Article
Computer Science, Information Systems
Fadhil Mukhlif, Norafida Ithnin, Omar B. Abdulghafoor, Faiz Alotaibi, Nourah Saad Alotaibi
Summary: By using network densification and unmanned aerial vehicle (UAV) communications, network coverage and throughput can be improved. This paper proposes a cognitive UAV for providing power to wireless nodes in IoT ground terminals and uses non-cooperative game theory to optimize users' utility function. Furthermore, an energy efficiency power allocation algorithm is proposed to achieve efficient power control in IoT wireless nodes.
CMC-COMPUTERS MATERIALS & CONTINUA
(2022)
Article
Telecommunications
Janani Natarajan, B. Rebekka
Summary: This paper proposes an ML based small cell ON/OFF algorithm in 5G Hetnets to address the challenges of throughput reduction and optimum power consumption in the small cell switching process. The network parameters affecting the system throughput are identified and a ML model is trained to predict the throughput and the required number of active small cells. The simulation results show a 17% improvement in throughput and energy efficiency compared to benchmark schemes.
WIRELESS PERSONAL COMMUNICATIONS
(2023)
Article
Computer Science, Hardware & Architecture
Sakshi Popli, Rakesh Kumar Jha, Sanjeev Jain
Summary: This study focuses on improving the energy efficiency of NB-loT DL performance by using small cell access points, considering two SCA positioning algorithms. The proposed adaptive SCA positioning algorithm (ASPA) shows significant improvement in saving energy consumption and enhancing sensor network efficiency, showcasing promising potential in communication.
JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
(2021)
Article
Computer Science, Information Systems
Ruiting Zhou, Xueying Zhang, Shixin Qin, John C. S. Lui, Zhi Zhou, Hao Huang, Zongpeng Li
Summary: This article introduces the deployment of small cells in 5G networks and their partnership with edge computing. It also proposes an online learning framework, LFSC, to guide task offloading in small cell networks. The theoretical analysis and simulation studies demonstrate the advantages of LFSC.
IEEE TRANSACTIONS ON MOBILE COMPUTING
(2022)
Article
Computer Science, Information Systems
Amna Mughees, Mohammad Tahir, Muhammad Aman Sheikh, Abdul Ahad
Summary: The review discusses various approaches to solving energy efficiency problems in ultra-dense networks, focusing on popular strategies such as machine learning, game theory, stochastic, and heuristic techniques. The challenges for improving energy efficiency in an ultra-dense network are identified and future research directions for enhancing energy efficiency in 5G and beyond 5G networks are outlined.
Article
Engineering, Electrical & Electronic
M. V. S. Aditya, Chitrarth Shrivastava, Gaurav S. Kasbekar
Summary: This paper discusses the energy savings and conditions for stable alliances when users cooperate in transferring files in a cellular network using D2D communication. By utilizing cooperative game theory and stable partitions framework, we study the problems under two different file transfer models and explore the complexity of the solutions.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2021)
Article
Computer Science, Hardware & Architecture
Hao Ran Chi, Ayman Radwan
Summary: The article presents a generic SC overlaid HetNet infrastructure for various OdD applications, conducts a survey of existing works, and highlights future research opportunities in the area of OdD optimization in SC-based mobile networks.
Review
Automation & Control Systems
Tulsi Pawan Fowdur, Bhuvaneshwar Doorgakant
Summary: This paper focuses on the energy consumption at the base station and access network levels in mobile networks, and suggests that machine learning techniques can be used to improve the energy efficiency in these components. The paper extensively reviews efficient base station deployment strategies, adaptive operational modes, and access network technologies that employ machine learning to enhance energy efficiency. It proposes a framework that combines efficient base station deployment methods and machine learning-based switching between different operation modes based on traffic load. The paper also discusses in detail an adaptive beamforming methodology for hotspot and user association, sub-channel and power allocation in heterogeneous networks.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2023)
Article
Computer Science, Information Systems
Azadeh Pourkabirian, Mohammad Hossein Anisi, Fereshteh Kooshki
Summary: This study proposes a power optimization approach for 5G femtocell networks, which uses non-cooperative game theory and a pricing mechanism to ensure quality of service for macro users and manage interference, ultimately optimizing network throughput and meeting QoS requirements for both macro and femto users.
