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View article: Energy-Efficient Resource Allocation Scheme Based on Reinforcement Learning in Distributed LoRa Networks
Energy-Efficient Resource Allocation Scheme Based on Reinforcement Learning in Distributed LoRa Networks Open
The rapid growth of Long Range (LoRa) devices has led to network congestion, reducing spectrum and energy efficiency. To address this problem, we propose an energy-efficient reinforcement learning method for distributed LoRa networks, enab…
View article: Energy Efficient Transmission Parameters Selection Method Using Reinforcement Learning in Distributed LoRa Networks
Energy Efficient Transmission Parameters Selection Method Using Reinforcement Learning in Distributed LoRa Networks Open
With the increase in demand for Internet of Things (IoT) applications, the number of IoT devices has drastically grown, making spectrum resources seriously insufficient. Transmission collisions and retransmissions increase power consumptio…
View article: A Seesaw Model Attack Algorithm for Distributed Learning
A Seesaw Model Attack Algorithm for Distributed Learning Open
We investigate the Byzantine attack problem within the context of model training in distributed learning systems. While ensuring the convergence of current model training processes, common solvers (e.g. SGD, Adam, RMSProp, etc.) can be eas…
View article: Adaptive Learning of Consistency and Inconsistency Information for Fake News Detection
Adaptive Learning of Consistency and Inconsistency Information for Fake News Detection Open
The rapid advancement of social media platforms has significantly reduced the cost of information dissemination, yet it has also led to a proliferation of fake news, posing a threat to societal trust and credibility. Most of fake news dete…
View article: Elucidating the Molecular Pathways and Therapeutic Interventions of Gaseous Mediators in the Context of Fibrosis
Elucidating the Molecular Pathways and Therapeutic Interventions of Gaseous Mediators in the Context of Fibrosis Open
Fibrosis, a pathological alteration of the repair response, involves continuous organ damage, scar formation, and eventual functional failure in various chronic inflammatory disorders. Unfortunately, clinical practice offers limited treatm…
View article: An efficient beaconing of bluetooth low energy by decision making algorithm
An efficient beaconing of bluetooth low energy by decision making algorithm Open
Ongoing research endeavors are exploring the potential of artificial intelligence to enhance the efficiency of wireless communication systems. Nevertheless, complex computational mechanisms, such as those inherent in neural networks, are n…
View article: An Intelligent Multi-Local Model Bearing Fault Diagnosis Method Using Small Sample Fusion
An Intelligent Multi-Local Model Bearing Fault Diagnosis Method Using Small Sample Fusion Open
It is essential to accurately diagnose bearing faults to avoid property losses or casualties in the industry caused by motor failures. Recently, the methods of fault diagnosis for bearings using deep learning methods have improved the safe…
View article: Combinatorial MAB-Based Joint Channel and Spreading Factor Selection for LoRa Devices
Combinatorial MAB-Based Joint Channel and Spreading Factor Selection for LoRa Devices Open
Long-Range (LoRa) devices have been deployed in many Internet of Things (IoT) applications due to their ability to communicate over long distances with low power consumption. The scalability and communication performance of the LoRa system…
View article: Pairing Optimization via Statistics: Algebraic Structure in Pairing Problems and Its Application to Performance Enhancement
Pairing Optimization via Statistics: Algebraic Structure in Pairing Problems and Its Application to Performance Enhancement Open
Fully pairing all elements of a set while attempting to maximize the total benefit is a combinatorically difficult problem. Such pairing problems naturally appear in various situations in science, technology, economics, and other fields. I…
View article: A Deep-Learning-Based Fault Diagnosis Method of Industrial Bearings Using Multi-Source Information
A Deep-Learning-Based Fault Diagnosis Method of Industrial Bearings Using Multi-Source Information Open
In recent years, the industrial motor bearing fault diagnosis method based on deep learning and multi-source information fusion has made some research progress, and research results show that the uncertainty of noise interference and signa…
View article: UAV data delivery and routing optimization in Piggyback Network
UAV data delivery and routing optimization in Piggyback Network Open
The Piggyback Network has been proposed as one of the technologies to enable Beyond 5G society. The Piggyback Network provides a high-speed data transfer system with frequency radio, such as millimeter-wave (mmW) links and Store-Carry-Forw…
View article: High-Speed Resource Allocation Algorithm Using a Coherent Ising Machine for NOMA Systems
High-Speed Resource Allocation Algorithm Using a Coherent Ising Machine for NOMA Systems Open
Non-orthogonal multiple access (NOMA) technique is important for achieving a high data rate in next-generation wireless communications. A key challenge to fully utilizing the effectiveness of the NOMA technique is the optimization of the r…
View article: Pairing optimization via statistics: Algebraic structure in pairing problems and its application to performance enhancement
Pairing optimization via statistics: Algebraic structure in pairing problems and its application to performance enhancement Open
