Recent News

  • Tunnel Field Effect Transistor Design and Analysis for Biosensing Applications October 11, 2022

    tunnel field effect transistor

    The Department of Electronics and Communication Engineering is glad to announce that Mr Garikapati Anith Chowdary, a BTech passed-out student has published a paper in collaboration with Assistant Professor Dr M Durga Prakash. The paper titled Tunnel Field Effect Transistor Design and Analysis for Biosensing Applications was published in the Q2 journal Silicon having an Impact Factor 2.941.

    The physical modelling of the tunnel field effect transistor (TFET) is done in this study. The Silvaco TCAD tool is used to design and simulate the TFET structure. The FET device has attracted a lot of attention as the ideal tool for creating biosensors because of its appealing properties such as ultra-sensitivity, selectivity, low cost, and real-time detection capabilities in a sensing point of view.

    These devices have a lot of potential as a platform for detecting biomolecules. Short channel effects, specificity, and nano-cavity filling have all been improved in FET-based biosensors. FET-based biosensors are appropriate for label-free applications. Random dopant variations and a thermal budget are seen during the construction of a JLFET. To overcome this problem, the charge-plasma-based concept was established in FETs in this study.

    Different metallurgical functions for electrodes were employed in this biosensor to behave as a p-type source and n-type drain. To alleviate the short channel effects, a dual material gate work function for the gate electrode was devised, as well as a double gate architecture. Biomolecules can be neutral or charge-based, and both types of biomolecules can be identified using a proof-of-concept FET-based biosensor. Changes in the drain current (Id) of the device were achieved by varying dielectric values and charges in the cavity region with variable cavity lengths.

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  • Defect detection algorithms September 9, 2022

    Defect detection algorithmsResearch at the Department of Electronics and Communication Engineering is currently developing defect detection algorithms. Assistant Professor Dr V Udaya Sankar, Professor Dr Yellampalli Siva Sankar, and their BTech student Ms Gayathri Lakshmi have published a paper, A Review of various defects in PCB, in the Journal of Electronic Testing: Theory and Applications with an impact factor of 0.795.


    Printed Circuit Boards (PCBs) are the building blocks for all electronic products. Fabrication of a PCB involves various mechanical and chemical processes. As obtaining accuracy in the mechanical and chemical processes is very difficult, various defects/faults are formed during PCBs fabrication. These fabrication defects lead to performance degradation of electronic products. This paper describes multiple defects present in PCBs under the Through-hole and SMD categories. To understand the frequency of occurrence and reason for defects in both manual and machine, PCB fabrication data was collected and analysed from April 2017 to July 2020 as a part of industry collaboration.

    The research is a review done on the defects present in PCB. Researchers surveyed various papers on PCB defects and their detection. Based on the literature review and information obtained from Efftronics systems Pvt. Ltd, they classified the defects, gave a detailed explanation for each, and provided some analysis of their occurrences.

    While doing the literature review, researchers observed that no paper mentioned all the defects that can occur in the case of PCB fabrication. For this reason, they came up with this paper which provides detailed information regarding the defects. Information is also obtained from the industry. Comparing the defects can help focus on the critical defects for future research on defect detection methodology.

    The project is done in collaboration with Efftronics Systems Pvt. Ltd. Through the partnership, the company supported sharing images, insights information related to defects and involved in discussions. Also, the company allowed visiting their premises to understand more about PCB defects. Researchers look forward to creating a prototype that detects all the defects mentioned in this paper for a given PCB.

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  • A multifarious study on Low-Power Wide-Area Networks August 25, 2022

    research SRMAP

    The Department of Electronics and Communication Engineering is delighted to announce that Assistant Professor Dr Anirban Ghosh and Research Scholar Mr Naga Srinivasarao Chilamkurthy have published their article titled “Low-Power Wide-Area Networks: A Broad Overview of its different aspects” in IEEE Access, a Q1 Journal, having an Impact Factor of 3.476. The work was published in collaboration with Dr Om Jee Pandey from the Indian Institute of Technology BHU, Dr Cenkeramaddi Linga Reddy from the University of Agder, and Dr Hong-Ning Dai from Hong Kong Baptist University, Hong Kong.

    This is a survey article on Low-power Wide-area networks which provides a detailed description of LPWAN technologies in the context of IoT applications. In this survey article, they review and provide an overarching description of LPWAN in terms of design goals, techniques to improve design objectives, and system architecture. They have also evaluated several existing and non-standardized LPWAN technologies and the market opportunities of LPWAN. With the help of this article, the researchers can choose the best LPWAN technology for their specific applications.

    The practical implementation of the article can be found in various social and commercial applications such as smart healthcare, intelligent transportation, climate-smart agriculture, rescue operations, logistics, smart cities, industries, utilities, smart buildings, consumer electronics, security, asset tracking, smart waste management systems, cognitive manufacturing, and Machine-to-Machine (M2M) communications. Their future research plans include working on Wireless Sensor Networks, Low-Power Wide-Area Networks, Small-World Networks, and applying machine learning and reinforcement learning techniques in the context of wireless networks for cyber-physical systems and IoT applications.

    Abstract of the Research

    Low-power wide-area networks (LPWANs) are gaining popularity in the research community due to their low power consumption, low cost, and wide geographical coverage. LPWAN technologies complement and outperform short-range and traditional cellular wireless technologies in a variety of applications, including smart city development, machine-to-machine (M2M) communications, healthcare, intelligent transportation, industrial applications, climate-smart agriculture, and asset tracking. This review paper discusses the design objectives and the methodologies used by LPWAN to provide extensive coverage for low-power devices. We also explore how the presented LPWAN architecture employs various topologies such as star and mesh. We examine many current and emerging LPWAN technologies, as well as their system architectures and standards, and evaluate their ability to meet each design objective. In addition, the possible coexistence of LPWAN with other technologies, combining the best attributes to provide an optimum solution is also explored and reported in the current overview. Following that, a comparison of various LPWAN technologies is performed, and their market opportunities are also investigated. Furthermore, an analysis of various LPWAN use cases is performed, highlighting their benefits and drawbacks. This aids in the selection of the best LPWAN technology for various applications. Before concluding the work, the open research issues, and challenges in designing LPWAN are presented.

