@karunya.edu
Professor ,Department of electronics and communication Engineering
Karunya Institute of Technology and Sciences
BE. ME, Ph.D
Antenna design, Wireless sensor networks, RF design
Scopus Publications
Scholar Citations
Scholar h-index
Scholar i10-index
Rayudu Bharath Kumar, Moses Nesasudha, and Doondi Kumar Janapala
Springer Science and Business Media LLC
Krishnasamy Vijaipriya, Nesasudha Moses, and Prawin Angel Michael
King Mongkut's University of Technology North Bangkok
Therefore, in today’s wireless communication systems and in particular, the Multi-User-Multiple Input Multiple Output-Orthogonal Frequency Division Multiplexing (MU-MIMO-OFDM) systems, channel estimation, the detection, and mitigation of the attack are important to ensure the safe operation of a system. Current approaches use distinct procedures for completing these jobs, and this causes high computational expenses, longer response times, and decreased performance of the system. In this work, a multi-task learning (MTL) framework is introduced to develop a new end-to-end deep learning solution of an Amalgamated Convolutional Neural Network (ACNN) for spatial feature extraction and a Bidirectional Long Short-Term Memory (Bi-LSTM) for temporal attack detection. The proposed system is effective in handling these tasks together because that would mean maximum efficiency and accuracy. To enhance the model’s efficiency, a Green Anaconda Optimization (GAO) algorithm is used to solve the multi-task loss function and enhance convergence rate and solution quality. The presented GAO approach provides a good balance between channel estimation, attack detection, and mitigation since GAO adapts the model parameters in the training process. Most of the current methods give slow convergence rates, and high computational costs, and are not very suitable for scale-up, especially in dynamic systems. These limitations make them unadoptable for real-time operations and analysis. The challenges described above are addressed by the proposed hybrid model with GAO, which is therefore ideal for modern secure wireless communication systems due to the reduced computational overhead and faster response time. The model reaches a first-level accuracy of 99% and costs 70 GFLOPs and 35 ms latency.
D. Durga Prasad, Nesasudha Moses, and Doondi Kumar Janapala
Springer Nature Switzerland
Mulagala Dileep, Nesasudha Moses, and Doondi Kumar Janapala
Springer Nature Switzerland
K. Vijaipriya, M. Nesasudha, and Prawin Angel Michael
Elsevier BV
Deepthy Grace Sudarsanan, Nesasudha Moses, and Karthikeyan Thavittupalayam Angappan
King Mongkut's University of Technology North Bangkok
PDMS is frequently utilized in the biomedical field because of its biocompatibility. The PDMS finds applications in medical implants, cardiovascular flow replication, and in the biomedical industry. This paper presents an innovative antenna design optimized for biomedical applications operating in the Industrial, Scientific, and Medical (ISM) band (2.4–2.5 GHz). The proposed antenna features a compact, flexible structure utilizing a Polydimethylsiloxane (PDMS) substrate to prioritize patient safety and comfort. For PDMS, the loss tangent is 0.0134 and the dielectric constant is 2.71. The design process employs parametric optimization to achieve a low-profile configuration with a wide impedance bandwidth and better radiation characteristics. Simulations and experimental validation using a multi-layered tissue phantom demonstrate superior performance, achieving a return loss below -10 dB across the ISM band. Additionally, Specific Absorption Rate (SAR) measurements confirm compliance with international safety standards, ensuring minimal electromagnetic exposure. PDMS-based flexible antennas hold promise for biomedical applications, but many existing designs face challenges related to limited gain, narrow bandwidth, and poor mechanical stability under continuous body movement. This highlights the need for more reliable and adaptable antenna solutions for on-body use. This study underscores the potential of the proposed ISM-band antenna to enhance the functionality and efficiency of biomedical communication systems, driving advancements in telemedicine and personalized healthcare solutions.
