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Enhanced Handover Management in 5G Networks using Machine Learning in Fading Scenarios 2

Enhanced Handover Management in 5G Networks using Machine Le...

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2nd International Conference on Computational Intelligence, Communication Technology and Networking, CICTN 2025

作者： Upadhyay, Deepak Rallapalli, Sreekanth Hussain, Zakir Venu, Nookala Sharma, Rashmi Shukla, Shipra Dept. of Computer Science and Engineering Graphic Era Hill University Dehradun India Department of MCA Nitte Meenakshi Institute of Technology Bengaluru India Centre for Internet of Things Madhav Institute of Technology & Science Deemed University Gwalior India Nagpur Campus Pune India G. L. Bajaj Institute of Technology and Management Greater Noida India

ISBN: (纸本)9798331530389

This study explores the use of machine learning (ML) to improve initial handover performance for 5G networks by analysing fading-affected scenarios. In this study, we assess the ability of ML models to predict optimal handover decisions compared with conventional methods. In this study, simulation results show that our ML-based methods can reduce the handover inaccuracy by 50%, decrease latency up to 10 times and stabilize network performance. We accompany our assessment with a series of graphical analyses to show how ML algorithms change their behaviour dynamically in response to deteriorating link intensity due user mobility and increasing h/o frequency, thereby degrading the network performance. The results clearly illustrate that ML enabled handover optimization is significantly more effective than traditional methods in accommodating fading-channel dynamics, thereby improving both the network performance and user experience of future generation wireless networks. © 2025 IEEE.

关键词： 5G mobile communication systems

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Machine Learning-driven Antenna Selection Strategies for Fading MIMO Systems

Machine Learning-driven Antenna Selection Strategies for Fad...

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Advancements and Key Challenges in Green Energy and Computing (AKGEC), International Conference on

作者： Deepak Upadhyay Kunj Bihari Sharma Mridul Gupta Abhay Upadhyay Nookala Venu Dept. of Computer Science and Engineering Graphic Era Hill University Dehradun India Dept. of Computer Science and Engineering Graphic Era deemed to be University Dehradun India Centre for Internet of Things Madhav Institute of Technology & Science Deemed University Gwalior India

ISBN: (数字)9798350390179

ISBN: (纸本)9798350390186

In this study, we investigate better performing antenna selection strategies in wireless communication systems based on machine learning algorithms. Reinforcement learning as well as neural networks among others are analysed for different metrics such a bit error rate (BER), signal-to-noise ratio (SNR) and data throughput. These results show that these methods are working well against the dynamic changing of channel conditions to provide reliable and efficient. The computational complexity analysis suggests affordable overhead, allowing the feasibility of real-time implementation. Although this method can simulate the scenario in a real environment, it is not scalable due to simulation fidelity and antenna array. On the one hand, future research will refine and expand upon these ML models with real-time adaptation capabilities - On the other hand significant field trials are needed to put this work into practice for specific applications making sure that we develop robust adaptive wireless communication systems in practice.

关键词： Measurement Hands Adaptation models Machine learning algorithms Computational modeling Neural networks Reinforcement learning Throughput Real-time systems Signal to noise ratio

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DistB-VNET: Distributed Cluster-based Blockchain Vehicular Ad-Hoc Networks through SDN-NFV for Smart City

DistB-VNET: Distributed Cluster-based Blockchain Vehicular A...

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International Conference on computer and Information Technology (ICCIT)

作者： Anichur Rahman MD. Zunead Abedin Eidmum Dipanjali Kundu Mahir Hossain MD Tanjum An Tashrif Md Ahsan Karim Md. Jahidul Islam Dept. of Computer Science and Engineering National Institute of Textile Engineering and Research (NITER) Constituent Institute of Dhaka University Savar Dhaka Dept. of Internet of Things and Robotics Engineering Bangabandhu Sheikh Mujibur Rahman Digital University Dept. of Computer Science and Engineering Green University of Bangladesh

