SUPRAJA C

@google.com

Assistant Professor
Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology,

SUPRAJA C


               Download Compact PDF  
https://researchid.co/suprajac
16

Scopus Publications

59

Scholar Citations

3

Scholar h-index

1

Scholar i10-index

Scopus Publications

  • CitZO-SVM: Machine Learning-Based Spectrum Sensing and Channel Allocation for Cognitive Radio Networks
    Supraja C, Kavitha Thandapani
    International Journal of Communication Systems, 2025
    In the fifth generation (5G) network, the cognitive radio network (CRN) is emerging as a solution for spectrum utilization by considering minimal spectrum usage. It is used with efficient spectrum sensing information and optimal channel assignment algorithms to optimize secondary user throughput. In this paper, a chaotic iterative zebra optimization‐based support vector machine (CitZO‐SVM) is proposed with the objective of improving the accuracy and reducing the complexity in CRN. To improve the sensing performance, the regularization parameters of SVM are optimized using the CitZO algorithm. The CitZO algorithm is modeled by integrating the chaotic iterative mapping and conventional Zebra optimization algorithm. Then, the channel assignment is employed optimally based on cooperative game theory by considering the utility factor and energy efficiency. Low complexity spectrum sensing and channel assignment algorithm are developed with less computational cost. The effectiveness of the proposed approach is verified through simulation results. The performance of the proposed approach is evaluated with 2.4 and 24 GHz bandwidth. The proposed technique achieves the throughput and the probability of 92.04 and 0.969 for 2.4 GHz frequency. The proposed methodology results in efficient spectrum utilization when compared to the existing channel assignment schemes.
  • 5G network based spectrum analysis for mm-wave and sub 6 GHz
    C. Supraja, T. Kavitha
    A Study on Next Generation Materials and Devicesv, 2025
    In this paper, MIMO and beam forming are important technologies for expanding the capacity of 5G and future networks. 5G can enable new services like remote control infrastructure, automobiles, and medical activities, which can alter industries with ultrareliable, available, low-latency communications.5G consists of low range frequency and high range frequency that is Low band and Mid band. The low frequency or low bands will range up to 1GHz to 6GHz and high frequency or high band will range from 24GHz to 40GHz. Massive Multiple-Input Multiple-Output (MIMO), which was originally designed for sub-6 GHz frequencies, is now also suitable for millimeter wave frequencies in the range of 30–300 GHz. The MIMO technology enhances the user’s throughput and capacity. The work represents comparing the sub-6 GHz and mm wave range frequencies, with the various beam-forming techniques. Based on these two frequencies the users capacity, spectrum efficiency and number of antennas are analyzed. The beam forming and Massive MIMO are the technique used for improving the parameters in 5G.The different types of beam forming and different bands are used to generate 5G signals for communication, where the number of users improved and good coverage of signals was identified. MIMO enables advanced beam-forming techniques, which help mm wave frequencies overcome higher path loss and susceptibility. The mm wave consists of a small wavelength, which allows a higher number of antennas, which are packed in a small area, so more data will be transferred simultaneously. Overall, the MIMO technique will help mm-wave signals achieve improved transmission rates, spectrum efficiency, signal quality, and reduced interference.
  • A hybrid binary logical regression -gradient decent approach for dynamic cooperative spectrum sensing in CRN
    Supraja C, Kavitha Thandapani
    International Journal of Electronics, 2025
  • 5G Based Millimeter Wave Spectrum Sensing for Cellular Networks
    Supraja C, Kavitha T
    Proceedings of the International Conference on Multi Agent Systems for Collaborative Intelligence Icmsci 2025, 2025
