Dr. Drakshayini M N

@tjohncollege.com

HOD Electronics and Communication Engineering
T. John Institute of Technology

Dr. Drakshayini M N


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https://researchid.co/drakshayini

EDUCATION

Ph. D. in Electronics and Communication Engineering from Reva University, Bangalore in 2024
M. Tech in Electronics from Sir. MVIT, Bangalore affiliated to VTU in 2005.
Bachelor of Engineering (B. E.) in Electronics and Communication Engineering from Dr. AIT, Bangalore, Bangalore University.

RESEARCH, TEACHING, or OTHER INTERESTS

Electrical and Electronic Engineering
7

Scopus Publications

58

Scholar Citations

4

Scholar h-index

2

Scholar i10-index

Scopus Publications

  • Design of Deep Learning-Based Intelligent Blind Direct Sequence Code Division Multiple (DS-CDMA) Access Receiver
    M. N. Drakshayini, Manjunath R. Kounte
    Lecture Notes in Networks and Systems, 2024
  • Predicting Heart Disease with Machine Learning: A Comparative Study
    Swetha R, Helen. K. Joy, Warusia Yassin, Sridevi. R, Drakshayini M N, Fabiola Hazel Pohrmen
    Proceedings of 5th International Conference on Iot Based Control Networks and Intelligent Systems Icicnis 2024, 2024
    Heart disease is considered as the leading causes of death worldwide. Detection in early stage helps to prevent the disease. Nearly 17 million heart disease deaths occur every year. If heart disease is detected early, it could save many lives. Using machine learning algorithms to detect heart disease early will benefit many people. The present study explains the utilization of machine learning algorithms and artificial intelligence in the detection of cardiac illness. Data science plays a crucial role in healthcare by facilitating the analysis and processing of large volumes of data, therefore enabling the application of Artificial Intelligence (AI) and Machine Learning (ML). This study aims to identify the optimal model for predicting heart disease by employing different classification methods of machine learning, including Logistic Regression (LR) and Support Vector Machine. keywords Artificial intelligence, machine learning, prediction of heart disease, selection of features, decision trees, logistic regression, and accuracy.
  • Estimation of Rayleigh flat channel coefficients using deep learning
    Drakshayini Melkote NanjundaShetty, Manjunath R. Kounte
    Transactions on Emerging Telecommunications Technologies, 2023
    Channel estimation is a significant prerequisite in wireless communication, especially where the multipath radio propagation incurs significant fading in a noisy environment. In such a scenario, Rayleigh fading model is traditionally adopted to represent the communication channel. In this article, a new method of getting the Rayleigh flat channel coefficients using deep learning is presented. Here, we presume that the channel state and the corresponding channel coefficients remain constant in a given communication context which depends on the locations of transmitter/receiver, time of the day and the communication environment. When the context changes, the channel state also changes and the corresponding coefficients switch to the respective matching values. Thus the channel coefficients can have several possible realizations or classes. In our scheme, the deep learning network, after training, acts as a classifier to detect the class or the context of the channel state and based on that determines the corresponding channel coefficients. In our proposed method, the percentage reduction in the percentage error is about 26% of that of its nearest competitor when the channel SNR is 10 dB.
  • A review of wireless channel estimation techniques: challenges and solutions
    M.N. Drakshayini, Manjunath R. Kounte
    International Journal of Wireless and Mobile Computing, 2022
    In wireless communication, the transmitted signal is subjected to distortion, noise, frequency shift, non-linear attenuation, fading, and so on due to the inherent nature of the physical characteristics of the channel. To compensate for these impairments, efficient and accurate Channel Estimation is an imperative requirement. In this review, Channel Estimation techniques available in the literature are selectively identified, analysed and evaluated. Channel Estimation methods can be broadly classified into two major divisions as 'Model-Based' and 'Deep Learning-Based'. Model-Based methods strive for block-wise optimisation. On the contrary Deep Learning-Based methods provide end-to-end optimisation irrespective of variations in the channel characteristics. The main objective is to reduce the computational overhead while improving the accuracy of the Channel Estimation under a diverse transmission and propagation environment. In this paper, we review the contributions of various authors in dealing with Channel Estimation for the application of Deep Learning techniques in Channel Estimation.
  • Smart DS-CDMA receiver based on feed forward neural network
    Drakshayini M N, Manjunath R Kounte
    Advances in Parallel Computing, 2022
    Direct Sequence Code Division Multiple Access (DS-CDMA) is a schemewhere several users transmit their data simultaneously over a common wireless communication channel,by spreading each data by distinct codes. At the receiver, the individual data are detected by appropriate decoding. In this paper, a new smart receiver is proposed for detecting DS-CDMA signals based on a multi-layer Feed Forward Neural Network (FFNN). The proposed receiver detects the transmitted data when the received signal is distorted due to channel noise, near-far effect and Rayleigh fading. The channel state information is indirectly captured during the training of the FFNN and hence the conventional channel state estimation using pilot signal or training sequences is eliminated. Experimental results show that the performance of the proposed receiver in terms of detection accuracy is superior to similar competitive demodulators.
  • Integrated antenna for the digital audio broadcasting and digital video broadcasting by orthogonal frequency division multiplexing
    , Drakshayini M N, Dr. Arun Vikas Singh, and
    International Journal of Innovative Technology and Exploring Engineering, 2019
    Digital Audio Broadcasting (DAB) system is one of the high - definition radio with the ability to provide high audio quality and data - based services for stationary and mobile receivers. Digital Video Broadcasting (DVB) is the popular broadcasting standards that enable handheld receivers to receive high definition digital television transmissions. Orthogonal Frequency Division Multiplexing (OFDM) system is a digital multi – carrier modulation technique intend offers high spectral efficiency. The main aim set is to arrive as an efficient unified system for multipurpose wireless system that would cater to all existing standards. This paper presents the unified approach for designing an integrated antenna for DAB and DVB using OFDM system. In this paper DAB and DVB using OFDM system is designed individually and their performance is measured by Bit Error Rate (BER). Integrated antenna for DAB and DVB using OFDM system is designed and simulated radiation patterns are presented. The proposed unified approach produces the better BER performance and better gain as compared to individual standard design.
  • A review on reconfigurable orthogonal frequency division multiplexing (OFDM) system for wireless communication
    Drakshayini M N, Arun Vikas Singh
    Proceedings of the 2016 2nd International Conference on Applied and Theoretical Computing and Communication Technology Icatcct 2016, 2017
    This paper presents the development of reconfigurable OFDM system for wireless communication system from a historical view. A review of research contributions to reconfigurable OFDM systems are summarized. These contributions comprise a development of reconfigurable OFDM system for Software Defined Radio, Implementation of reconfigurable digital modulator for OFDM system, evolution of FFT design for OFDM system, Evolution of reconfigurable OFDM mother model for different OFDM standards and Implementation of reconfigurable radio using OFDM system are discussed.