ISBN: (数字)9798331519094

ISBN: (纸本)9798331519100

In the developing topic of smart cities, Vehicular Ad-Hoc Networks (VANETs) are crucial for providing successful interaction between vehicles and infrastructure. This research proposes a distributed Blockchain-based Vehicular Ad-hoc Network ("DistB-VNET") architecture that includes binary malicious traffic classification, Software Defined Networking (SDN), and Network Function Virtualization (NFV) to ensure safe, scalable, and reliable vehicular networks in smart cities. The suggested framework is the decentralized blockchain for safe data management, SDN-NFV for dynamic network management and resource efficiency, and a noble isolation forest algorithm that works as an IDS (Intrusion Detection System). Further, "DistB-VNET" offers a dual-layer blockchain system, where a distributed blockchain provides safe communication between vehicles, while a centralized blockchain in the cloud is in charge of data verification and storage. This improves security, scalability, and adaptability, ensuring better traffic management, data security, and privacy in VANETs. Furthermore, the unsupervised isolation forest model achieves a high accuracy of 99.23% for detecting malicious traffic. Additionally, reveals that our method greatly improves network performance, offering decreased latency, increased security, and reduced congestion, an effective alternative for existing smart city infrastructures.

关键词： Smart cities Scalability Heuristic algorithms Forestry Dynamic scheduling Blockchains Network function virtualization Resource management Vehicle dynamics Software defined networking

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Deep Learning-Based Spectrum Sharing for Dynamic Resource Allocation in 6G Cognitive Radio Networks 4

Deep Learning-Based Spectrum Sharing for Dynamic Resource Al...

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4th International Conference on Power, Control and Computing Technologies, ICPC2T 2025

作者： Upadhyay, Deepak Upadhyay, Abhay Venu, Nookala Kukreti, Kamlesh Dept. of Computer Science and Engineering Graphic Era Hill University Dehradun India Dept. of Computer Science and Engineering Graphic Era Deemed to Be University Dehradun India Centre for Internet of Things Madhav Institute of Technology & Science Deemed University Gwalior India Dept. of Electronics and Communication Engineering Graphic Era Deemed to be University Dehradun India

ISBN: (纸本)9798331530402

We conduct an extensive study on deep learning-based spectrum sharing to resolve dynamic resource allocation in 6G cognitive radio networks in this paper. The approach uses modern machine learning models to optimize spectrum usage, increase prediction accuracy of spectrum availability, and reduce interference among the primary and secondary users. We need to evaluate the performance of deep learning algorithms against the traditional spectrum allocation methods in simulation. In the paper, regular quality of service metrics such as throughput distribution and fairness among users are demonstrated to be much improved with these results, where both latency and energy consumption have been cut down dramatically. This work demonstrates the paradigm-shifting role of deep learning in spectrum management for 6G networks, pointing towards intelligent and effective resource allocation mechanisms in tomorrow's communications. © 2025 IEEE.

关键词： Cognitive radio

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Deep Learning-Based Spectrum Sharing for Dynamic Resource Allocation in 6G Cognitive Radio Networks

Deep Learning-Based Spectrum Sharing for Dynamic Resource Al...

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Power, Control and Computing Technologies (ICPC2T), Conference on

作者： Deepak Upadhyay Abhay Upadhyay Nookala Venu Kamlesh Kukreti Dept. of Computer Science and Engineering Graphic Era Hill University Dehradun India Dept. of Computer Science and Engineering Graphic Era Deemed to Be University Dehradun India Centre for Internet of Things Madhav Institute of Technology & Science Deemed University Gwalior India Dept. of Electronics and Communication Engineering Graphic Era deemed to be University Dehradun India

ISBN: (数字)9798331530402

ISBN: (纸本)9798331530419

We conduct an extensive study on deep learningbased spectrum sharing to resolve dynamic resource allocation in 6G cognitive radio networks in this paper. The approach uses modern machine learning models to optimize spectrum usage, increase prediction accuracy of spectrum availability, and reduce interference among the primary and secondary users. We need to evaluate the performance of deep learning algorithms against the traditional spectrum allocation methods in simulation. In the paper, regular quality of service metrics such as throughput distribution and fairness among users are demonstrated to be much improved with these results, where both latency and energy consumption have been cut down dramatically. This work demonstrates the paradigm-shifting role of deep learning in spectrum management for $6 \mathbf{G}$ networks, pointing towards intelligent and effective resource allocation mechanisms in tomorrow’s communications.

关键词： Deep learning 6G mobile communication Accuracy Quality of service Interference Dynamic scheduling Throughput Resource management Cognitive radio Reliability

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Cyber security-based Multikey Management System in Cloud Environment 8

Cyber security-based Multikey Management System in Cloud Env...