    Spectrum is availed extensively in modern civilization. The frequency is commonly referred to as intangible radio frequency. The frequency of the Invisible Radio is used to transmit wireless signals. The allocation and sensing for a spectrum in AM and FM base stations mostly takes place in the region of the electromagnetic spectrum. An intelligent radio can efficiently handle this spectrum sensing, allocation, which can assist to reduce spectrum shortages (Cognitive radio). Spectrum is distributed via the cognitive radio technology to both licensed and unlicensed users. The spectrum is allocated dynamically, and as a result of this tactic, spectrum usage will rise. The wireless sensor is made up of hundreds of wireless nodes placed within a specific radius for spectrum allocation and sensing. The most modern spectrum sensing techniques employed in cognitive radio networks will be Covered. The Two step Energy Detection Algorithm is used for spectrum Sensing which produces high efficiency. In Particular, the work shows the better Coverage area by estimating distance, SNR,False Alarm Probability, Detection Probability etc
  • AR/VR-based object detection for blind people using 5G communication
    C. Supraja, T. Kavitha
    Machine Learning for Radio Resource Management and Optimization in 5g and Beyond, 2025
    Augmented reality (AR) and virtual reality (VR) have transformed health care by focusing on the benefits of individuals with disabilities. The AR/VR technology demonstrates how well it is used in the health care department for people with disability. This technology helps blind people identify objects with the help of voice control, which makes the work easier and smoother for them. Existing studies like Microsoft Lens, Accuvein, Touch Surgery, and Vuzix M400 are not very focused on the individual disabilities of people like the blind, deaf, and dumb. The main objective of this work is to develop an AR, VR, or MR-based model used by blind people to identify objects with a voice command using 5G technology. 5G technology plays a vital role in the field of AR/VR health care. It uses millimeter-wave frequency for operating, which provides high speed and less delay. The device will work in both offline and online modes. In online mode, the data will be stored in the cloud. In offline mode, Smart Glass might have internal storage to save data temporarily. By using this technique, blind people will be provided with smart vision glasses, which will make their lives simpler, smarter, and more protective. This chapter describes how smart vision glasses, NuEyes Pro, Envision, and Microsoft Hololens 2 technologies can be used for people with disability and guide them using voice control with the help of machine learning and AI technology using 5G. The Smart Vision Glass will capture the image and analyze it using a HOG algorithm for object detection. 5G technology plays an immense role in delivering high-speed data with low latency. The microphone is placed in a smart vision glass to recognize the audio of blind people using voice recognition software. After that, it is given to the national language processing algorithm to understand the language. As a final step, a virtual assistant will come into play, where numerous machine learning algorithms are used to provide a wide range of functionalities such as automatic speech recognition, internet recognition, diary management, machine translation, personalization, and reinforcement learning. The framework will show promising output for people with disability in the health care system. This framework will be very useful for people who are visually challenged or people with hearing impairment. It can be extended in the future by implementing a deep neural network and a larger number of parameters like motion sensors, head tracking, and the blue-eye technology concept for people with visual impairment.
  • New Radio User Equipment for Positioning Accuracy Enhancement using AI
    Kavitha Thandapani, A. Arulmary, B. Manimaran, N. Ashok Kumar, Supraja C, Murugan C
    Proceedings of 7th International Conference on Inventive Material Science and Applications Icima 2025, 2025