B. Anitha Vijayalakshmi, S. Lekashri, M. Gomathi, R. Ashwini, B. Arunsundar, and M. Nesasudha
Springer Science and Business Media LLC
J. Vijitha Ananthi, P. Subha Hency Jose, and M. Nesasudha
Springer Science and Business Media LLC
Rama Krishna Chokkakula, Nesasudha Moses, and Doondi Kumar Janapala
IEEE
K. Vijaipriya, M. Nesasudha, and Prawin Angel Michael
Wiley
ABSTRACTIn general, Multi‐User Multiple Input Multiple Output Orthogonal Frequency Division Multiplexing (MU‐MIMO‐OFDM) enables multiple users to simultaneously communicate with a single base station using multiple antennas and OFDM modulation. Nevertheless, resource allocation challenges such as power management and delay optimization arise within MU‐MIMO‐OFDM systems, requiring sophisticated solutions to ensure efficient use of resources and optimal system performance. Thus, joint power and delay optimization‐based resource allocation using a Deep Convolutional Pyramid‐Dilated Neural Network (DCPDNN) with Red piranha optimization and Optimal Delay Scheduling conflict graphs Algorithm (DCPDNN‐RPO‐ODSCGA) in MU‐MIMO‐OFDM system is proposed in this presented research. The proposed mechanism is performed in two stages: power allocation and delay optimization. In the first stage, through a Deep Convolutional Pyramid‐Dilated Neural Network (DCPDNN), which aims to maximize throughput, the network resources are distributed to user equipment (UEs) based on power and transmission rate. To reduce the loss function, Red Piranha Optimization (RPO) is proposed to optimize the layers of DCPDNN. In the second stage, the Optimal Delay Scheduling conflict graphs Algorithm (ODSCGA) is proposed for the optimizing delay in the MU‐MIMO‐OFDM system. The multiracial envelope procedure and service curve for traffic flows in the uplink transmission are used in the ODSCGA approach to estimate the delay‐bound value. Ideas like the maximal weight independent set and optimal conflict graph are also utilized. The simulations of DCPDNN‐RPO‐ODSCGA were conducted using MATLAB software. Thus, the proposed approach has attained higher spectral capacity, higher fairness index, and increased cumulative distribution function (CDF), 29.74%, 32.98%, and 16.46% lower loss rate, 28.05%, 24.09%, and 17.45% improved energy efficiency, 15.09%, 13.78%, and 12.05% lower processing time than other conventional approaches like MPQM‐SCA, Hyb‐BF‐DSA, and SIA‐FDBD methods, respectively.
R. Catherine Shekinah, P. Beulah Jenifer, K. Indhurani, M. Nesasudha, and T. A. Karthikeyan
Springer Nature Singapore
T. A. Karthikeyan, M. Nesasudha, and M. L. Valarmathi
Springer Science and Business Media LLC
J. Vijitha Ananthi, P. Subha Hency Jose, and M. Nesasudha
Elsevier BV
Karthikeyan T. Angappan, Moses Nesasudha, Moses Abi T. Zerith, and Agbotiname Lucky Imoize
Walter de Gruyter GmbH
Abstract A Polydimethylsiloxane (PDMS) based antenna is designed for skin tumor detection. The antenna functions at 2.45 GHz with a bandwidth of 2.30–2.64 GHz working in the ISM (Industrial, Scientific, and Medical) band. The size of the antenna is 40 × 40 × 1 mm3. This antenna detects tumors in the skin by considering the variations in values of the E-field, J-surf, and H-field. Various analyses such as the distance between the patch and stacked layer skin phantom for different tumor sizes and input power to the antenna are changed and antenna performance is observed. A significant amount of changes is attained which denotes the presence of the tumor. The proposed antenna is fabricated and the corresponding results are analyzed in the Anechoic Chamber. The antenna has an efficiency of 99 % with a Specific Absorption Rate of 1.3846 W/kg which is lower than 1.6 W/kg as per the recommendations of FCC standard.