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8th International Conference on engineering and Emerging Technologies, ICEET 2022

作者： Jeyaselvi, M. Jayakumar, C. Sathya, M. Ibrahim, S Jafar Ali Kalyan Chakravarthy, N.S. SRM Institute of Science and Technology Kattankulathur603203 India Sri Venkateshwara College of Engineering Department of Computer Science and Engineering Sriperumbudur India AMC Engineering College Dept of Information Science and Engineering Bengaluru Karnataka India Vellore Institute of Technology Dept of Internet of Things TN Vellore632014 India QIS College of Engineering and Technology Director-Data Science and Business Systems AP Ongole523 272 India

ISBN: (纸本)9781665491068

The revolutionary expansion in processing and storing mechanisms through the internet has given rise to affordable and powerful computing features. These qualities have been enhanced as a result of this growth. Computing in the cloud is an emerging technology that provides users with the ability to access data storage facilities as well as application access facilities in an online setting. This approach presents an almost infinite number of chances and difficulties. In light of this, ensuring the safety of one's data and preventing the accumulation of duplicate or otherwise identical information in the cloud are both highly critical concerns that must be handled. As a result, a method known as deduplication was created to cut down on the amount of data in the identical storage system. In this investigation, a unique approach for removing repetitive or duplicate data from cloud servers, which will also help reduce the amount of internet access and storage space needed, has been presented. The results of the experiments show that the suggested system not only offers a higher level of protection for the data that is stored in stored in the cloud but also addresses the primary issues of rent systems. © 2022 IEEE.

关键词： Cloud storage

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Optimal Resource Allocation in Dynamic Fading Channels via Meta-Learning Techniques

Optimal Resource Allocation in Dynamic Fading Channels via M...

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Advancements and Key Challenges in Green Energy and Computing (AKGEC), International Conference on

作者： Deepak Upadhyay Kunj Bihari Sharma Mridul Gupta Abhay Upadhyay Nookala Venu Dept. of Computer Science and Engineering Graphic Era Hill University Dehradun India Dept. of Computer Science and Engineering Graphic Era deemed to be University Dehradun India Dept. of Electronics and Communication Engineering Graphic Era deemed to be University Dehradun India Centre for Internet of Things Madhav Institute of Technology & Science Deemed University Gwalior India

ISBN: (数字)9798350390179

ISBN: (纸本)9798350390186

In this paper, we address the optimally dynamical resource allocation problem for fading channels utilizing meta-learning methods with an application to improve efficiency and performance in wireless communication systems. Extensive experiments are conducted and our meta-learning model has demonstrated the ability to adapt itself dynamically in various channel conditions, leading to improvement of Signal-to-Noise Ratio (SNR), reduction of Bit Error Rate (BER) and enhancement on throughput when compared with traditional methods. Visualizations like performance analysis comparisons, heatmaps or 3D plots are used to show how the model can be leverage as effectively manager of resources where they are and when they suit best. The performance improvements demonstrated here are statistically significant testifying for the scalability of our work. The findings of this study demonstrate the major benefits that can be achieved by meta-learning to overcome immanent issues in fast-changing wireless conditions and its potential to propel future communication technologies forward.

关键词： Metalearning Fading channels Wireless communication Heating systems Adaptation models Visualization Bit error rate Throughput Resource management Signal to noise ratio

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Delta-γ Modeling of Wireless System Resilience in Multipath Fading and Interference Environments

Delta-γ Modeling of Wireless System Resilience in Multipath...

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International Conference on Contemporary Computing and Informatics (IC3I)

作者： Deepak Upadhyay Abhay Upadhyay Kunj Bihari Sharma Mridul Gupta Nookala Venu Dept. of Computer Science and Engineering Graphic Era Hill University Dehradun India Dept. of Computer Science and Engineering Graphic Era deemed to be University Dehradun India Dept. of Electronics and Communication Engineering Graphic Era deemed to be University Dehradun India Centre for Internet of Things Madhav Institute of Technology & Science Deemed University Gwalior India