Fully pairing all elements of a set while attempting to maximize the total benefit is a combinatorically difficult problem. Such pairing problems naturally appear in various situations in science, technology, economics, and other fields. I…
View article: A Lightweight Transmission Parameter Selection Scheme Using Reinforcement Learning for LoRaWAN
A Lightweight Transmission Parameter Selection Scheme Using Reinforcement Learning for LoRaWAN Open
The number of IoT devices is predicted to reach 125 billion by 2023. The growth of IoT devices will intensify the collisions between devices, degrading communication performance. Selecting appropriate transmission parameters, such as chann…
View article: Multi-Armed-Bandit Based Channel Selection Algorithm for Massive Heterogeneous Internet of Things Networks
Multi-Armed-Bandit Based Channel Selection Algorithm for Massive Heterogeneous Internet of Things Networks Open
In recent times, the number of Internet of Things devices has increased considerably. Numerous Internet of Things devices generate enormous traffic, thereby causing network congestion and packet loss. To address network congestion in massi…
View article: BER Minimization by User Pairing in Downlink NOMA Using Laser Chaos Decision-Maker
BER Minimization by User Pairing in Downlink NOMA Using Laser Chaos Decision-Maker Open
In next-generation wireless communication systems, non-orthogonal multiple access (NOMA) has been recognized as essential technology for improving the spectrum efficiency. NOMA allows multiple users transmit data using the same resource bl…
View article: Dynamic channel bonding in WLANs by hierarchical laser chaos decision maker
Dynamic channel bonding in WLANs by hierarchical laser chaos decision maker Open
Laser chaos decision-maker has been demonstrated to enable ultrahigh-speed decision-making in solving multi-armed bandit (MAB) problems in the GHz order. In addition to recent intensive studies of photonic information processing devices an…
View article: User pairing using laser chaos decision maker for NOMA systems
User pairing using laser chaos decision maker for NOMA systems Open
Non-Orthogonal Multiple Access is one of the most important technologies in 5G and Beyond 5G wireless communications, which improve system performance by power domain multiplexing. In realizing Non-Orthogonal Multiple Access, the pairing o…
View article: A Localization Method Based on Partial Correlation Analysis for Dynamic Wireless Network
A Localization Method Based on Partial Correlation Analysis for Dynamic Wireless Network Open
Recent localization methods for wireless networks cannot be applied to dynamic networks with unknown topology. To solve this problem, we propose a localization method based on partial correlation analysis in this paper. We evaluate our pro…
View article: A reinforcement learning based collision avoidance mechanism to superposed LoRa signals in distributed massive IoT systems
A reinforcement learning based collision avoidance mechanism to superposed LoRa signals in distributed massive IoT systems Open
For Massive IoT systems, various Low Power Wide Area (LPWA) systems have been developed and deployed, i.e., LoRa, SigFox, etc. In this paper, to avoid destructive collisions when multiple IoT LoRa signals simultaneously received in the sam…
View article: Performance evaluation of pulse-based multiplexing protocol implemented on massive IoT devices
Performance evaluation of pulse-based multiplexing protocol implemented on massive IoT devices Open
An Internet of Things (IoT) employing resource-restricted (e.g., battery-limited) IoT devices at high densities will require an effective multiplexing protocol that can be implemented with low energy consumption, while being able to effect…
View article: Analysis on Effectiveness of Surrogate Data‐Based Laser Chaos Decision Maker
Analysis on Effectiveness of Surrogate Data‐Based Laser Chaos Decision Maker Open
The laser chaos decision maker has been demonstrated to enable ultra‐high‐speed solutions of multiarmed bandit problems or decision‐making in the GHz order. However, the underlying mechanisms are not well understood. In this paper, we anal…
View article: Multiple Radios for Fast Rendezvous in Heterogeneous Cognitive Radio Networks
Multiple Radios for Fast Rendezvous in Heterogeneous Cognitive Radio Networks Open
In cognitive radio networks (CRNs), if two unlicensed secondary users (SUs) want to communicate with each other, they need to rendezvous with each other on the same channel at the same time. Rendezvous is the first key step for SUs to be a…
View article: A Sensitive Secondary Users Selection Algorithm for Cognitive Radio Ad Hoc Networks
A Sensitive Secondary Users Selection Algorithm for Cognitive Radio Ad Hoc Networks Open
Secondary Users (SUs) are allowed to use the temporarily unused licensed spectrum without disturbing Primary Users (PUs) in Cognitive Radio Ad Hoc Networks (CRAHNs). Existing architectures for CRAHNs impose energy-consuming Cognitive Radio…
View article: Code Synchronization Algorithm Based on Segment Correlation in Spread Spectrum Communication
Code Synchronization Algorithm Based on Segment Correlation in Spread Spectrum Communication Open
Spread Spectrum (SPSP) Communication is the theoretical basis of Direct Sequence Spread Spectrum (DSSS) transceiver technology. Spreading code, modulation, demodulation, carrier synchronization and code synchronization in SPSP communicatio…
View article: Coordinate Channel-Aware Page Mapping Policy and Memory Scheduling for Reducing Memory Interference Among Multimedia Applications
Coordinate Channel-Aware Page Mapping Policy and Memory Scheduling for Reducing Memory Interference Among Multimedia Applications Open
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