    Positioning accuracy is crucial for New Radio (NR) User Equipment (UE) in various applications, including navigation, emergency response, and IoT-enabled services. However, environmental factors such as multipath propagation and non-line-of-sight (NLOS) conditions in urban and indoor environments often degrade the positioning accuracy of NR systems. To address these challenges, this paper presents an AI-based approach for enhancing NR UE positioning accuracy. The proposed method leverages a neural network model trained on noisy NR positioning data to predict corrected positions, mitigating the impact of common errors in real-world scenarios like complex and dynamic environments. By implementing machine learning models for signal fingerprinting, sensor fusion, beam fusion, beam prediction and mobility estimation, but in proposed system intelligently adapts to varying channel conditions and user contexts. Simulated data with line-of-sight (LOS) and NLOS conditions are used to test the model's performance, demonstrating a significant improvement in positioning accuracy compared to conventional methods. Results indicate that the AI-driven model significantly mitigates positioning error, thereby enhancing the reliability and precision of NR UE positioning. This innovative solution harbors promising applications in 5G and beyond, contributing to the evolution of accurate, AI-enabled location-based services.
  • Video Transmission Using Wireless Optical Communication in Underwater
    Kavitha Thandapandi, Supraja C, Murugan C, Arulmary A, M. Krishnamurthy, N. Ashokkumar
    5th International Conference on Sustainable Communication Networks and Application Icscna 2024 Proceedings, 2024
    The Optical wireless underwater video transmission represents a novel approach in wireless communication, driven by the need for high speed, reliable data transfer in underwater environments. The work explores the challenges inherent in underwater video transmission and gives solution for leaveraging wireless optical communication(WOC). The Severe underwater Environment characterized by high signal attenuation, Scattering, and absorption, poses significant limitations for conventional radio frequency- based communication systems. To Obtain solutions for these challenges, Specialized underwater transmitter and receivers are designed and implemented using Python and Arudino Platforms. The components faciliate effective signal propagation by optimizing the optical transmission process, which ensure minimal loss and enhanced reliability. The Integration of advanced optical Components allows the system to achieve higher data rates and robust video transmission, even under the unique Constraints imposed by aquatic mediums. The proposed system is designed to improve the overall efficiency of underwater communication which focusing on overcoming physical and technological barriers. The video comprehensive transmission framework, the work demonstrates potential applications in underwater monitoring. The research not only contributes to the growing field of underwater communication technologies but also paves the way for innovative solutions in marine research, environmental monitoring, and underwater exploration, addressing the critical demand for reliable, high-quality data transfer in challenging underwater environments.
  • Design of Auto Encoder based on DNN for MIMO Systems
    T. Kavitha, J. Jaswanth, M. Manoj Kumar, Supraja C, N. Ashokkumar, Narayana Reddy Yatm
    2024 3rd International Conference on Electrical Electronics Information and Communication Technologies Iceeict 2024, 2024
    In recent years, multiple-input multiple-output (MIMO) systems have gained significant attention in wireless communication due to their ability to enhance spectral efficiency and reliability. Designing efficient signal processing techniques for MIMO systems is crucial for achieving high data rates and reliable communication. In this paper, we propose a novel approach utilizing autoencoder-based deep neural networks (DNNs) for signal processing in MIMO systems. The autoencoder is a type of neural network that learns to encode input data into a lower- dimensional representation and then decode it back to its original form. By leveraging the inherent dimensionality reduction capabilities of autoencoders, we aim to efficiently capture the spatial characteristics of MIMO channels and mitigate the effects of channel impairments. First, we present the architecture of the proposed autoencoder-based DNN tailored for MIMO systems. The input to the network consists of received signals from multiple antennas, and the output is the estimated transmitted symbols. We design the network layers to perform feature extraction, channel estimation, and