ISBN: (数字)9798350350067

ISBN: (纸本)9798350350074

In this paper, we pursue the resilience of wireless communication systems in multipath fading and interference environments utilizing Delta- $\gamma$ modelling. Furthermore, fading phenomena such as Rayleigh/Rician/Nakagami channels can be simulated to examine the impact on important performance metrics like SNR, BER and throughput. Different types of interference scenarios, covering co-channel and adjacent channel interferences are also studied to understand impact on system capacity as well as reliability. This article investigates the use of adaptive modulation techniques, multiple-input multiple-output (MIMO) strategies and advanced interference management schemes by extensive *** results illustrate the importance of adaptive strategies in overcoming fading and interference which leads to an increase in system resilience as well as a robust communication link. Metrics for the outage probability and mean time to failure (MTTF) can inform how reliable systems are across operational scenarios. This work reconciles theory with practice to provide a systematic way of controlling the operational parameters in wireless networks under varying conditions. These lessons will be crucial in steering the design of forthcoming wireless systems that must more reliably satisfy a broader set of application requirements.

关键词： Fading channels Measurement Adaptive systems Wireless networks Interference Reliability theory Probability Throughput Resilience Signal to noise ratio

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Dynamic Resource Allocation and Security Strategies in Cooperative Relaying Systems with Eavesdropping Threats

Dynamic Resource Allocation and Security Strategies in Coope...

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International Symposium on Wireless Personal Multimedia Communications (WPMC)

作者： Deepak Upadhyay Kunj Bihari Sharma Abhay Upadhyay Mridul Gupta Nookala Venu Dept. of Computer Science and Engineering Graphic Era Hill University Dehradun India Dept. of Computer Science and Engineering Graphic Era deemed to be University Dehradun India Dept. of Electronics and Communication Engineering Graphic Era deemed to be University Dehradun India Centre for Internet of Things Madhav Institute of Technology & Science Deemed University Gwalior India

ISBN: (数字)9798350392319

ISBN: (纸本)9798350356137

The dynamic resource allocation and security strategies for cooperative relaying systems proposed here provide significant performance improvements along with robust security features over traditional methods. The method improves throughput, energy efficiency and secrecy capacity by dynamically provisioning resources according to real-time network conditions in conjunction with its interference-suppression techniques such adaptive beamforming and artificial noise. The system is quite good at preventing eavesdropping, and it has such high signal-to-noise ratios that there is a very low error rate. The use case results show that the integrated framework optimizes resource consumption while mitigating security threats, thereby offering a trade-off between existing solutions thus solving some of their shortcomings. Our work demonstrates the opportunity for efficient and secure communication in dynamic environments.

关键词： Wireless communication Error analysis Dynamic scheduling Throughput Real-time systems Security Resource management Multimedia communication Eavesdropping Signal to noise ratio

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Performance Enhancement and Secrecy Analysis of Hybrid RF/FSO Communication Links Under Combined κ-μ Fading and Exponential Turbulence Conditions 2

Performance Enhancement and Secrecy Analysis of Hybrid RF/FS...

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2nd International Conference on Computational Intelligence, Communication Technology and Networking, CICTN 2025

作者： Upadhyay, Deepak Prakhar Moray, Rashmy Sharma, Rashmi Venu, Nookala Shukla, Shipra Dept. of Computer Science and Engineering Graphic Era Hill University Dehradun India Department of CSE Roorkee Institute of Technology Pune India A constituent of Symbiosis International Deemed University India Nagpur Campus Pune India Centre for Internet of Things Madhav Institute of Technology & Science Deemed University Gwalior India G. L. Bajaj Institute of Technology and Management Greater Noida India

ISBN: (纸本)9798331530389

In this study, the secrecy performance evaluation of hybrid RF/FSO communication systems over κ-μ fading and exponential turbulence channels are conducted. We analyse the secure information rate and evaluate the throughput and secrecy capacity of the system through simulations. The results indicate that the proposed hybrid system improves reliability and security by combining adaptive modulation, beamforming, and encryption to combat interference and secure data transmission. Geographical heat maps help to visualize the influence of environmental factors on system performance. Federated learning in hybrid RF/FSO systems have been investigated in detail through simulations and numerical results to show the considerable improvements in communication reliability and performance that the increased redundancy and robustness of the hybrid scheme provides. This helps gain valuable insights into a better design of wireless networks in the future by highlighting the benefits of hybrid communication techniques and simulation-driven design to enhance performance and security across diverse complex environments and conditions. © 2025 IEEE.

关键词： Adaptive modulation

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