B. Anitha Vijayalakshmi, B. Arunsundar, C. Tamizhselvan, and M. Nesasudha
Springer Science and Business Media LLC
T A Karthikeyan, M Nesasudha, S Saranya, and B Sharmila
Elsevier BV
B. Anitha Vijayalakshmi, S. Lekashri, R. Mary Victoria, M. Gomathi, and M. Nesasudha
Springer Science and Business Media LLC
B. Anitha Vijayalakshmi, A. Senthil Kumar, V. Kavitha, and M. Nesasudha
Springer Science and Business Media LLC
T. A. Karthikeyan, M. Nesasudha, and G. Shine Let
Springer Science and Business Media LLC
B. Anitha Vijayalakshmi, P. Gandhimathi, and M. Nesasudha
Springer Science and Business Media LLC
Doondi Kumar Janapala, Nesasudha Moses, and Jebasingh Bhagavathsingh
Cambridge University Press (CUP)
Abstract This research work presents an implantable antenna that operates at 5.8 GHz. By using a radiator with a loop-based design, the antenna can be made smaller. Radiator is made up of three connected rectangular loops. On the substrate’s back side, an I-shaped ground plane is used. As substrate and superstrate, polydimethylsiloxane (PDMS) with dimensions of 7 mm × 5 mm × 0.3 mm is used. The conducting sections are made using copper foil that is 30 µm thick. The suggested antenna is examined by the implantable medical device using realistic human scalp phantom models and a homogenous skin box. Simulated study revealed that it operates around 5.8 GHz with a bandwidth from 5.69 to 5.92 GHz. The specific absorption rate was 0.28 and 0.26 W/kg for skin box and human scalp phantoms, respectively, at 1 mW input power across 1 g volume tissue.
B. Anitha Vijayalakshmi, K. Gokulkannan, S. Sri Nandhini Kowsalya, R. Mary Victoria, and M. Nesasudha
Springer Science and Business Media LLC
RB Kumar, M Nesasudha, DK Janapala
Sensing and Imaging 27 (1), 100 , 2026
2026
J Bhagavathsingh, S Abraham, M Nesasudha, DK Janapala
Scientific Reports , 2026
2026
BA Vijayalakshmi, S Lekashri, M Gomathi, R Ashwini, B Arunsundar, ...
Journal of Optics 54 (4), 2187-2196 , 2025
2025
Citations: 12
GS Deepthy, M Nesasudha, TA Karthikeyan
Mechanics of Advanced Composite Structures 12 (Special Issue 2: Mechanics of … , 2025
2025
Citations: 1
JV Ananthi, PSH Jose, M Nesasudha
National Academy Science Letters 48 (3), 309-312 , 2025
2025
Citations: 1
TA Karthikeyan, M Nesasudha, ML Valarmathi
Journal of Materials Science: Materials in Electronics 35 (35), 2226 , 2024
2024
Citations: 4
JV Ananthi, PSH Jose, M Nesasudha
Computers and Electrical Engineering 120, 109665 , 2024
2024
Citations: 3
KT Angappan, M Nesasudha, MAT Zerith, AL Imoize
Frequenz 78 (9-10), 433-453 , 2024
2024
Citations: 2
BA Vijayalakshmi, K Gokulkannan, SSN Kowsalya, RM Victoria, ...
Journal of Optics, 1-8 , 2024
2024
Citations: 5
B Anitha Vijayalakshmi, B Arunsundar, C Tamizhselvan, M Nesasudha
Wireless Personal Communications 138 (4), 2733-2746 , 2024
2024
Citations: 5
M Nesasudha, TA Karthikeyan
2024 5th International Conference on Smart Sensors and Application (ICSSA), 1-6 , 2024
2024
Citations: 5
TA Karthikeyan, M Nesasudha, S Saranya, B Sharmila
Journal of Industrial Information Integration 41, 100673 , 2024
2024
Citations: 21
B Anitha Vijayalakshmi, S Lekashri, R Mary Victoria, M Gomathi, ...