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  • Energy efficient MIMO-NOMA aided IoT network in B5G communications August 8, 2022

    Research SRMAP

    The Department of Electronics and Communication Engineering is glad to announce that Assistant Professor Dr Sunil Chinnadurai and his research scholar Mr Shaik Rajak have published a paper titled “Energy Efficient MIMO-NOMA aided IoT Network in B5G Communications” in the Q1 journal Computer Networks having an Impact Factor of 5.5. With an intent to accelerate the development of future intelligence wireless systems, the paper proposes an energy-efficient massive multiple-input-multiple-output (MIMO)- non-orthogonal multiple access (NOMA) aided internet of things (IoT) network to support the massive number of distributed users and IoT devices with seamless data transfer and connectivity.

    Abstract of the research

    Massive MIMO has been identified as a suitable technology to implement the energy efficient IoT network beyond 5G (B5G) communications due to its distinct characteristics with a large number of antennas. However, providing fast data transfer and maintaining hyperconnectivity between the IoT devices in B5G communications will bring the challenge of energy deficiency. Hence, they considered a massive MIMO-NOMA aided IoT network considering imperfect channel state information and practical power consumption at the transmitter. The far users of the base stations are selected to investigate the power consumption and quality of service. Then, they calculated the power consumption which is a non-convex function and non-deterministic polynomial problem. To solve the above problem, fractional programming properties are applied which converted the polynomial problem into the difference of convex function. And then they employed the successive convex approximation technique to represent the non-convex to convex function. Effective iterative-based branches and the reduced bound process are utilized to solve the problem. Numerical results observed that their implemented approach surpasses previous standard algorithms on the basis of convergence, energy efficiency, and user fairness.

    Explanation of the research in layman’s terms

    • A cost-effective (i.e., energy efficient) maximization problem for the multiple cells NOMA heterogeneous network scheme is explored when meeting the transmission power and data necessity of far users. The singular value uncertainty model (SVUM) is deliberated to add the errors with the transmitted signal. Since it’s a non-convex problem and challenging to solve, they used the properties of fractional programming to convert it into its corresponding mathematical terms. ITS needs higher data rate and seamless connectivity to operate with maximum speed and safety.
    • SCA methods are then applied to change the optimisation problem. After that, an effective iterative scheme is employed based on Branch and Reduced Bound (BRB) that resolves the energy-efficient SVUM problem and satisfies the convergence criteria.
    • The proposed iterative BRB method enhances user fairness and decreases inter-tier interference (ITI). IRS has been recognised as the key enabling technology to provide the data required by the ITS with less power consumption.
    • Energy efficiency achieved by the proposed BRB method is examined with the help of numerical results and found that the proposed algorithm provides better efficacy than the majorisation minimisation (MM) method and the well-known OMA scheme.

    Practical implementations of the research

    • To provide high data rates to wireless sensors and the internet of things (IoT), future communication systems can ultimately be advanced by implementing NOMA, small cell, and heterogeneous networks (HetNets) along with MIMO.
    • An energy-efficient massive MIMO-NOMA aided IoT network to support the massive number of distributed users and IoT devices with seamless data transfer and connectivity between them in B5G communications.

    Future research plans

    • To explore the energy efficiency of AI-driven IoT networks for applications such as intelligent health care and intelligent vehicular communications.
    • MIMO-NOMA with IRS elements to reduce power consumption and improve the connectivity between the users.
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  • Dr Divya Chaturvedi to join as a special issue guest editor at Hindawi August 5, 2022

    Dr Divya Chaturvedi SRMAP

    It is a matter of incredible honour to SRM University-AP, for Dr Divya Chaturvedi, Assistant Professor, Department of Electronics and Communication Engineering has been chosen as a special issue guest editor at Hindawi, one of the world’s largest publishers of peer-reviewed, fully open access journals of scientific, technical, and medical literature. Dr Divya has been keenly pursuing the umpteen possibilities of substrate integrated waveguide based cavity backed antennas, leaky wave antennas, wearable antennas for medical applications, and Multi-Input Multi-Output (MIMO) for 5G communication since the beginning of her career. And her research genius has bestowed her with numerous awards and recognitions over these years.

    As a guest editor for Hindawi, Dr Divya would be responsible for the special issues “Substrate Integrated Waveguide (SIW) Based Circuits and Systems” and “The Future of Wireless Communications Systems: 5G and beyond” from the journals: International Journal of Antennas and Propagation and Journal of Computer Networks and Communications respectively. While the former aims to publish outstanding papers presenting cutting-edge advances in the field of microwave and millimetre-wave circuits and systems, the recent technological advancements in wireless communication systems will be focused in the latter.

    Having served as the reviewer and member of various editorial boards and conferences, Dr Divya comes with a wealth of experience to put her expertise for the advancement of the publication. At Hindawi, she gets to work with a strong team of editors and network with like-minded colleagues around the world. ”It is truly fascinating to be a part of the Hindawi editorial board. The influential network that we build here could provide leads on professional opportunities or introduce us to new contacts in our discipline”, she remarked. This would also give her the liberty to handle manuscripts close to her professional interests and exert her creativity in the inception and development of a topic. The tenure of her role as an editor is expected to last for twelve months.

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