symbol detection jointly. Furthermore, we investigate the training methodology for the proposed DNN. We employ a combination of supervised learning with labeled data and unsupervised learning to exploit the abundance of unlabeled data typically available in MIMO systems. We discuss the challenges associated with training deep networks for MIMO channels, including data preprocessing, network initialization, and optimization techniques. To evaluate the performance of the proposed approach, extensive simulations are conducted using realistic channel models and various system configurations. We compare the proposed autoencoder-based DNN with conventional MIMO detection techniques, such as maximum likelihood detection and linear precoding. Performance metrics such as bit error rate (BER) and spectral efficiency are used to assess the effectiveness of the proposed method under different channel conditions and signal-to-noise ratios. The simulation results demonstrate that the autoencoder-based DNN offers significant performance gains over conventional techniques, particularly in scenarios with high channel correlation and nonlinearities. Moreover, the proposed approach exhibits robustness to channel estimation errors and outperforms existing deep learning-based methods for MIMO systems. In conclusion, this paper presents a promising framework for leveraging autoencoder-based DNNs in MIMO systems, offering improved performance and flexibility in signal processing tasks. The proposed approach opens up new avenues for further research in applying deep learning techniques to enhance the efficiency and reliability of wireless communication systems.
  • Wearable Brain Computer Interfaces (BCI) in Fog Computing using Wireless Technology
    S Kumari, P Shiny Sherlee, A Shafinian Aro, C Supraja
    Proceedings of the 7th International Conference on Intelligent Computing and Control Systems Iciccs 2023, 2023
    The overall dominance of various wave patterns and electrical activity across time is used to assess EEG brain waves. This kind of brain computer (BCI) interface enables, however, considerably limits the human’s freedom to communicate with machines. This computer-aided device collects brain inputs, analyses beta waves, and converts them. The function of this system is followed by Node-red and fog computing through the values that are crafted for output signals. The potential to observe physiological actions exhibited in brain waves which are transmitted online live into beta wave signals and monitored from tablets and televisions is accomplished by using non-invasive sensors.
  • A Smart and Precision Agriculture System Using DHT11 Plus FPGA
    R. Jenila, C. Kanmani Pappa, C. Supraja
    Smart Innovation Systems and Technologies, 2022
  • Design of 32 Channel Wavelength Division Multiplexing Optical Communication System
    C. Supraja, T. Kavitha, C. Kanmani Pappa
    IEEE International Conference on Knowledge Engineering and Communication Systems Ickes 2022, 2022
  • Design of High Performance Parallel Multiplication using FPGA
    Jenila R, Supraja C, Dharani N, Dinesh Kumar V
    Proceedings of 2022 IEEE International Conference on Current Development in Engineering and Technology Ccet 2022, 2022
  • Design of Elliptical to Circular Dielectric Resonator Antenna for Microwave Imaging Application
    V. Ramkumar, Supraja C, V. Chinnammal, Rahul Krishnan, L. Saravanan, J.Joselin Jeya Sheela
    3rd International Conference on Power Energy Control and Transmission Systems Icpects 2022 Proceedings, 2022
  • An Innovative Sensing Machine Learning Technique to Detect Credit Card Frauds in Wireless Communications
    G. Sasikala, M. Laavanya, B. Sathyasri, C. Supraja, V. Mahalakshmi, S. S. Sreeja Mole, Jaison Mulerikkal, S. Chidambaranathan, C. Arvind, K. Srihari, Minilu Dejene
    Wireless Communications and Mobile Computing, 2022
  • VLSI implementation of error detection and correction codes for space engineering
    R. Jenila, C. Supraja, C. Kanmani Pappa, N. Dharani
    Proceedings of the 3rd International Conference on Intelligent Communication Technologies and Virtual Mobile Networks Icicv 2021, 2021
  • Automated secern robot
    P. Santosh Reddy, Ch. Praveena Kumari, Ch. Sai Supraja, K. Prabhakara Rao
    Proceedings International Conference on Trends in Electronics and Informatics Icei 2017, 2017

