Reconfigurable Intelligent Surface Projects for ME, MTech, Masters, MS abroad, and PhD students. These Reconfigurable Intelligent Surface ieee projects are implemented with future work and extension for final year students with research paper writing and 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 Reconfigurable Intelligent Surface Projects
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Latency-Aware Computation Offloading in Multi-RIS-Assisted Edge Networks
This project focuses on making mobile computing faster for devices like smartphones and IoT gadgets. It studies how to send tasks from devices to nearby powerful servers with less delay. The research uses special surfaces called RIS to improve wireless signals and chooses the best paths for data. The results show that using multiple RIS can reduce overall delays by up to 24%. -
A Generalized Delay and Backlog Analysis for Multiplexing URLLC and eMBB: Reconfigurable Intelligent Surfaces or Decode-and-Forward
This project studies how to improve communication networks that carry both urgent and high-data traffic. It looks at using smart surfaces and relay nodes to strengthen signals and create multiple paths. The research predicts delays and data backlogs using a new mathematical approach. Results show this method gives more accurate performance estimates than older techniques. -
A Simulation Framework for Cooperative Reconfigurable Intelligent Surface-Based Systems
This project studies how to improve wireless communication using multiple smart reflecting surfaces called RIS. It uses computer simulations to see how signals travel and change when they bounce off these surfaces. The study measures how often signals drop and how long outages last under different conditions. It shows that using several RIS together can make the connection more reliable than using just one. -
An Efficient Ray-Based Modeling Approach for Scattering From Reconfigurable Intelligent Surfaces
This project focuses on improving wireless communication using special surfaces called reconfigurable intelligent surfaces (RISs). These surfaces can control how signals bounce or pass through them. The researchers created a new method to simulate how signals interact with these surfaces quickly and accurately. Their method works well and gives results similar to existing complex techniques but is much faster. -
Energy Harvesting Maximization for Reconfigurable Intelligent Surfaces Using Amplitude Measurements
This project focuses on making a special surface, called a reconfigurable intelligent surface (RIS), work using energy it gathers from the environment instead of external power. The researchers developed methods that adjust the surface to capture the most energy using only simple power readings. They tested these methods in simulations and showed they perform better than random adjustments. The work helps RIS devices operate efficiently even in noisy or uncertain conditions. -
Fairness Enhancement of UAV Systems With Hybrid Active-Passive RIS
This project studies wireless communication using drones to connect with multiple users. It uses smart surfaces that can actively or passively reflect signals to improve coverage. The goal is to make the connection fair for all users by optimizing the drone’s path, signal direction, and surface settings. The results show that even a few active elements on the surface can greatly improve communication speed compared to fully passive surfaces. -
Going Beyond a Simple RIS Trends and Techniques Paving the Path of Future RIS
This project looks at improving future wireless networks, like 6G, which need very fast and reliable connections. High-frequency signals lose strength quickly and are easily blocked. The study explores reconfigurable intelligent surfaces (RIS) that can control how signals travel to boost coverage and speed. It also discusses how machine learning can make these systems smarter and more efficient. -
Joint RIS-Aided Precoding and Multislot Scheduling for Maximum User Admission in Smart Cities
This project focuses on improving wireless networks in smart cities using special surfaces called reconfigurable intelligent surfaces (RIS). These surfaces can control how signals travel, helping more users get better service. The study develops a method to schedule users and adjust signals efficiently, even when the system is complex. Tests show this approach serves more users and works well even when network information is slightly outdated. -
Optimal RIS Partitioning and Power Control for Bidirectional NOMA Networks
This project studies how special smart surfaces, called RIS, can improve wireless communication in NOMA networks. The method divides the surface to make signals stronger for users and removes the need for adjusting uplink power. It tests different scenarios to ensure good quality and fair data rates. Simulations show that using RIS greatly improves network performance. -
Performance Analysis of Randomly Distributed Reconfigurable Intelligent Surfaces With Different Phase Profiles
This project studies how smart surfaces placed on buildings and objects can improve wireless communication. It looks at real-world conditions instead of ideal assumptions. The work analyzes how to connect users to these surfaces and measures communication reliability. Simulations show how design choices affect performance. -
Rapidly Time-Varying Reconfigurable Intelligent Surfaces for Downlink Multiuser Transmissions
This project studies special surfaces called reconfigurable intelligent surfaces (RISs) that can control wireless signals in real time. By changing their properties quickly, these surfaces can improve network performance, balance user fairness, and boost data rates. The work shows how fast or slow adjustments affect communication depending on the available information about the channels. It provides guidelines for designing RISs to make wireless networks more efficient.
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