
Sihui Zheng, Cong Shen, Xiang Chen
Summary: This paper focuses on the design and analysis of physical layer quantization and transmission methods for wireless federated learning. Through careful design of quantization and transmission methods, high accuracy can be achieved with minimal bandwidth consumption across different data set distributions, client participation levels, and quantization levels.
IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS
(2021)
Article
Computer Science, Information Systems
Faramarz Jabbarvaziri, Naveen Mysore Balasubramanya, Lutz Lampe
Summary: This article proposes uplink GF-NOMA transmission schemes using HARQ Type III to reduce packet drop rate. Two packet combining methods are considered, including chase combining and incremental redundancy combining. A GF single-transmission (GFST) scheme is introduced, where all redundancy versions of the packet are transmitted in one shot. The proposed methods are demonstrated to be superior to existing methods in mMTC scenarios through comprehensive evaluation of GF and conventional grant-based methods.
IEEE INTERNET OF THINGS JOURNAL
(2021)
Article
Automation & Control Systems
Zixiao Zhao, Qinghe Du, Houbing Song
Summary: In this article, a learning network is proposed to timely discover intrusion in the fifth generation network for Industrial internet of things (IoT), and can identify two types of intrusion. By extracting traffic load information from the states (success, collision, and idle) of access resources observed at media access control and physical layers, the learning network can effectively capture the number of active devices, provide reasonable prediction using history records, and achieve more accurate detection compared with baseline approaches.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2023)
Article
Engineering, Electrical & Electronic
Jie Zheng, Ling Gao, Haijun Zhang, Dusit Niyato, Jie Ren, Hai Wang, Hongbo Guo, Zheng Wang
Summary: Interference management and power transfer can significantly improve dense Internet of Things heterogeneous networks over 5G networks. The proposed approach in this paper optimizes interference aware UL/DL decoupling, airtime resource allocation, and energy transfer to achieve over 20% improvement in system utility compared to state-of-the-art solutions in dense IoT HetNets. The algorithm efficiently translates the complex optimization problem into a solvable space, maintaining user fairness and rate experience in a fast and scalable manner.
IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS
(2021)
Article
Engineering, Electrical & Electronic
Thomas Ketseoglou, Matthew C. Valenti, Ender Ayanoglu
Summary: The study focuses on analyzing and defining high-efficiency precoding groups in dense millimeter-wavelength cells, using multi-carrier analysis to model inter-group interference, achieving balanced throughput among different groups.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2021)
Article
Engineering, Electrical & Electronic
Xu Chen, Zhiyong Feng, Zhiqing Wei, J. Andrew Zhang, Xin Yuan, Ping Zhang
Summary: This paper proposes a Concurrent Downlink and Uplink (CDU) JCAS system that can use the echo of transmitted dedicated signals for sensing in the uplink while performing reliable uplink communication. A novel successive interference cancellation-based CDU JCAS processing method is proposed to estimate uplink communication symbols and downlink sensing parameters. Extensive simulation results verify the feasibility of the CDU JCAS system, showing a performance improvement of more than 10 dB compared to traditional JCAS methods while maintaining reliable uplink communication.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2023)
Article
Engineering, Electrical & Electronic
Praveen Pawar, Aditya Trivedi
Summary: The research proposes a JUDRA approach to maximize the throughput of 5G networks while ensuring quality of service. By utilizing the characteristics of sequential geometric programming, the resource allocation and power allocation problems are solved in two stages. The comparative results validate the effectiveness of the approach in reducing data traffic load and improving spectrum efficiency.
IEEE TRANSACTIONS ON COMMUNICATIONS
(2021)
Article
Engineering, Electrical & Electronic
Bin Lyu, Parisa Ramezani, Dinh Thai Hoang, Abbas Jamalipour
Summary: This paper discusses the integration of intelligent reflecting surface (IRS) technology into non-orthogonal multiple access (NOMA) wireless powered communication networks (WPCNs). The proposed NOMA-based scheme achieves a considerable performance gain in uplink sum-rate while meeting the minimum rate requirement.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2022)
Article
Engineering, Electrical & Electronic
Praneeth re Susarla, Bikshapathi Gouda, Yansha Deng, Markku Juntti, Olli Silven, Antti Tolli
Summary: This paper proposes a deep Q-Network based framework for uplink UAV-BS beam alignment, which utilizes location information to maximize beamforming gain. Experimental results show that the proposed framework converges faster and performs similarly to the traditional exhaustive approach in real-time conditions.
IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS
(2023)
Article
Computer Science, Artificial Intelligence
Xingcai Zhou, Le Chang, Jinde Cao
Summary: This article proposes two communication-efficient nonconvex federated learning algorithms that reduce communication costs by adapting uplink and downlink communications. Numerical experiments demonstrate the significant advantage of these algorithms in communication.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2023)
Article
Computer Science, Hardware & Architecture
Yinghui Zhang, Robert H. Deng, Elisa Bertino, Dong Zheng
Summary: The evolving 5G cellular networks require security and efficiency for frequent handovers, and the RUSH protocol proposed in this paper addresses existing authentication challenges while achieving universality and robustness. RUSH utilizes chameleon hash functions and blockchains to enable anonymous mutual authentication with key agreement, and it has been proven to resist various attacks while outperforming other schemes in both computation and communication efficiency.
IEEE TRANSACTIONS ON DEPENDABLE AND SECURE COMPUTING
(2021)
Article
Computer Science, Information Systems
Engin Eyceyurt, Yunus Egi, Josko Zec
Summary: The prediction of uplink throughput is crucial for cellular networks, requiring consideration of the environment and LTE parameters to improve the accuracy of machine learning algorithms.