Journal of Optics 53 (4), 3434-3440 , 2024
2024
Citations: 3
BA Vijayalakshmi, AS Kumar, V Kavitha, M Nesasudha
Journal of Optics 53 (3), 2428-2434 , 2024
2024
Citations: 6
TA Karthikeyan, M Nesasudha, GS Let
Plasmonics 19 (3), 1499-1515 , 2024
2024
Citations: 8
R Catherine Shekinah, P Beulah Jenifer, K Indhurani, M Nesasudha, ...
International Conference on Intelligent Communication, Control and Devices … , 2024
2024
BA Vijayalakshmi, P Gandhimathi, M Nesasudha
Journal of Optics 53 (2), 933-939 , 2024
2024
Citations: 12
BA Vijayalakshmi, B Arunsundar, A Gopalan, P Gandhimathi, V Kavitha, ...
Journal of Optics 52 (3), 1399-1404 , 2023
2023
Citations: 3
GS Deepthy, M Nesasudha
2023 Second International Conference on Electrical, Electronics, Information … , 2023
2023
Citations: 2
GS Let, M Nesasudha, NM Sivamangai, SSS Priya
Computer Aided Constellation Management and Communication Satellites … , 2023
2023
Citations: 2
MN Sudha, ML Valarmathi, AS Babu
Computers and Electronics in Agriculture 78 (2), 215-221 , 2011
2011
Citations: 101
DK Janapala, M Nesasudha, T Mary Neebha, R Kumar
Wireless Personal Communications 122 (4), 3467-3483 , 2022
2022
Citations: 37
DK Janapala, M Nesasudha, TM Neebha, R Kumar
International Journal of RF and Microwave Computer‐Aided Engineering 29 (9 … , 2019
2019
Citations: 34
M Nesasudha
2020 5th International Conference on Devices, Circuits and Systems (ICDCS … , 2020
2020
Citations: 23
TA Karthikeyan, M Nesasudha, S Saranya, B Sharmila
Journal of Industrial Information Integration 41, 100673 , 2024
2024
Citations: 21
TM Neebha, M Nesasudha
Engineering science and technology, an international journal 21 (5), 938-944 , 2018
2018
Citations: 20
M Nesasudha
Health and Technology 11 (6), 1191-1204 , 2021
2021
Citations: 19
TM Neebha, M Nesasudha
2017 First International Conference on Recent Advances in Aerospace … , 2017
2017
Citations: 18
TM Neebha, M Nesasudha, DK Janapala
Computers in Biology and Medicine 116, 103578 , 2020
2020
Citations: 16
VP Ajay, M Nesasudha
Intelligent Automation & Soft Computing 34 (1) , 2022
2022
Citations: 15
N Sudha, ML Valarmathi, TC Neyandar
Proceeding of IJCA on International Conference on VLSI, Communications and … , 2011
2011
Citations: 15
R Orugu, M Nesasudha, DK Janapala
2021 International Conference on Computer Communication and Informatics … , 2021
2021
Citations: 14
DK Janapala, M Nesasudha, TM Neebha, R Kumar
2019 IEEE 1st International Conference on Energy, Systems and Information … , 2019
2019
Citations: 14
BA Vijayalakshmi, M Nesasudha
Optical and Quantum Electronics 53 (9), 489 , 2021
2021
Citations: 13
BA Vijayalakshmi, S Lekashri, M Gomathi, R Ashwini, B Arunsundar, ...
Journal of Optics 54 (4), 2187-2196 , 2025
2025
Citations: 12
BA Vijayalakshmi, P Gandhimathi, M Nesasudha
Journal of Optics 53 (2), 933-939 , 2024
2024
Citations: 12
BA Vijayalakshmi, M Nesasudha
Optical & Quantum Electronics 52 (2) , 2020
2020
Citations: 12
MN Sudha, SJ Benitta
Intelligent Decision Technologies 10 (4), 365-371 , 2016
2016
Citations: 12
MN Sudha, ML Valarmathi, G Rajsekar, MK Mathew, N Dineshraj, ...
Wireless Sensor Network 1 (4), 350 , 2009
2009
Citations: 12
BA Vijayalakshmi, M Nesasudha
Optical and Quantum Electronics 52 (12), 518 , 2020
2020
Citations: 10