RECENT SCHOLAR PUBLICATIONS

  • Division Multiple (DS-CDMA) Access
    MN Drakshayini, MR Kounte
    Proceedings of Ninth International Congress on Information and Communication … , 2024
    2024.0
  • Design of a Deep Learning based Intelligent Receiver for a Wireless Communication System
    MN Drakshayini, MR Kounte, C Ravindra
    International Journal of Electrical and Electronics Research 12 (1), 228-237 , 2024
    2024.0
    Citations: 1
  • Design of Deep Learning-Based Intelligent Blind Direct Sequence Code Division Multiple (DS-CDMA) Access Receiver
    MN Drakshayini, MR Kounte
    International Congress on Information and Communication Technology, 327-337 , 2024
    2024.0
  • Estimation of Rayleigh flat channel coefficients using deep learning
    MRK Drakshayini Melkote NanjundaShetty
    Transactions on Emerging Telecommunications Technologies , 2022
    2022.0
    Citations: 9
  • Estimation of Rayleigh flat channel coefficients using deep learning
    MRK Drakshayini Melkote NanjundaShetty
    Transactions on Emerging Telecommunications Technologies , 2022
    2022.0
  • Smart DS-CDMA Receiver Based on Feed Forward Neural Network
    MN Drakshayini, MR Kounte
    Advances in Parallel Computing Algorithms, Tools and Paradigms, 19-25 , 2022
    2022.0
  • A review of wireless channel estimation techniques: challenges and solutions
    MN Drakshayini, MR Kounte
    International Journal of Wireless and Mobile Computing 23 (2), 193-203 , 2022
    2022.0
    Citations: 27
  • UNIFIED DIGITAL AUDIO AND DIGITAL VIDEO BROADCASTING SYSTEM USING ORTHOGONAL FREQUENCY DIVISION MULTIPLEXING (OFDM) SYSTEM
    MN Drakshayini, AV Singh
    GARI Publisher , 2018
    2018.0
  • A review on reconfigurable orthogonal frequency division multiplexing (OFDM) system for wireless communication
    MN Drakshayini, AV Singh
    2016 2nd International Conference on Applied and Theoretical Computing and … , 2016
    2016.0
    Citations: 11
  • Foundation of Computer Science (FCS), NY, USA
    MN Drakshayini, AV Singh
    2016.0
  • An Efficient Orthogonal Frequency Division Multiplexing (OFDM) System and Performance Analysis of Digital Audio Broadcasting (DAB) System
    MN Drakshayini, DAV Singh
    International Journal of Computer Applications 148 (8) , 2016
    2016.0
    Citations: 7
  • Performance Of Digital Video Broadcastingterrestrial (Dvb-T) Using Ofdm As System
    MN Drakshayini, AV Singh, S Vyshanava Nandini
    IJRET: International Journal of Research in Engineering and Technology … , 0
    Citations: 3