RECENT SCHOLAR PUBLICATIONS

  • 5G network based spectrum analysis for mm-wave and sub 6 GHz
    C Supraja, T Kavitha
    A Study on Next-Generation Materials and Devices, 261-266 , 2025
    2025
  • A hybrid binary logical regression-gradient decent approach for dynamic cooperative spectrum sensing in CRN
    K Thandapani
    International Journal of Electronics 112 (9), 1898-1920 , 2025
    2025
  • New Radio User Equipment for Positioning Accuracy Enhancement using AI
    K Thandapani, A Arulmary, B Manimaran, NA Kumar, S C, M C
    2025 7th International Conference on Inventive Material Science and … , 2025
    2025
  • Automatic Anti Collision System For Intelligent Transportation System
    C Supraja
    Proceedings of the International Conference on Advanced Research in … , 2025
    2025
    Citations: 1
  • Next Generation Optical SDM Communication System using Artificial Intelligence
    C Supraja, C Murugan
    Proceedings of the International Conference on Advanced Research in … , 2025
    2025
  • CitZO-SVM: machine learning-based spectrum sensing and channel allocation for cognitive radio networks
    C Supraja, K Thandapani
    INTERNATIONAL JOURNAL OF COMMUNICATION SYSTEMS 38 (7) , 2025
    2025
    Citations: 2
  • AR/VR-based object
    C Supraja, T Kavitha
    Machine Learning for Radio Resource Management and Optimization in 5G and … , 2025
    2025
  • AR/VR-based object detection for blind people using 5G communication
    C Supraja, T Kavitha
    Machine learning for radio resource management and optimization in 5G and … , 2025
    2025
    Citations: 2
  • 5G Based Millimeter Wave Spectrum Sensing for Cellular Networks
    C Supraja, T Kavitha
    2025 International Conference on Multi-Agent Systems for Collaborative … , 2025
    2025
  • Video Transmission Using Wireless Optical Communication in Underwater
    K Thandapandi, C Supraja, C Murugan, A Arulmary, M Krishnamurthy, ...
    2024 International Conference on Sustainable Communication Networks and … , 2024
    2024
  • Design of Auto Encoder based on DNN for MIMO Systems
    T Kavitha, J Jaswanth, MM Kumar, N Ashokkumar, NR Yatm
    2024 Third International Conference on Electrical, Electronics, Information … , 2024
    2024
    Citations: 1
  • Design of 32 channel wavelength division multiplexing optical communication system
    C Supraja, T Kavitha, CK Pappa
    2022 International Conference on Knowledge Engineering and Communication … , 2022
    2022
    Citations: 3
  • Design of High Performance Parallel Multiplication using FPGA
    R Jenila, C Supraja, N Dharani, V Dinesh Kumar
    2022 IEEE International Conference on Current Development in Engineering and … , 2022
    2022
  • Design of Elliptical to Circular Dielectric Resonator Antenna for Microwave Imaging Application
    V Ramkumar, C Supraja, V Chinnammal, R Krishnan, L Saravanan, ...
    2022 International Conference on Power, Energy, Control and Transmission … , 2022
    2022
    Citations: 3
  • A smart and precision agriculture system using DHT11 plus FPGA
    R Jenila, CK Pappa, C Supraja
    Machine Learning and Autonomous Systems: Proceedings of ICMLAS 2021, 579-589 , 2022
    2022
    Citations: 6
  • An innovative sensing machine learning technique to detect credit card frauds in wireless communications
    G Sasikala, M Laavanya, B Sathyasri, C Supraja, V Mahalakshmi, ...
    Wireless Communications and Mobile Computing 2022 (1), 2439205 , 2022
    2022
    Citations: 36
  • Research Article An Innovative Sensing Machine Learning Technique to Detect Credit Card Frauds in Wireless Communications
    G Sasikala, M Laavanya, B Sathyasri, C Supraja, V Mahalakshmi, ...
    2022
  • Vlsi implementation of error detection and correction codes for space engineering
    R Jenila, C Supraja, CK Pappa, N Dharani
    2021 Third International Conference on Intelligent Communication … , 2021
    2021
    Citations: 5
  • CO-OPERATIVE SPECTRUM SENSING USING HETNET AND OFDM IN COGNITIVE RADIO NETWORKS
    DS 1Supraja.C
    S.A. ENGINEERING COLLEGE , 2018
    2018
  • Analysing the Spectrum Sensing using the Het Net Systems of Cognitive Radio Networks
    DS 1Supraja.C
    International Journal of Pure and Applied Mathematics 119 (ISSN: 1314-3395), 8 , 2018
    2018

