Article
Computer Science, Hardware & Architecture
Martha Hernandez Ochoa, Mario Siller, Hector A. Duran-Limon, Liliana Duran-Polanco
Summary: With the rise of 5G technology, the importance of heterogeneous networks (HetNets) has increased, requiring cooperation between networks such as WiFi and LTE to ensure high-quality service and maximum throughput. This study proposes a WiFi available bandwidth estimation technique and traffic steering strategy to improve WiFi-LTE network performance and reduce LTE usage and charges.
COMPUTER STANDARDS & INTERFACES
(2021)
Article
Engineering, Multidisciplinary
Muhammad Khurram Ehsan, Asghar Ali Shah, Muhammad Rizwan Amirzada, Neelma Naz, Kostromitin Konstantin, Muhammad Sajid, Asad Raza Gardezi
Summary: The CR-enabled radio environment provides a seamless operating framework to meet the requirements of next-generation wireless systems. Traffic characterization studies help optimize the coexistence framework, and the multivariate Gaussian mixture model (MGMM) is proposed in both scenarios for sparse WLAN data traffic.
ALEXANDRIA ENGINEERING JOURNAL
(2021)
Article
Computer Science, Information Systems
Miguel Sepulcre, Javier Gozalvez
Summary: This paper introduces a new heterogeneous V2V communication algorithm that dynamically selects communication technology based on vehicles' application requirements and communication conditions. It aims to meet vehicles' application needs and improve network capacity.
IEEE TRANSACTIONS ON MOBILE COMPUTING
(2021)
Article
Telecommunications
R. Narmadha, U. Anitha
Summary: In heterogeneous networks, long authentication delays are observed, causing decreased throughput and increased duration for the entire authentication process. Key exchange between administrative domains leads to authentication delay. The increasing number of mobile nodes requesting authentication results in higher operating cost and poses a significant challenge. Interoperability of dissimilar networks is necessary for better data rates, spectrum efficiency, and serviceability. Proposed research aims at developing an efficient authentication technique to enhance data transmission security in heterogeneous networks.
WIRELESS PERSONAL COMMUNICATIONS
(2023)
Article
Chemistry, Analytical
Juan Jesus Hernandez-Carlon, Jordi Perez-Romero, Oriol Sallent, Irene Vila, Ferran Casadevall
Summary: This paper proposes a deep reinforcement learning solution for optimizing traffic allocation in multi-connectivity networks. The results show that this approach performs near-optimally and outperforms other reference schemes.
Article
Telecommunications
Mhd Saria Allahham, Alaa Awad Abdellatif, Naram Mhaisen, Amr Mohamed, Aiman Erbad, Mohsen Guizani
Summary: This paper presents a distributed framework for dynamic network selection and resource allocation, using a deep Multi-Agent Reinforcement Learning algorithm to maximize edge nodes' quality of experience, improve energy efficiency, and leverage adaptive compression schemes. Experimental results demonstrate that the framework outperforms state-of-the-art network selection techniques in terms of energy consumption, latency, and cost.
IEEE TRANSACTIONS ON COGNITIVE COMMUNICATIONS AND NETWORKING
(2022)
Article
Computer Science, Information Systems
Feng Wang, Vincent K. N. Lau
Summary: This article investigates the joint RAT selection and transceiver design for over-the-air aggregation of intermediate values (IVAs) in multi-RAT MEC systems. A low-complexity algorithm is proposed to solve the problem, and extensive numerical results verify its effectiveness compared to other existing schemes.
IEEE INTERNET OF THINGS JOURNAL
(2022)
Article
Engineering, Electrical & Electronic
Chia-Peng Lee, Phone Lin, Yingrong Coral Sung
Summary: The paper proposes the Module Switching Mechanism (MSM) consisting of the PS scheme and the AWU scheme to reduce the power consumption for dual-mode smart devices. By controlling the on/off of LTE transceiver module with timers in the PS scheme, and allowing LTE module to be turned on through NB-IoT module in the AWU scheme, the power saving ratio and call dropping probability are studied through analytical models and simulation experiments.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2021)
Article
Biochemical Research Methods
Yang Yue, Yongxuan Liu, Luoying Hao, Huangshu Lei, Shan He
Summary: Drug combinations can have both therapeutic effects and adverse effects. By learning the shared mechanistic commonalities between these effects, a multi-task heterogeneous network learning method called Muthene was developed, which improved the accuracy of therapeutic effect predictions by including adverse effect predictions as an auxiliary task.
BRIEFINGS IN BIOINFORMATICS
(2023)
Article
Biochemical Research Methods
Yang Yue, Yongxuan Liu, Luoying Hao, Huangshu Lei, Shan He
Summary: Drug combinations can have both therapeutic effects and adverse effects. We proposed a method called Muthene to improve the accuracy of therapeutic effect predictions by learning the shared mechanistic commonalities between therapeutic effects and adverse effects. Experimental results showed that Muthene generated more accurate predictions and provided a deeper understanding of the mechanisms of drug combinations.
BRIEFINGS IN BIOINFORMATICS
(2022)
Article
Computer Science, Artificial Intelligence
Wei Dong, Junsheng Wu, Xinwan Zhang, Zongwen Bai, Peng Wang, Marcin Wozniak
Summary: Aggregation functions based on full rank aggregation matrices and injective aggregation functions are explored in this work to enhance the representation capacity of Graph Neural Networks (GNNs). The injectivity of aggregation functions is proven to be necessary for ensuring rich representation capacity. By using injective aggregation functions as a pre-processing step, satisfactory performance and computational efficiency are achieved on large-scale graph-based traffic data for traffic state prediction tasks.
KNOWLEDGE-BASED SYSTEMS
(2022)
Article
Transportation Science & Technology
Martin Rodriguez-Vega, Carlos Canudas-de-Wit, Hassen Fourati
Summary: This study proposes a data-based approach for estimating the vehicle density of each road section in an urban traffic network. Real data from Grenoble, France is used to validate the estimator, and the results show that the proposed methods perform well.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2022)
Article
Engineering, Electrical & Electronic
Jeremiah O. Abolade, Dominic B. O. Konditi
Summary: This work presents a meanderingly slitted bio-inspired (MSB)-shaped antenna, operating at 2.1GHz and 5.2GHz frequencies with high radiation efficiency and bandwidth, suitable for various applications.
INTERNATIONAL JOURNAL OF ANTENNAS AND PROPAGATION
(2022)
Article
Engineering, Electrical & Electronic
Fereshteh Atri Niasar, Amir Reza Momen, Seyed Abolfazl Hosseini
Summary: This paper proposes a dynamic optimization model that maximizes the total uplink/downlink energy efficiency in heterogeneous cellular networks. By applying different optimization methods, fair resource management can be achieved, leading to a significant improvement in the overall network energy efficiency.
AEU-INTERNATIONAL JOURNAL OF ELECTRONICS AND COMMUNICATIONS
(2022)
Article
Chemistry, Multidisciplinary
Dariusz Wiecek, Igor Michalski, Krzysztof Rzezniczak, Dariusz Wypior
Summary: This paper presents a method for implementing wireless traffic steering in mobile networks, using a high-level multi-RAT heterogeneous network orchestration approach to achieve maximum energy efficiency and improve the energy consumption efficiency of user mobile terminals.
APPLIED SCIENCES-BASEL
(2021)