COMPUTER COMMUNICATIONS
(2021)
Article
Thermodynamics
Hamed Jafari, Soroush Safarzadeh, Ehsan Azad-Farsani
Summary: This research investigates the impact of energy efficiency improvement in hydrogen fuel cell cars on sustainable development, considering a supply chain involving government, supplier, manufacturer, agency, and customers. The study finds that increasing the efficiency improvement rate can increase the demand for hydrogen cars and members' profits, under government incentives.
Article
Automation & Control Systems
Xiaohong Guan, Zhanbo Xu, Yaping Liu, Jiang Wu, Jiang Zhu, Wenwei Xu
Summary: This article reviews two main approaches to enhancing energy efficiency of wireless communication systems and presents a new optimization-based approach to reducing the energy consumption and costs.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2023)
Article
Engineering, Electrical & Electronic
Khushboo Mawatwal, Rajarshi Roy, Debarati Sen
Summary: This paper addresses resource allocation in interference-prone 5G small-cell networks, proposing a potential game based on state and utilizing both time-invariant and time-varying communication graph structures. Through extensive simulations, it is shown that the proposed algorithm outperforms existing schemes in terms of QoE, computational complexity, and stability of resource allocation, while remaining robust to wireless link failure and state transitions. Additionally, it exhibits relatively less performance degradation under imperfect channel state information compared to current methods.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2021)
Article
Computer Science, Artificial Intelligence
Theodor Cimpeanu, Cedric Perret, The Anh Han
Summary: This study focuses on achieving optimal outcomes at minimal costs by analyzing interference mechanisms based on different levels of information and fairness standards in the Ultimatum game in a spatial setting. The research reveals that strict information gathering is required for monitoring the population at a macroscopic level to obtain optimal results, with local observations being able to mediate this requirement.
KNOWLEDGE-BASED SYSTEMS
(2021)
Article
Computer Science, Hardware & Architecture
Aamina Akbar, Sobia Jangsher, Farrukh A. Bhatti
Summary: PD-NOMA leverages users' distinct channel gains for multiplexing different signals in a single resource block in power domain, resulting in higher spectral efficiency, improved user fairness, better cell-edge throughput, increased reliability and connectivity, and low latency.
Article
Computer Science, Information Systems
Lionel Nkenyereye, Ramavath Prasad Naik, Jong-Wook Jang, Wan-Young Chung
Summary: Vehicle-to-everything services are being implemented and automakers recognize the potential of V2X in enhancing safety applications. LTE-V and C-V2X technologies are introduced to support V2V, V2I, and V2N services. To overcome the challenges posed by high mobility, cutting-edge technologies like SDN and small cells are utilized in 5G networks. Small cells, which are lower-power cell sites deployed at regular intervals, coupled with SDN-based control, play a crucial role in creating a cluster platform with high computation performance. A novel distributed software-defined small cell-linked road side unit vehicular network architecture is proposed, which improves packet delivery ratio and minimizes end-to-end delay according to the simulation results.
Article
Engineering, Electrical & Electronic
Hang Zou, Chao Zhang, Samson Lasaulce, Lucas Saludjian, H. Vincent Poor
Summary: This paper discusses the problem of executing a task from a quantized version of the information source. The task is modeled by minimizing a general goal function with quantized parameters. The paper shows how to design a quantizer to minimize the gap between the quantized version and the optimal result. The analysis provides quantization strategies and allows a practical algorithm to be designed.
IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS
(2023)
Article
Engineering, Electrical & Electronic
Mohammad Karimzadeh Farshbafan, Walid Saad, Merouane Debbah
Summary: This paper proposes a holistic goal-oriented semantic communication framework to facilitate cooperative execution of sequential tasks in a dynamic environment between a speaker and a listener. A common language based on a hierarchical belief set is introduced for semantic communications between speaker and listener. A novel bottom-up curriculum learning (CL) framework based on reinforcement learning is proposed to solve the optimization problem and gradually identify the structure of the belief set and the perfect and abstract description of the events.
