Satyendra Singh Yadav

Scopus Publications

A 1-Bit Holey Substrate-Integrated Reconfigurable Intelligent Surface for Enhanced Signal Coverage
Sunanda Mukhopadhyay, Abhishek Sarkhel, Debojyoti Chattapadhyay, Soumendu Ghosh, Satyendra Singh Yadav
IEEE Antennas and Wireless Propagation Letters, 2026
This letter proposes a low-insertion-loss, 1-bit re-configurable intelligent surface (RIS) with a high relative band-width to enhance signal coverage in indoor environments. The RIS meta-atom, with an aperture of 0.22λ<sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">0</sub>, accomplishes phase tailoring by embedding a varactor diode between two triangular patches printed on top of a dielectric substrate and a holey sub-strate, which serves as an intermediate layer, backed by a metal-lic patch as a reflector. The presence of the holey substrate ena-bles a maximum tunable phase shift of 231° with a relative bandwidth of 21.10% over a frequency span of 3.01-3.72 GHz. Furthermore, a characteristic mode-based approach has been employed for the realization of high relative bandwidth over a frequency range, which makes this work unique. Thereaf-ter, an array of 16×16 meta-atoms with a specific phase gradi-ent map has been placed in a realistic wireless indoor environ-ment to authenticate the signal coverage enhancement. Finally, the RIS prototype has been fabricated and measured to demon-strate a power intensity enhancement in the indoor environment.
A Multi-Metric Performance Analysis of STAR-RIS Aided MIMO-NOMA Framework for CIoT-Enabled 6G Wireless Networks
Debbarni Sarkar, Satyendra Singh Yadav, Vipin Pal, Keshav Singh, Kapal Dev, Hyundong Shin
IEEE Transactions on Consumer Electronics, 2026
Consumer internet of things (CIoT) devices are increasingly being integrated into various aspects of wireless communication, enhancing the scalability of networks. Along with these, in sixth-generation (6G) wireless networks, reconfigurable intelligent surface (RIS) has emerged as a prominent technology that can dynamically control the wireless environment. As a progression of this technology, recently, simultaneously transmitting and reflecting-RIS (STAR-RIS) has gained significant attention for its ability to achieve full-space coverage by simultaneously transmitting and reflecting signals. On the other hand, multiple input multiple output (MIMO) and non-orthogonal multiple access (NOMA) technologies have already proven their dominance in fifth-generation (5G) wireless communication networks by obtaining massive connectivity and high spectral efficiency. This paper proposes a mode switching-based STAR-RIS aided MIMO-NOMA framework for 6G wireless networks to cover the non-line-of-sight (NLoS) region as a footprint. The proposed framework adopts the selection combining and maximum ratio combining protocols to meet the quality of service requirements of the CIoT devices in NLoS regions. The study also derives mathematical formulations for the proposed framework by analyzing key performance metrics, including achievable data rate (ADR), outage probability, bit error rate (BER), diversity order, and throughput. To evaluate the effectiveness of the proposed system, comparative analyses are conducted against benchmark models such as STAR-RIS assisted single-input single-output (SISO) orthogonal multiple access and STAR-RIS assisted SISO-NOMA schemes. Simulation results affirm the superiority of the proposed framework for both the reflecting and transmitting regions of the STAR-RIS. In the transmitting region, under the maximum ratio combining protocol, the far CIoT device of the proposed STAR-RIS aided MIMO-NOMA framework attains an ADR at least 0.45 times higher than the conventional framework. Further, the BER of the proposed framework is 0.93 times lower than conventional framework.
