Engineering, Electrical and Electronic Engineering, Electrical and Electronic Engineering, Electrical and Electronic Engineering
4
Scopus Publications
1
Scholar Citations
1
Scholar h-index
Scopus Publications
Fractional Spectral Adaptive Filtering for Robust Compressive Sensing: Rational Discrete Fractional Transform-LMS Recovery and Air-Comp Application Pendyala V Muralidhar, B.Rama Rao, A. S. Srinivasa Rao, D.Nataraj, K S Chakradhar, M.Sivasankara Rao Proceedings of the 9th International Conference on Electronics Communication and Aerospace Technology Iceca 2025, 2025 Recent developments in over-the-air computation (Air-Comp) and wireless sensor networks (WSNs) have highlighted the increasing need for compressive sensing (CS) recovery algorithms that can operate dependably in real-world wireless settings. In contrast to ideal circumstances, noise and multipath affect real-world channels. The precision and stability of conventional recovery techniques are weakened by propagation, fading, and other factors. Under low-noise or noise-free conditions, classical algorithms like Orthogonal Matching Pursuit (OMP) and time-domain Least Mean Squares (LMS) show good recovery; however, when realistic impairments are introduced, their performance drastically deteriorates, resulting in slow, unstable, or suboptimal convergence. To address these limitations, the propose a robust, spectrum-adaptive CS recovery approach using the Least Mean Squares (LMS) algorithm in the Rational Discrete Fractional Transform (REDT) domain. The REDT provides a sparsity-enhancing transform framework that regularizes adaptive filtering, thereby suppressing additive noise and reducing spectral spreading caused by wireless channels. By transforming the CS recovery problem into the REDT domain, signals achieve sparser representations, which facilitate faster convergence, improved denoising, and greater robustness against channel fading. Comprehensive results, validated through error convergence and recovery plots, reveal that REDT-LMS consistently surpasses conventional LMS, achieving lower steady-state error and higher reconstruction accuracy. This demonstrates not only the theoretical suitability of REDT-domain adaptive filtering for compressive sensing recovery but also its practical efficiency for emerging applications in Air-Comp and distributed edge-based sensor networks. The proposed method offers a reproducible, open-source-supported framework, making it a viable solution for next-generation wireless sensing and communication systems.
Design of Wearable Patch Antenna Using Wireless Body Area Networks - Review M. Sivasankara Rao, M. Sandeep, D. Vanaja, D. Ramcharan Proceedings 2024 International Conference on Social and Sustainable Innovations in Technology and Engineering Sasi ITE 2024, 2024 Antennas are essential in wireless communication, serving as a link between digital devices and the vast networks that run our modern life. They are particularly crucial in wide area networks (WANs), which span large geographic areas. Antennas are designed to broadcast and receive signals across great distances while maintaining flawless connectivity. Wireless Body Area Networks (WBANs) have emerged as transformative technology in various applications, such as healthcare monitoring and sports performance analysis. The proposed idea focuses on designing and optimizing a wearable antenna specifically for WBANs, addressing the unique challenges of on-body communication. The system offers reliable wireless connectivity while considering size constraints, power efficiency and regulatory compliance. Key objectives include selecting the appropriate frequency band, choosing the right antenna type, optimizing antenna placement for user comfort and achieving precise impedance matching for efficient data transmission. The proposed idea uses electromagnetic simulation tools for design and construction of physical prototypes for real-world testing.
Bus Detection System for Blind Using Rfid with Prototypes for the Bus Stop and For the Bus MSSR Sasikanth K, Vinay Kumar G, Sudhakar K, Surya Y International Journal of Research 5 (12) , 2018 2018
Error minimization in Brain tissue extraction for T1 weighted MR images GLN Murthy, B Anuradha, M Siva, S Rao, KL Manassa IJIRCCE 3 (5) , 2015 2015 Citations: 1
MOST CITED SCHOLAR PUBLICATIONS
Error minimization in Brain tissue extraction for T1 weighted MR images GLN Murthy, B Anuradha, M Siva, S Rao, KL Manassa IJIRCCE 3 (5) , 2015 2015 Citations: 1
Descriptions of Different Privacy Methodologies in Spectrum analysis of MST Radar Data DSP Sivasankara Rao M JARDCS 12 (6), 963-972 , 2020 2020
Bus Detection System for Blind Using Rfid with Prototypes for the Bus Stop and For the Bus MSSR Sasikanth K, Vinay Kumar G, Sudhakar K, Surya Y International Journal of Research 5 (12) , 2018 2018
