Communication Network Final Year Projects with Source Code

Byadmin Final Year Projects

Communication Network Final Year Projects for BE, BTech, ME, MSc, MCA and MTech final year engineering students. These Communication Network projects give practical experience and help complete final-year submissions. All projects follow IEEE standards and each project includes source code, project thesis report, presentation, project execution and explanation.

Communication Network Final Year Projects

  1. Opportunistic Backscatter Communication Protocol Underlying Energy Harvesting IoT Networks
    This project focuses on improving communication in Internet of Things (IoT) networks where devices can send data without batteries using backscatter technology. It introduces a new method that helps these devices share wireless signals more smoothly and efficiently while also harvesting energy from the network. The method reduces data collisions and increases overall network speed and energy use. Compared to older approaches, it makes IoT networks faster and more energy-efficient.
  2. A Fresh Look at Routing Protocols in Unmanned Aerial Vehicular Networks A Survey
    This project studies how drones communicate with each other while moving in the air. It explains why choosing the best path for sending data is difficult because drone networks change quickly. The work compares different new routing methods and shows how well they perform. It also highlights remaining challenges and areas for future research in drone communication.
  3. A Survey of Resource Management in D2D Communication for B5G Networks
    This project studies a new type of wireless communication called Device-to-Device (D2D) for future networks beyond 5G. D2D allows nearby devices to connect directly without relying on a base station. The goal is to increase data speed, network coverage, and energy efficiency while reducing delays. The study reviews current challenges, like interference and security, and suggests ways to improve D2D communication in upcoming networks.
  4. An Online Learning Approach to Shortest Path and Backpressure Routing in Wireless Networks
    This project focuses on improving data transmission in wireless networks where the quality of connections is uncertain and changes over time. It develops a smart algorithm called OLSB that learns which paths are best for sending data while keeping costs low. The algorithm adapts automatically, improving network efficiency without knowing all connection details in advance. Simulations show that OLSB performs very well and closely matches the best possible routing strategy.
  5. Decentralized Federated Learning Over Slotted ALOHA Wireless Mesh Networking
    This project studies a way to train machine learning models without a central server, using devices that share updates with their neighbors. It focuses on keeping data private while still achieving high accuracy. The system is tested on the MNIST image dataset using a CNN model, and it shows over 95% accuracy. The method also reduces communication costs and trains faster compared to traditional centralized systems.
  6. Intelligent Driver Model-Based Vehicular Ad Hoc Network Communication in Real-Time Using 5G New Radio Wireless Networks
    This project focuses on improving communication between vehicles using 5G networks. It creates smart models for lane changes and accident avoidance to make vehicle movements more accurate and safe. The system is tested in different road shapes, and simulations show that vehicles communicate better and respond faster using 5G. Overall, it enhances traffic safety and efficiency through advanced vehicle-to-vehicle communication.
  7. ML-RPL Machine Learning-Based Routing Protocol for Wireless Smart Grid Networks
    This project uses machine learning to make wireless smart grid networks work better. It improves an existing routing protocol by predicting the best path for data to travel. The system helps data reach its destination more reliably and quickly. Tests show it delivers more packets with less delay, making the network more efficient.
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Communication Network Project Synopsis & Presentation

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Communication Network Project Thesis Writing

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