Article
Engineering, Electrical & Electronic
Bushra Rashid, Ayaz Ahmad, Sher Ali, Zeeshan Kaleem, Ahmed Alkhayyat, Chau Yuen
Summary: In this paper, the authors investigate energy efficient resource allocation for uplink multi-carrier non orthogonal multiple access (MC-NOMA) based two-tier heterogeneous networks (HetNets) with wireless backhaul. They formulate a joint NU clustering, power, and subchannel allocation problem for system's energy efficiency maximization. The proposed approach exploits channel diversity and guarantees user fairness.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2023)
Article
Computer Science, Information Systems
Hosein Azarhava, Javad Musevi Niya, Mohammad Ali Tinati
Summary: This paper investigates the resource allocation problem in a NOMA-based Wireless Energy Harvesting Sensor Network (WEHSN) to improve energy efficiency and system throughput. By converting the problem to a parametric form and applying the KKT conditions, a closed-form expression for optimization is derived. Numerical results show that the NOMA-based WEHSN outperforms the OFDMA and TDMA-based methods in terms of energy efficiency and throughput.
COMPUTER COMMUNICATIONS
(2023)
Article
Computer Science, Information Systems
Haixia Cui, Xianwan Ye, Fan You
Summary: This paper introduces an energy-efficient resource allocation algorithm for heterogeneous SWIPT-NOMA systems, considering the minimum rate requirements of users, energy harvesting, and transmission power of heterogeneous radio access technologies, and utilizing Dinkelbach and Lagrangian Duality theory to maximize energy efficiency performance jointly with power and time scheduling management.
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
Telecommunications
Hao Xie, Yongjun Xu
Summary: This paper investigates a robust resource allocation problem in NOMA-assisted HetNets, aiming to maximize the total energy efficiency of SCUs under imperfect channel state information. By considering bounded channel uncertainties, the problem is formulated as a mixed-integer and nonlinear programming problem, which is then transformed into an equivalent convex optimization problem using Dinkelbach's method. A robust Dinkelbach-based algorithm is proposed to jointly optimize the transmit power and the RB allocation. Simulation results demonstrate that the proposed algorithm outperforms existing algorithms in terms of energy efficiency and robustness.
DIGITAL COMMUNICATIONS AND NETWORKS
(2022)
Article
Engineering, Electrical & Electronic
Weixin Yin, Lei Xu, Huijun Wang, Yuwang Yang, Yulin Wang, Tianyou Chai
Summary: The study proposes a resource allocation and assignment algorithm for video traffic to improve efficiency and video transmission quality in heterogeneous NOMA networks. The problem is solved through two subproblems, addressing resource allocation and assignment in a structured approach.
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY
(2021)
Article
Computer Science, Hardware & Architecture
Indranil Sarkar, Sanjay Kumar
Summary: In the era of IoT, computational offloading has become crucial for delay-sensitive task completion and data processing. This paper proposes a deep-learning-based binary offloading strategy to optimize offloading decisions and bandwidth allocation, achieving near-optimal performance in terms of reducing overall delay and energy consumption.
JOURNAL OF SUPERCOMPUTING
(2022)
Article
Computer Science, Information Systems
Amin Mohajer, Mahya Sam Daliri, A. Mirzaei, A. Ziaeddini, M. Nabipour, Maryam Bavaghar
Summary: Mobile Edge Computing is a viable solution for addressing the increasing demand for broadband services in new-generation heterogeneous systems. The dense deployment of small cell networks is a key feature of next-generation radio access networks, but it can lead to increased operational costs and carbon emissions. Energy efficiency and fairness assurance are critical issues in MEC-based cellular systems, especially considering the resource and computational limitations of the user layer.
IEEE TRANSACTIONS ON SERVICES COMPUTING
(2023)
Article
Computer Science, Information Systems
Liqing Shan, Songtao Gao, Shuaishuai Chen, Mingkai Xu, Fenghui Zhang, Xuecai Bao, Ming Chen
Summary: This paper studies the energy-efficient resource allocation problem in cellular D2D-aided V2X networks with NOMA. By jointly optimizing power allocation and spectrum reusing, the minimum energy efficiency of each link is maximized to meet QoS requirements and consider maximum performance from the user's perspective.
