Device-To-Device Communication Projects for M.E, M.Tech, Masters, MS abroad, and PhD students. These Device-To-Device Communication ieee projects are implemented with future work and extension for final year project submission with research paper publishing. These research projects guide final year students to learn, practice, and complete their academic submissions successfully. Each project includes complete source code, project report, PPT, a tutorial, documentation, and a research paper.
Latest Device-To-Device Communication Projects
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Combining Lyapunov Optimization and Deep Reinforcement Learning for D2D Assisted Heterogeneous Collaborative Edge Caching
This project focuses on improving content sharing in wireless networks. Devices can share data directly with nearby devices or get it from a base station. The method uses smart learning to decide which devices should store and share content. It reduces delays, saves energy, and keeps the network running smoothly. -
Bee System-Based Self Configurable Optimized Resource Allocation Technique in Device-to- Device (D2D) Communication Networks
This project focuses on improving mobile network performance as traffic keeps growing. It uses a method inspired by how bees search for food to efficiently allocate resources between nearby devices. If the network is overloaded, extra resources and relay nodes are added to maintain good service. The approach improves user experience by reducing delay, saving energy, and supporting mobility. -
Reliability-Driven End–End–Edge Collaboration for Energy Minimization in Large-Scale Cyber-Physical Systems
This project focuses on making large-scale cyber-physical systems, like smart factories or connected devices, more energy-efficient and reliable. It studies how devices and edge computers can work together to handle tasks without wasting energy. The researchers created a method to group tasks, control them efficiently, and offload work smartly. Their approach reduced energy use by over 50% compared to other methods. -
An Energy-Efficient Deep Mutual Learning System Based on D2D-U Communications
This project focuses on helping mobile devices learn from each other without sharing private data. The system uses direct device-to-device communication over unlicensed spectrum. It finds the best way to pair devices and allocate communication resources to save energy. The results show that this method improves learning between devices. -
Optimizing D2D Communication With Practical STAR-RIS and Irregular Configurations
This project improves device-to-device wireless communication using smart surfaces that can send and reflect signals at the same time. It makes the system cheaper and able to cover more area by using simple signal controllers. The research also proposes turning on only some surface elements in a smart way to improve performance. Their method boosts both the communication speed and energy efficiency compared to existing systems. -
Reliability in Post-Disaster Networks A Novel Interference-Mitigation Strategy
This project studies how to keep mobile networks working well after a disaster. It looks at how active and inactive base stations affect signal quality for users. The study proposes a way to improve coverage and reliability by selectively silencing some base stations. The results show that this method can help users stay connected even in emergency situations.
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