IEEE TRANSACTIONS ON COMMUNICATIONS
(2023)
Article
Engineering, Electrical & Electronic
Ju-Hyung Lee, Hyowoon Seo, Jihong Park, Mehdi Bennis, Young-Chai Ko
Summary: This paper proposes a novel contention-based random access solution for low Earth orbit satellite (LEO SAT) networks, called eRACH, which achieves automatic protocol establishment through multi-agent deep reinforcement learning in a non-stationary network environment. In contrast to existing model-based and standardized protocols, eRACH does not require central coordination or additional communication across users, and training convergence is stabilized through regular orbiting patterns. Compared to RACH, simulation results show that eRACH achieves 54.6% higher average network throughput, around two times lower average access delay, and a Jain's fairness index of 0.989.
IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS
(2023)
Article
Computer Science, Hardware & Architecture
Won Joon Yun, Yunseok Kwak, Hankyul Baek, Soyi Jung, Mingyue Ji, Mehdi Bennis, Jihong Park, Joongheon Kim
Summary: This paper proposes a novel learning framework by integrating Federated Learning (FL) with width-adjustable slimmable neural networks (SNNs) to address the challenges posed by heterogeneous energy, wireless channel conditions, and non-IID data distributions. The proposed method, named SlimFL, utilizes superposition coding (SC) and superposition training (ST) to achieve communication and energy efficiency in global model aggregation and local model updating. Formal proofs and data-intensive simulations demonstrate that SlimFL is capable of dealing with non-IID data distributions and poor channel conditions while maintaining high communication efficiency.
IEEE-ACM TRANSACTIONS ON NETWORKING
(2023)
Article
Entomology
Sheng-Yu Zhang, Han Gao, Ankarjan Askar, Xing-Peng Li, Guo-Cai Zhang, Tian-Zhong Jing, Hang Zou, Hao Guan, Yun-He Zhao, Chuan-Shan Zou
Summary: This study reveals that the steroid hormone 20-hydroxyecdysone (20E) disrupts lipid metabolism in the fat body of Hyphantria cunea larvae, accelerating fatty acid beta-oxidation and promoting lipolysis. However, it negatively regulates gluconeogenesis.
Article
Computer Science, Information Systems
Ali Pourranjbar, Georges Kaddoum, Walid Saad
Summary: Conventional anti-jamming methods are ineffective against a single jammer following multiple different jamming policies or multiple jammers with distinct policies. This article proposes an anti-jamming method that can adapt to the current jamming attack and estimates future occupied channels in the multiple jammers scenario. The proposed methods outperform the baseline method and achieve high success rates and ergodic rates.
IEEE INTERNET OF THINGS JOURNAL
(2023)
Article
Engineering, Electrical & Electronic
Gilsoo Lee, Walid Saad, Mehdi Bennis, Cheonyong Kim, Minchae Jung
Summary: In this paper, the problem of ephemeral edge computing in IoT is studied, and a novel online framework is proposed to optimize task allocation and computation in a limited time period. By considering communication and computation latency, the proposed framework maximizes the number of computed tasks and solves the joint optimization problem using an online greedy algorithm. Simulation results demonstrate that the proposed online algorithm achieves near-optimal task allocation with an optimality gap no higher than 7.1% compared to the offline, optimal solution with complete task knowledge.
IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS
(2023)
Article
Thermodynamics
Cary A. Faulkner, Dominik S. Jankowski, John E. Castellini, Wangda Zuo, Philipp Epple, Michael D. Sohn, Ali Taleb Zadeh Kasgari, Walid Saad
Summary: The study proposes a CGAN model for predicting indoor airflow distribution and addresses the limitations of current methods, including limited output prediction. A novel feature-driven algorithm is also designed to reduce the amount of expensive training data while maintaining prediction accuracy.
BUILDING SIMULATION
(2023)
Article
Computer Science, Information Systems
Sheikh Salman Hassan, Do Hyeon Kim, Yan Kyaw Tun, Nguyen H. H. Tran, Walid Saad, Choong Seon Hong
Summary: This study investigates the design of an energy-efficient resource allocation system for non-terrestrial networks (NTNs) that integrates space and aerial networks with terrestrial systems. The goal is to maximize system energy efficiency by optimizing user equipment association, power control, and unmanned aerial vehicle deployment. The study proposes a mixed-integer nonlinear programming problem and develops an algorithm to decompose and solve each problem distributedly. Simulation results demonstrate that the algorithm achieves better energy efficiency and spectral efficiency than baselines.
