MIMO Projects for M.E, M.Tech, Masters, MS abroad, and PhD students. These MIMO 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 MIMO Projects
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A Novel Three-Dimensional Direction-of-Arrival Estimation Approach Using a Deep Convolutional Neural Network
This project focuses on finding the direction from which signals come in a three-dimensional space. It uses a special type of artificial intelligence called a deep convolutional neural network to analyze data from a small antenna array. The system can accurately predict angles from any direction, even when multiple signals arrive at the same time. The goal is to make signal detection faster, precise, and reliable in different conditions. -
A Survey on Reconfigurable Intelligent Surface for Physical Layer ecurity of Next-Generation Wireless Communications
This project studies new ways to make future 6G wireless networks faster and more secure. It focuses on using special smart surfaces that can control signals to prevent eavesdropping. The research reviews different methods to improve security for various network types. It also discusses challenges and ideas for future wireless systems. -
Joint MIMO Communications and Sensing With Hybrid Beamforming Architecture and OFDM Waveform Optimization
This project studies a wireless system that can send data to users and sense the environment at the same time. It uses advanced 5G signals to communicate with multiple users while also detecting objects and their positions. The system carefully manages its signals to reduce interference and improve both communication and sensing accuracy. Simulations show it can detect targets reliably while still maintaining good data transmission. -
Multivariate Extreme Value Theory Based Channel Modeling for UltraReliable Communications
This project studies how to make 5G and future wireless networks extremely reliable. It focuses on rare, extreme drops in signal strength and models them for multiple channels at once. The researchers use advanced statistics to better predict these extreme events in MIMO systems. They test their method on real car data and show it predicts extreme cases more accurately than older methods.
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