Dr. R. Anil kumar

@acet.ac.in

Associate Professor and Department of ECE
Aditya college of engineering and technology



           

https://researchid.co/anidecs

Dr. R. Anil Kumar is currently working as an associate professor in the electronics and communication engineering department at Aditya College of Engineering Technology, Surampalem. He received a doctoral degree from JNTUK University, Kakinada. He published 15 technical papers in various international journals and presented six technical papers at various conferences. He is an expert in wireless communications, signal processing, and ML and DS. He published three patents. He is an associate member of IETE and ISTE.

EDUCATION

Ph.D awarded from JNTUK University Kannada

RESEARCH, TEACHING, or OTHER INTERESTS

Engineering, Computer Networks and Communications, Electrical and Electronic Engineering, Artificial Intelligence

17

Scopus Publications

Scopus Publications

  • Optimum Power Forecasting Technique for Hybrid Renewable Energy Systems Using Deep Learning
    Shashank Singh, V. Subburaj, K. Sivakumar, R. Anil Kumar, M. S. Muthuramam, Ravi Rastogi, Vishal Ratansing Patil, and A. Rajaram

    Informa UK Limited

  • Design of Compact Triangle-Shaped MIMO Antenna with High Isolation for UWB Applications
    G. Vasantha, Sanjeev Kumar, N. Radha, R Anil Kumar, and Kunal Srivastava

    IEEE
    For use in ultrawideband (UWB) applications, a small triangle-shaped monopole MIMO antenna is proposed in this article. The designed antenna is composed of two modified triangular monopoles with rectangular slots carved onto the ground plane. A partial ground plane is employed at the substrate's back side when using microstrip feeding, and it offers good impedance matching for desired UWB band applications. The designed antenna has a dimension of only 14 mm x 26 mm x 1.59 mm. The operating band of the antenna is 10.5 GHz (4.0 -14.5 GHz) and the isolation is below 17 dB. This UWB antenna's performance has been analyzed, taking into account the effect of varying the antenna's geometric parameters. Throughout the entire operating band, good impedance matching, acceptable radiation pattern, and radiation efficiency greater than 92 % are observed.

  • Scheduling in Multi-Hop Wireless Networks using a Distributed Learning Algorithm
    Amit Jaykumar Chinchawade, S. Rajyalaxmi, Shashank Singh, R.Anil Kumar, Ravi Rastogi, and Mohd Asif Shah

    IEEE
    This study takes on the challenge of learning and scheduling in a Multi-Hop Wireless Network (MHWN) without having any prior knowledge of connection charges. Earlier scheduling methods needed knowledge of the connection rates, whereas Techniques for training often required a centralized authority and had an exponential performance. These represent a significant barrier to creating a reliable distributed strategy for resource allocation that relies on learning in massive multi-hop networks. Management of multihop control It is a tough task to implement wireless networks in a distributed fashion while meeting end-to-end timing constraints for a variety of flows. Using the notions of Draining Time and Continuous Review, which originate from the notion of fluid boundaries of queues, an algorithm is constructed that meets delay needs for various streams in a system. This study proposes a regulated maximal matching, a completely distributed scheduling algorithm that ensures at least 50% of the performance of a centralized method. The approach employs a distributed optimization procedure called iterative gradient ascent, which is carried out in a cyclic fashion between nodes with little data interchange. The system prioritizes flows using weights that change over time. The effectiveness of the algorithm is analyzed in a network setting where interruption is symbolized by isolated nodes.

  • Histogram Computation with a Reconfigurable Memory Based Fast VLSI Architecture
    M.N.N.L. Sai Ramesh and R Anil Kumar

    IOS Press
    Computation of histogram is the primary work that used in digital image processing systems. Mutual Information is the best measurement that also used for image registration. Calculation of the mutual information requires obtaining separate and combining histogram of the two images. By the increase of the histogram size, the demand for the hardware resource for the computation of the histogram is increased. This paper about the computation of the memory-based VLSI architecture has been shown. The architecture of the computation of the histogram is existed by using the plotting in the field programmable field array. Parallelization of histogram functions is a major problem due to memory collisions. So, to avoid these collisions there is a new technique called parallel histogram computation used. To implement the parallel histogram, it is requiring dual–ported memory. By making the computation of the histogram fast, there are several benefits obtained. Some of the examples are texture classification, image compression, etc shown in this manuscript.