IEEE INTERNET OF THINGS JOURNAL
(2023)
Editorial Material
Engineering, Multidisciplinary
Zhi Zhou, Dusit Niyato, Zehui Xiong, Xiaowen Gong, Walid Saad, Xiaoming Fu
Summary: The papers in this special issue discuss the interaction between edge computing and artificial intelligence (AI) in 6G mobile communication networks. They focus on the potential of 6G networks to create an Internet of Intelligence by connecting people, things, and intelligence to solve human challenges and improve our world. Edge computing, which pushes computing tasks and services from the network core to the edge, is recognized as an essential component for empowering 6G networks with AI capabilities.
IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING
(2023)
Article
Microbiology
Mary E. Crompton, Luca F. Gaessler, Patrick O. Tawiah, Lisa Polzer, Sydney K. Camfield, Grady D. Jacobson, Maren K. Naudszus, Colton Johnson, Kennadi Meurer, Mehdi Bennis, Brendan Roseberry, Sadia Sultana, Jan-Ulrik Dahl
Summary: In this study, the researchers identified a novel defense strategy, the RcrR regulon, in uropathogenic Escherichia coli (UPEC), which protects the bacteria from the antimicrobial oxidant hypochlorous acid (HOCl). They found that the expression of the rcrARB operon, controlled by the HOCl-sensing transcriptional repressor RcrR, plays a crucial role in protecting UPEC from HOCl. The deletion of the rcrB gene, encoding a hypothetical membrane protein, increased UPEC's susceptibility to HOCl. The researchers also investigated the mechanism behind RcrB's protection and found that RcrB expression is induced by and protects from several reactive chlorine species (RCS) but not reactive oxygen species (ROS). RcrB plays a protective role for RCS-stressed planktonic cells under various growth and cultivation conditions, but does not seem to be relevant for UPEC's biofilm formation.
JOURNAL OF BACTERIOLOGY
(2023)
Article
Computer Science, Information Systems
David E. E. Ruiz-Guirola, Onel L. A. Lopez, Samuel Montejo-Sanchez, Richard Demo Souza, Mehdi Bennis
Summary: Prolonging the lifetime of MTC networks is crucial for a sustainable digitized society. Accurately predicting MTC traffic and optimizing resource allocation can lead to significant energy savings. However, selecting the right predictor depends on trade-offs between accuracy, complexity, and network characteristics, and this debate is lacking in current literature.
IEEE WIRELESS COMMUNICATIONS LETTERS
(2023)
Proceedings Paper
Computer Science, Hardware & Architecture
Mounssif Krouka, Anis Elgabli, Chaouki ben Issaid, Mehdi Bennis
Summary: In this paper, a decentralized Newton-type approach is proposed to solve the problem of decentralized federated learning. The algorithm leverages the fast convergence of second-order methods and reduces communication and privacy concerns. The approach consists of solving an inner problem and an outer problem alternately using a decentralized manner and performing one decentralized Newton step at every iteration. Simulation results demonstrate that the proposed algorithm outperforms several baselines and provides efficient solutions for bandwidth-limited systems under different SNR regimes.
2023 IEEE WIRELESS COMMUNICATIONS AND NETWORKING CONFERENCE, WCNC
(2023)
Article
Chemistry, Multidisciplinary
Mohammad Fahda, Manal Ammar, Walid Saad, Mohamad Hmadeh, Mazen Al-Ghoul
Summary: In this study, the high-quality synthesis of ZIF-(8, 67) crystals and their mixed metal derivatives was achieved in an aqueous medium with reduced organic ligand consumption and controlled particle size. The rapid and precise control over the transition from ZIF-L to ZIF-(8, 67) was demonstrated using flow rates and molar ratios of the initial ZIF precursors. The synthesis of smaller ZIF-8 nanoparticles and the controlled doping of ZIF-8 with cobalt were also achieved.
Article
Computer Science, Information Systems
Yantong Wang, Ye Hu, Zhaohui Yang, Walid Saad, Kai-Kit Wong, Vasilis Friderikos
Summary: This paper proposes a novel framework for proactive caching that combines model-based optimization with data-driven techniques. It transforms an optimization problem into a grayscale image and uses Convolutional Neural Networks (CNNs) to predict content caching locations. Two algorithms are provided to address competition and accelerate search.
IEEE TRANSACTIONS ON MOBILE COMPUTING
(2023)