COMPUTER COMMUNICATIONS
(2023)
Article
Computer Science, Information Systems
Rui Tang, Ruizhi Zhang, Yongjun Xu, Jinpu He
Summary: This study focuses on the energy-efficient optimization problem in a non-orthogonal multiple access (NOMA)-based unmanned aerial vehicle (UAV)-assisted data collection system for traffic offloading. An alternating-based offline optimization algorithm is proposed to obtain the optimal online UAV trajectory policy, and the deep deterministic policy gradient algorithm is used to approach the optimal UAV placement. Simulation results show that the proposed algorithm can achieve efficient performance with an average online operation time of fewer than 0.2 seconds.
IEEE WIRELESS COMMUNICATIONS LETTERS
(2023)
Article
Engineering, Electrical & Electronic
Zechen Liu, Xin Liu, Victor C. M. Leung, Tariq S. Durrani
Summary: In this paper, a dual-UAV-assisted IoT using non-orthogonal multiple access (NOMA) is proposed to improve IoT capacity. By optimizing communication scheduling, UAV transmit power and UAV motion parameters, energy consumption of the UAVs can be reduced while ensuring a certain throughput. The numerical results show that optimizing UAV motion parameters can effectively improve energy efficiency of UAVs, and the proposed dual-NOMA-UAV assisted IoT achieves higher energy efficiency than the OMA-UAV assisted IoT.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2023)
Article
Engineering, Electrical & Electronic
Handan Zheng, Li Li
Summary: This paper investigates energy efficient resource allocation in HetNets by imposing different kinds of backhaul capacity constraints on small cells, aiming at improving network energy efficiency and relieving backhaul data volume traffic pressure. Through concave-convex fractional programming and convex optimization theory, the proposed algorithms have good convergence performance and evaluate the impact of backhaul capacity constraints on network performance.
INTERNATIONAL JOURNAL OF COMMUNICATION SYSTEMS
(2022)
Article
Computer Science, Information Systems
Donghyeon Kim, Sean Kwon, Haejoon Jung, In-Ho Lee
Summary: In this paper, resource allocation algorithms for subchannels and transmit powers are proposed to improve the sum rate performance of downlink power-domain non-orthogonal multiple access (NOMA) in heterogeneous networks (HetNets), while satisfying a minimum data-rate requirement. The proposed subchannel allocation scheme achieves NOMA gain without the constraint of the number of NOMA users on each subchannel, and the power allocation scheme is based on deep neural network (DNN) and unsupervised learning. Simulation results show that the proposed schemes outperform conventional methods in terms of sum rates.
Article
Engineering, Electrical & Electronic
Alemu Jorgi Muhammed, Hongyang Chen, Abegaz Muhammed Seid, Zhu Han, Quan Yu
Summary: The integration of millimeter-wave (mmWave) and non-orthogonal multiple access (NOMA) has attracted attention due to their massive bandwidth support and higher spectral efficiency. This paper proposes a user grouping algorithm to simplify the process of user clustering and suppress inter-cluster interference. It also presents a hybrid analog/digital precoding scheme to maximize energy-efficiency in NOMA HetNet. The formulation of an optimization problem and the development of distributed power allocation algorithms are introduced to optimize resource allocation.
IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS
(2023)
Article
Chemistry, Analytical
Zhengjia Xu, Ivan Petrunin, Teng Li, Antonios Tsourdos
Summary: This paper proposes three heuristic solutions, namely stochastic algorithm, GRASP, and SSD, to achieve dynamic power and channel allocation for users in the downlink multi-channel non-orthogonal multiple access systems. Multiple constraints are considered based on practical scenarios, and the effectiveness and performance of the algorithms are compared through demonstration and simulation.
Article
Computer Science, Theory & Methods
Nilesh Chakraborty, Jianqiang Li, Victor C. M. Leung, Samrat Mondal, Yi Pan, Chengwen Luo, Mithun Mukherjee
Summary: This paper presents a comprehensive survey of honeyword-based authentication techniques, covering twenty-three techniques reported since 2013. The paper aims to help readers understand the practical workings of honeyword-based security mechanisms, compare existing techniques, and identify gaps and research opportunities.
ACM COMPUTING SURVEYS
(2023)
Article
Computer Science, Information Systems
Feijie Wu, Ho Yin Yuen, Henry Chan, Victor C. M. Leung, Wei Cai
Summary: Applying P2P architecture to online video games has attracted attention due to its cost-saving benefits. However, issues with distributed data storage and cheating prevention have hindered its adoption. Inspired by blockchain techniques, we propose PoP, a decentralized data storage system with an anti-cheating mechanism for P2P games. Our game-theory model and experiments demonstrate the effectiveness of PoP compared to PoW.