MOST CITED SCHOLAR PUBLICATIONS

  • An innovative sensing machine learning technique to detect credit card frauds in wireless communications
    G Sasikala, M Laavanya, B Sathyasri, C Supraja, V Mahalakshmi, ...
    Wireless Communications and Mobile Computing 2022 (1), 2439205 , 2022
    2022
    Citations: 36
  • A smart and precision agriculture system using DHT11 plus FPGA
    R Jenila, CK Pappa, C Supraja
    Machine Learning and Autonomous Systems: Proceedings of ICMLAS 2021, 579-589 , 2022
    2022
    Citations: 6
  • Vlsi implementation of error detection and correction codes for space engineering
    R Jenila, C Supraja, CK Pappa, N Dharani
    2021 Third International Conference on Intelligent Communication … , 2021
    2021
    Citations: 5
  • Design of 32 channel wavelength division multiplexing optical communication system
    C Supraja, T Kavitha, CK Pappa
    2022 International Conference on Knowledge Engineering and Communication … , 2022
    2022
    Citations: 3
  • Design of Elliptical to Circular Dielectric Resonator Antenna for Microwave Imaging Application
    V Ramkumar, C Supraja, V Chinnammal, R Krishnan, L Saravanan, ...
    2022 International Conference on Power, Energy, Control and Transmission … , 2022
    2022
    Citations: 3
  • CitZO-SVM: machine learning-based spectrum sensing and channel allocation for cognitive radio networks
    C Supraja, K Thandapani
    INTERNATIONAL JOURNAL OF COMMUNICATION SYSTEMS 38 (7) , 2025
    2025
    Citations: 2
  • AR/VR-based object detection for blind people using 5G communication
    C Supraja, T Kavitha
    Machine learning for radio resource management and optimization in 5G and … , 2025
    2025
    Citations: 2
  • Automatic Anti Collision System For Intelligent Transportation System
    C Supraja
    Proceedings of the International Conference on Advanced Research in … , 2025
    2025
    Citations: 1
  • Design of Auto Encoder based on DNN for MIMO Systems
    T Kavitha, J Jaswanth, MM Kumar, N Ashokkumar, NR Yatm
    2024 Third International Conference on Electrical, Electronics, Information … , 2024
    2024
    Citations: 1
  • 5G network based spectrum analysis for mm-wave and sub 6 GHz
    C Supraja, T Kavitha
    A Study on Next-Generation Materials and Devices, 261-266 , 2025
    2025
  • A hybrid binary logical regression-gradient decent approach for dynamic cooperative spectrum sensing in CRN
    K Thandapani
    International Journal of Electronics 112 (9), 1898-1920 , 2025
    2025
  • New Radio User Equipment for Positioning Accuracy Enhancement using AI
    K Thandapani, A Arulmary, B Manimaran, NA Kumar, S C, M C
    2025 7th International Conference on Inventive Material Science and … , 2025
    2025
  • Next Generation Optical SDM Communication System using Artificial Intelligence
    C Supraja, C Murugan
    Proceedings of the International Conference on Advanced Research in … , 2025
    2025
  • AR/VR-based object
    C Supraja, T Kavitha
    Machine Learning for Radio Resource Management and Optimization in 5G and … , 2025
    2025
  • 5G Based Millimeter Wave Spectrum Sensing for Cellular Networks
    C Supraja, T Kavitha
    2025 International Conference on Multi-Agent Systems for Collaborative … , 2025
    2025
  • Video Transmission Using Wireless Optical Communication in Underwater
    K Thandapandi, C Supraja, C Murugan, A Arulmary, M Krishnamurthy, ...
    2024 International Conference on Sustainable Communication Networks and … , 2024
    2024
  • Design of High Performance Parallel Multiplication using FPGA
    R Jenila, C Supraja, N Dharani, V Dinesh Kumar
    2022 IEEE International Conference on Current Development in Engineering and … , 2022
    2022
  • Research Article An Innovative Sensing Machine Learning Technique to Detect Credit Card Frauds in Wireless Communications
    G Sasikala, M Laavanya, B Sathyasri, C Supraja, V Mahalakshmi, ...
    2022
  • CO-OPERATIVE SPECTRUM SENSING USING HETNET AND OFDM IN COGNITIVE RADIO NETWORKS
    DS 1Supraja.C
    S.A. ENGINEERING COLLEGE , 2018
    2018
  • Analysing the Spectrum Sensing using the Het Net Systems of Cognitive Radio Networks
    DS 1Supraja.C
    International Journal of Pure and Applied Mathematics 119 (ISSN: 1314-3395), 8 , 2018
    2018