Ishan Budhiraja
0000-0002-7495-5032
22 papers found
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Energy Maximization for Wireless Powered Communication Enabled IoT Devices With NOMA Underlaying Solar Powered UAV Using Federated Reinforcement Learning for 6G Networks
A Hybrid Secure Resource Allocation and Trajectory Optimization Approach for Mobile Edge Computing Using Federated Learning Based on WEB 3.0
A Hybrid Task Offloading and Resource Allocation Approach for Digital Twin-Empowered UAV-Assisted MEC Network Using Federated Reinforcement Learning for Future Wireless Network
A Cooperative Game Approach for Multi-lane Merging Decision-making Algorithm for CAVs
A Systematic Analysis of Enhancing Cyber Security Using Deep Learning for Cyber Physical Systems
Quantum Computing Integrated Patterns for Real-Time Cryptography in Assorted Domains
A Deep Reinforcement Learning Scheme for Sum Rate and Fairness Maximization Among D2D Pairs Underlaying Cellular Network With NOMA
Secrecy Rate Maximization in THz-Aided Heterogeneous Networks: A Deep Reinforcement Learning Approach
ETMA: Efficient Transformer-Based Multilevel Attention Framework for Multimodal Fake News Detection
Holochain: An Agent-Centric Distributed Hash Table Security in Smart IoT Applications
Latency-Energy Tradeoff in Connected Autonomous Vehicles: A Deep Reinforcement Learning Scheme
Energy Consumption Minimization Scheme for NOMA-Based Mobile Edge Computation Networks Underlaying UAV
An Energy Efficient Scheme for WPCN-NOMA Based Device-to-Device Communication
A Systematic Review on NOMA Variants for 5G and Beyond
ISHU: Interference Reduction Scheme for D2D Mobile Groups Using Uplink NOMA
URJA: Usage Jammer as a Resource Allocation for Secure Transmission in a CR-NOMA-Based 5G Femtocell System
Cross-Layer Interference Management Scheme for D2D Mobile Users Using NOMA
An Energy-Efficient Resource Allocation Scheme for SWIPT-NOMA based Femtocells users with Imperfect CSI
Energy-Delay Tradeoff Scheme for NOMA-Based D2D Groups With WPCNs
DIYA: Tactile Internet Driven Delay Assessment NOMA-Based Scheme for D2D Communication
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