  • A Future Awareness for Healthcare Applications Using Data Mining
    K. T. Sree, R Anil Kumar, and G. Rama Naidu

    IOS Press
    This research report showcases various data mining (DM) techniques such as Classification, Regression, and Clustering in brief and also discusses the aptest framework method for the healthcare industry, CRISP-DM. This report also explores the various data mining applications in the healthcare industry. DM is utilized to extract the data from a lot of information. DM includes two models, predictive and descriptive. Classifying data is to form classes either with the final objective of learning new antiques or searching new areas. This is why specialists have for many years tried to locate the enshrouded examples in the knowledge that can be classified and contrasted as well as other concepts which are the result of common principles.

  • An Analysis of Image Segmentation Methods
    K. T. S. Lakshmi and R Anil Kumar

    IOS Press
    Image segmentation is a crucial stage in image processing because it allows for meaningful image analysis and information extraction. Image segmentation may be done in a variety of ways. This study examines a few of these approaches for grayscale images. MATLAB 8.1 was used to construct the paper. In order to analyze and extract information from these pictures, segmentation is essential. The segmentation of images has a promising future and has been the focus of modern study. The usual segmentation methods were addressed here: edge detection, clustering, and region growth. The problem with segmentation is that no one approach is suited for a certain type of picture, nor are all techniques applicable to all images.

  • Enhanced Particle Swarm Optimization based Node Localization Scheme in Wireless Sensor Networks
    Shashank Singh, R. Poonkuzhali, G. Nithya, R. Anil Kumar, J. Kartigeyan, and S. Ramya

    IEEE
    Wireless sensor networks (WSNs) are widely examined recently because of their various applications in processes which has to scatter over a vast region. sensor's locations in WSNs generally must be known. WSN comprises great quantity of sensors thereby installing global position system devices in all of them does not accept. Some of the anchor nodes with well-known locations are generally utilized. Forecasting sensor node locations from radio strength signal index are regarded as a hard optimization issue. This article introduces an Enhanced Particle Swarm Optimization based Node Localization Scheme (EPSONLS) in WSN. The presented EPSONLS technique mainly aims to determine the location of the unknown nodes in the network. To do so, the presented EPSONLS model applies the PSO algorithm to identify the node position. In addition, the EPSONLS model determines the node location with the goal of minimizing localization error and time. An extensive-ranging experimental examination is performed and the outcomes are investigated under distinct prospects. The simulation outcome demonstrated the betterment of the EPSONLS model over recent approaches.

  • Optimal Extreme Learning Machine based Traffic Congestion Control System in Vehicular Network
    Rajendra Kumar Bharti, D. Suganthi, S.K Abirami, Relangi Anil Kumar, B Gayathri, and S. Kayathri

    IEEE
    Over the past decade, Smart cities have been advanced and minimizing traffic congestion become the main concern in the progression of smart cities. The rapid growth in the number of road vehicles has raised the number of road accidents and traffic congestion. To Solve this problem, Vehicular Network (VN) formulated several novel concepts which include traffic control, vehicular communications, and navigation. Machine Learning (ML) will be an effective technique for identifying hidden insights into ITS without being programmed clearly by learning from data. This article develops an Optimal Extreme Learning Machine based Traffic Congestion Control System (OELM-TCCS) in vehicular networks. The presented OELM-TCCS technique mainly focuses on the identification and recognition of traffic congestion in VANET. To perform this, the presented OELM-TCCS technique primarily designs a new ELM model to carry out the classification process. In addition, the presented OELM-TCCS technique executes the satin bowerbird optimization (SBO) algorithm for parameter tuning of the ELM method. To demonstrate the boosted performance of the OELM-TCCS model, a series of experiments were executed. The experimental outcomes indicate the betterment of the OELM-TCCS method over recent methods with maximum accuracy of 99.17%.

  • Cardiac Surveillance System Using by the Modified Kalman Filter
    Sabbella Urmila, R. Anil Kumar, and Mahesh K. Singh

    Springer Nature Switzerland

  • Intertwine Connection-Based Routing Path Selection for Data Transmission in Mobile Cellular Networks and Wireless Sensor Networks
    Vijay, Shams Tabrez Siddiqui, Ritu, Relangi Anil Kumar, Avinash Kumar, S. Umamaheswararao, Narahari Dudiki, Y. Venkateswara Reddy, and Kenenisa Dekeba

    Hindawi Limited
    In a network setting, a sensor node's round-trip delay time over hostile nodes compromises the node's ability to transmit data from the sender node to the destination node. Minimum distance path discovery causes the path failure, since aggressive nodes are available. Node connectivity is poor which should cause the packet loss; it does not control more energy consumption, since packet broadcasting is repeated for many times using that path. So, the proposed intertwine connection-based routing path selection (ICBRPS) technique allows only energy efficient routing path, path connectivity is important, and routing path is damaged because of the presence of aggressive nodes. It hacks the information from sensor and operates unpredictable manner. The objective of this presented ICBRPS scheme is to improve the routing path in efficient manner. If any damages occur during the transmission of data, then the alternate best node connectivity path is created by energetic route discovery method. The performance metrics of parameters are delay, network overhead, energy consumption, packet loss, packet delivery ratio, and connectivity ratio. It enhances the connectivity rate and reduces the energy consumption.