MOST CITED SCHOLAR PUBLICATIONS

  • A review of wireless channel estimation techniques: challenges and solutions
    MN Drakshayini, MR Kounte
    International Journal of Wireless and Mobile Computing 23 (2), 193-203 , 2022
    2022.0
    Citations: 27
  • A review on reconfigurable orthogonal frequency division multiplexing (OFDM) system for wireless communication
    MN Drakshayini, AV Singh
    2016 2nd International Conference on Applied and Theoretical Computing and … , 2016
    2016.0
    Citations: 11
  • Estimation of Rayleigh flat channel coefficients using deep learning
    MRK Drakshayini Melkote NanjundaShetty
    Transactions on Emerging Telecommunications Technologies , 2022
    2022.0
    Citations: 9
  • An Efficient Orthogonal Frequency Division Multiplexing (OFDM) System and Performance Analysis of Digital Audio Broadcasting (DAB) System
    MN Drakshayini, DAV Singh
    International Journal of Computer Applications 148 (8) , 2016
    2016.0
    Citations: 7
  • Performance Of Digital Video Broadcastingterrestrial (Dvb-T) Using Ofdm As System
    MN Drakshayini, AV Singh, S Vyshanava Nandini
    IJRET: International Journal of Research in Engineering and Technology … , 0
    Citations: 3
  • Design of a Deep Learning based Intelligent Receiver for a Wireless Communication System
    MN Drakshayini, MR Kounte, C Ravindra
    International Journal of Electrical and Electronics Research 12 (1), 228-237 , 2024
    2024.0
    Citations: 1
  • Division Multiple (DS-CDMA) Access
    MN Drakshayini, MR Kounte
    Proceedings of Ninth International Congress on Information and Communication … , 2024
    2024.0
  • Design of Deep Learning-Based Intelligent Blind Direct Sequence Code Division Multiple (DS-CDMA) Access Receiver
    MN Drakshayini, MR Kounte
    International Congress on Information and Communication Technology, 327-337 , 2024
    2024.0
  • Estimation of Rayleigh flat channel coefficients using deep learning
    MRK Drakshayini Melkote NanjundaShetty
    Transactions on Emerging Telecommunications Technologies , 2022
    2022.0
  • Smart DS-CDMA Receiver Based on Feed Forward Neural Network
    MN Drakshayini, MR Kounte
    Advances in Parallel Computing Algorithms, Tools and Paradigms, 19-25 , 2022
    2022.0
  • UNIFIED DIGITAL AUDIO AND DIGITAL VIDEO BROADCASTING SYSTEM USING ORTHOGONAL FREQUENCY DIVISION MULTIPLEXING (OFDM) SYSTEM
    MN Drakshayini, AV Singh
    GARI Publisher , 2018
    2018.0
  • Foundation of Computer Science (FCS), NY, USA
    MN Drakshayini, AV Singh
    2016.0