Signal Processing Projects

Channel estimation for IRS-MIMO assisted communication system

This project aims at semi-blind channel estimation for the proposed system with reduced overhead pilots.
The classical Machine learning algorithm, Expectation Maximization is used for the estimation.
Various protocols are defined and the best protocol is presented along with the simulation results.

FTN-MIMO Signal Optimization for Wireless Communication

Conducted a comprehensive study on integrating Faster-than-Nyquist (FTN) signaling with MIMO technology to enhance bandwidth efficiency, demonstrating significant capacity gains through advanced mathematical modeling and Python simulations.
Analyzed and compared the performance of traditional and orthogonalized FTN-MIMO systems across various signal-to-noise ratios (SNRs), identifying key enhancements that could advance future wireless communications.

5-Band Equalizer Using Linear Phase FIR Filters (DSP)

• Developed a 5-band equalizer employing linear-phase FIR filters and dynamic range reduction strategies in MATLAB, optimizing filter lengths for enhanced control over specific frequency bands.

• Conducted detailed performance analyses through simulations, fine-tuning filter configurations to improve audio quality with advanced functionalities like gain control and pitch adjustment.