ACM TRANSACTIONS ON INTERNET TECHNOLOGY
(2023)
Article
Computer Science, Information Systems
Xingyu Feng, Chengwen Luo, Jiongzhang Chen, Yijing Huang, Jin Zhang, Weitao Xu, Jianqiang Li, Victor C. M. Leung
Summary: This article proposes a distributed learning framework called IoTSL for efficient cloud-edge collaboration in IoT systems. By using generative adversarial networks and differential privacy techniques, IoTSL trains local data-based generators on devices with privacy protection, reduces communication costs and alleviates the catastrophic forgetting phenomenon. Experimental results show that compared to conventional SL, IoTSL significantly reduces communication costs and efficiently alleviates the forgetting phenomenon.
IEEE INTERNET OF THINGS JOURNAL
(2023)
Article
Automation & Control Systems
Xunfeng Wu, Qiuzhen Lin, Wu Lin, Yulong Ye, Qingling Zhu, Victor C. M. Leung
Summary: Dynamic multimodal optimization problems (DMMOPs) require searching multiple global optimal solutions with changing objectives and constraints over time. However, DMMOPs have not received enough attention and limited studies have been done in this area. This paper proposes a Kriging Model-based Evolutionary Algorithm with Support Vector Machine (KMEA-SVM) to tackle DMMOPs by addressing the challenges induced by both multimodality and dynamics. Experimental results on twenty-four test DMMOPs demonstrate that KMEA-SVM outperforms several state-of-the-art evolutionary algorithms in seeking multiple optima in dynamic environments.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2023)
Article
Engineering, Civil
Ying Ju, Yuchao Chen, Zhiwei Cao, Lei Liu, Qingqi Pei, Ming Xiao, Kaoru Ota, Mianxiong Dong, Victor C. M. Leung
Summary: This paper proposes a deep reinforcement learning based joint secure offloading and resource allocation scheme to improve the secrecy performance and resource efficiency of multi-user vehicular edge computing networks.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2023)
Article
Computer Science, Information Systems
Haneul Ko, Jaewook Lee, Sangwon Seo, Sangheon Pack, Victor C. M. Leung
Summary: In federated learning, low computing power, poor wireless channel conditions, and insufficient data can result in a long convergence time. To address this, a constrained Markov decision process (CMDP) problem is formulated to minimize the average round time while maintaining minimum numbers of trained data and trained data classes. The CMDP problem is converted into a linear programming (LP) to obtain the optimal scheduling policy. Additionally, a joint client selection and bandwidth allocation algorithm (JCSBA) is developed to reduce the curse of dimensionality in CMDP and effectively reduce the convergence time by up to 49%.
IEEE TRANSACTIONS ON MOBILE COMPUTING
(2023)
Article
Engineering, Electrical & Electronic
Hui Ma, Haijun Zhang, Wenyu Zhang, Victor C. M. Leung
Summary: This article investigates the use of reconfigurable intelligent surface (RIS) as a promising technology for 6G networks. The study focuses on a power splitting aided broadcasting network where one access point (AP) transmits identical messages to multiple users. By controlling reflect amplitude coefficients, the RIS is able to assist the AP while achieving power self-sustainability through energy harvesting. An algorithm based on block coordinate descent, convex approximation, and alternating direction method of multipliers techniques is proposed to optimize the AP transmit beamforming vector and the RIS reflect beamforming matrix. Simulation results demonstrate the effectiveness of the algorithm.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2023)
Article
Engineering, Electrical & Electronic
Zechen Liu, Xin Liu, Victor C. M. Leung, Tariq S. Durrani
Summary: In this paper, a dual-UAV-assisted IoT using non-orthogonal multiple access (NOMA) is proposed to improve IoT capacity. By optimizing communication scheduling, UAV transmit power and UAV motion parameters, energy consumption of the UAVs can be reduced while ensuring a certain throughput. The numerical results show that optimizing UAV motion parameters can effectively improve energy efficiency of UAVs, and the proposed dual-NOMA-UAV assisted IoT achieves higher energy efficiency than the OMA-UAV assisted IoT.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2023)
Article
Engineering, Electrical & Electronic
Xin Liu, Yingfeng Yu, Bao Peng, Xiangping Bryce Zhai, Qiuming Zhu, Victor C. M. Leung
Summary: This paper studies secure downlink communication in worst-case scenarios where a base station communicates with a mobile vehicle with the presence of an eavesdropper. A reconfigurable intelligent surface mounted unmanned aerial vehicle (RIS-UAV) is employed as an aerial passive relay to assist the communication. The goal is to maximize the worst-case downlink secrecy rate by optimizing power allocation, RIS passive beamforming, and UAV trajectory. The formulated optimization problem is non-convex and non-smooth, and is divided into three subproblems for solution using successive convex approximation (SCA), $\mathcal {S}$-Procedure, and semidefinite relaxation (SDR). An alternating iterative optimization algorithm is proposed to obtain suboptimal solutions. Numerical simulations demonstrate the effectiveness of the proposed scheme compared to other benchmarks.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2023)
Article
Engineering, Multidisciplinary
Yupei Liu, Haijun Zhang, Huan Zhou, Keping Long, Victor C. M. Leung
Summary: This paper focuses on the resource allocation problem in the space-air-ground integrated vehicular networks (SAGVN). It proposes a user association and subchannel/power allocation scheme to optimize the connection and communication performance of small cells. Edge computing is also applied to offload local tasks to improve communication performance.
IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING
(2023)
Article
Telecommunications
Huan Zhou, Zhenyu Zhang, Yuan Wu, Mianxiong Dong, Victor C. M. Leung
Summary: This paper considers the joint optimization of computation offloading, service caching, and resource allocation in a collaborative MEC system with multi-users. The problem is formulated as a Mixed-Integer Non-Linear Programming (MINLP) aiming to minimize the long-term energy consumption of the system. A Deep Deterministic Policy Gradient (DDPG) based algorithm is proposed to solve the optimization problem and determine the strategies for computation offloading, service caching, and resource allocation. Simulation results show that the proposed DDPG based algorithm can significantly reduce the long-term energy consumption of the system and outperform other benchmark algorithms in different scenarios.
IEEE TRANSACTIONS ON GREEN COMMUNICATIONS AND NETWORKING
(2023)
Article
Engineering, Civil
Xiaobo Yang, Daosen Zhai, Ruonan Zhang, Lei Liu, F. Richard Yu, Victor C. M. Leung
Summary: This paper proposes an A2G channel model with UAV 3D wobbles based on the geometry-based stochastic model (GBSM) and analyzes its characteristics. The study finds that even slight wobbles of UAVs can significantly affect the channel's temporal correlation. Numerical results show that the channel's correlation function decreases rapidly with increasing wobble angles and carrier frequency. This research contributes to the theoretical exploration and system design of A2G communication based on UAVs.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2023)
Article
Computer Science, Artificial Intelligence
Yongfeng Li, Lingjie Li, Huimei Tang, Qiuzhen Lin, Zhong Ming, Victor C. M. Leung
Summary: This paper proposes a low-consumption redefined decision variable analysis (R-DVA) method for solving large-scale multiobjective optimization problems (LMOPs). R-DVA detects the interrelationship among convergent decision variables using a distance-based hierarchical clustering method, saving a large number of evaluations. Additionally, an evolutionary-state-oriented evolutionary (EsoE) strategy with two search models is designed to monitor the population's evolutionary state and achieve a good trade-off between convergence and diversity.
SWARM AND EVOLUTIONARY COMPUTATION
(2023)
Article
Computer Science, Information Systems
Dongyang Xu, Lei Liu, Ning Zhang, Mianxiong Dong, Victor C. M. Leung, James A. Ritcey
Summary: Protecting the initial access of IoT devices over wireless channels is challenging, especially when malicious quantum adversaries tamper critical wireless messages. We propose a nested hash access system with post-quantum encryption to solve this issue. The system encodes and decodes preambles precisely and resiliently using random repetition coding and nested hash coding on multidomain physical-layer resources.
IEEE INTERNET OF THINGS JOURNAL
(2023)
Article
Engineering, Electrical & Electronic
Kisong Lee, Hyun-Ho Choi, Woongsup Lee, Victor C. M. Leung
Summary: Interference, traditionally seen as detrimental to wireless communications, can be converted into a viable energy source for low-powered IoT devices through wireless energy harvesting. This paper introduces a wireless-powered interference network (WPIN) that proactively controls interference to improve bidirectional transmission rates. It presents an overview of WPIN applications in various wireless topologies, introduces a wireless interference harvesting protocol, and investigates coordinated resource management and beamforming schemes to improve WPIN performance. The simulation results demonstrate that properly utilizing interference decreases negative effects on information decoding and increases harvested energy, thus improving both downlink and uplink capacities.
IEEE VEHICULAR TECHNOLOGY MAGAZINE
(2023)