  • Enhanced Path Routing with Buffer Allocation Method Using Coupling Node Selection Algorithm in MANET
    Rajendra Kumar Bharti, Soundarajan S, Sushma V. Sumant, C. Anand Deva Durai, Relangi Anil Kumar, Kamlesh Singh, Hemant Palivela, B. Rajesh Kumar, and Baru Debtera

    Hindawi Limited
    In a mobile network, nodes are placed in infrequent manner, which are moved along network in abruptly. Communication flaw between sender node and accepting node in path, the node having restricted energy and restricted transmission rate. It does not provide perfect route for communication among mobile nodes. It increases the packet drop rate and minimizes the lifetime of network. This work has proposed enhanced path routing with buffer allocation (IPBA) scheme which is implemented to obtain better communication; it protects the node from packet loss, and the buffer is used to maintain the temporary details of nodes and data packets that are ready to broadcast and receive. The coupling node selection algorithm is constructed to offer the path which frequently communicates data packets in normal case; the two efficient nodes are coupled with each other, and this type of nodes is selected to perform communication. It reduces the packet loss rate and increases network lifetime. End-to-end delay, communication overhead, throughput, network lifetime, packet loss, and energy consumption are the parameters considered for performance evaluations.

  • Performance analysis of an efficient linear constellation precoded generalized frequency division multiplexing with index modulation in 5G heterogeneous wireless network
    Relangi Anil Kumar and K. Satya Prasad

    Wiley
    Nowadays, wireless accesses are demanded with new applications, but they generate many technical issues. Moreover, the issues related to the beyond fifth generation (5G) wireless networks can be tackled using an orthogonal frequency division multiplexing (OFDM) schemes. Due to the huge growth of wireless users, this scheme exists with some technical challenges. An enhanced radio access technology is required to tackle the technical constraints of upcoming 5G wireless network applications. Nowadays, the generalized frequency division multiplexing (GFDM) scheme is exploited by wireless networks because of their benefits like spectral efficiency, low latency, and out‐of‐band (OOB) emission. In this paper, a linear constellation precoded GFDM with interleaved quadrature index modulation (LCP‐GFDM‐IQIM) scheme is proposed to harvest extra diversity gain by spreading the information symbols in‐phase/quadrature component. Also, in‐phase/quadrature (I and Q) dimensions are explored in index modulation (IM). Both theoretical and simulation analysis shows that the proposed LCP‐GFDM‐IQIM scheme achieves better spectral efficiency and energy efficiency as compared to the existing methods.

  • Performance Analysis of GFDM Modulation in Heterogeneous Network for 5G NR
    R. Anil Kumar and K. Satya Prasad

    Springer Science and Business Media LLC

  • Circuits Based on the Memristor for Fundamental Operations
    A. Nandini, R. Anil Kumar, and Mahesh K Singh

    IEEE
    The memristor, which is the fourth passive element that is lacking, is a nonvolatile device with two terminals. It promises advancement in future technology, which will aid in the reduction of power consumption, the reduction of cost, and the increase of performance of integrated circuits. This work presents a thorough investigation of memristor modeling through the use of Mat lab simulations. For the purpose of anticipating the behavior of the memristor device, we consider three different modeling strategies. In addition to the solid-state thin film memristor device, a spintronic memristor device based on magnetic technology was also simulated in this study. The fact that it has nanoscale geometry means that it is susceptible to process fluctuations during the fabrication process. The electrical behavior of the memristor deviates from the desired values as a result of process changes. As a result, the yield of a memristor-based memory design is lowered as a result. Also discussed in this study is a concrete model of a spintronic device that is based on the mechanism of magnetic-domain-wall motion and is described in detail.

  • Review of 5G Communications Over OFDM and GFDM
    Pasupuleti Sai Deepthi, Vura Sai Priyanka, R. Anil Kumar, and Sanjeev Kumar

    Springer Nature Singapore

  • Multi-point Data Transmission and Control-Data Separation in Ultra-Dense Cellular Networks
    Krishna Pavani Karri, R. Anil Kumar, and Sanjeev Kumar

    Springer Nature Singapore

  • Wireless Powered Uplink of NOMA Using Poisson Cluster Process with Two Orthogonal Signal Sets
    Ashok Kumar Kona, R. Anil Kumar, and Sanjeev Kumar

    Springer Nature Singapore