Intelligent Resource Allocation for Satellite-RIS-Assisted URLLC-ISAC Systems Using Deep Learning Approach
Debbarni Sarkar, Keshav Singh, Satyendra Singh Yadav, Chih-Peng Li
IEEE Transactions on Cognitive Communications and Networking, 2026
In sixth-generation (6G) wireless communication, cognitive satellite-terrestrial networks play a crucial role in ensuring seamless and reliable connectivity for satellite users (SUs) and concurrently enable efficient spectrum sharing among cellular users (CUs). However, the coexistence of SUs and CUs introduces challenges such as interference management, latency constraints, privacy threats from potential eavesdroppers (Eves), and the need for accurate sensing to support dynamic spectrum access. To address these challenges, the reconfigurable intelligent surface (RIS) emerges as a promising and cost-efficient technology, and its performance can be further enhanced through integration with ultra-reliable low-latency communication (URLLC). URLLC ensures fast, reliable, and secure communication for SUs and CUs and supports both real-time and mission-critical applications. Along with these, integrated sensing and communication (ISAC) is a pivotal technology that enhances the system performance through environmental monitoring, detecting Eves activity, and strengthening both satellite and terrestrial links. Recently, deep learning (DL) techniques have gained significant attention as powerful tools in optimizing network performance, improving signal detection, enabling smarter resource allocation, and adaptive beamforming. Therefore, this paper introduces an intelligent resource allocation approach in a satellite-RIS-assisted URLLC-ISAC system. A DL model has been proposed to optimize the sensing beam, maximizing the minimum beam gain across multiple targets to enhance resource allocation. The proposed DL model jointly optimizes transmit beamforming, the reflecting units, and the sensing matrix under practical constraints. Simulation results demonstrate the model’s effectiveness in handling the complex optimization in the system under consideration. Simulation results show that the convergence and feasibility of the proposed model, and the proposed DL model outperform in optimizing the beam gain compared to the benchmark models. The performance has also been analyzed for both active and passive RIS configurations. Furthermore, to test the model’s efficacy in changing channel conditions, the performance of the proposed model has been validated across different channels. The time complexity analysis of the proposed model has also been evaluated.
FCMOC: Fuzzy-C-Means based Optimal Clustering Approach for Load Balanced Energy Efficient Wireless Sensor Networks
Ikkurthi Bhanu Prasad, Saumitra Gangwar, Yogita, Satyendra Singh Yadav, Krishna Kumar, Vipin Pal
IEEE Sensors Journal, 2026
A Super Light Convolutional Neural Network for Automatic Modulation Recognition in Unmanned Aerial Vehicles based 6G Wireless Network
Debbarni Sarkar, Samarth Verma, Rupa Kumari, Yogita Yogita, Vipin Pal, Satyendra Singh Yadav
IEEE Latin America Transactions, 2025
Automatic Modulation Recognition (AMR) is a fundamental capability for Unmanned Aerial Vehicle (UAV) communication systems in sixth-generation (6G) wireless networks. It enables UAVs to intelligently identify and track received signals, supporting reliable connectivity under dynamic environments. In practical UAV applications, AMR methods must achieve high recognition accuracy with minimal computational complexity, since UAV platforms operate under strict constraints in storage, memory, and processing power. While recent Deep Learning (DL)-based solutions have advanced AMR performance, most prioritize accuracy at the cost of significantly larger models and higher computational demands. Conversely, lightweight models often lack the accuracy required for real-time deployment, limiting their practical utility. To overcome these limitations, this paper presents a novel Super Light Convolutional Neural Network (SLCNN) for AMR. Unlike conventional models, SLCNN em-ploys a carefully optimized architecture with fewer convolutional layers, smaller filters, and pooling operations, combined with Gaussian noise and dropout for robust generalization. This design strategy reduces model size and inference time while preserving high accuracy. The proposed SLCNN was evaluated on the HisarMod 2019.1 dataset and validated across RML 2016.10a, 2016.10b, and 2018.01a datasets. Experimental comparisons with Convolutional Long Short-Term Memory Deep Neural Network (CLNN), Long Short-Term Memory, Gated Recurrent Unit, and Residual Network highlight that SLCNN achieves superior results, attaining 98.50% classification accuracy with significantly reduced computational cost. Furthermore, deployment on the NVIDIA Jetson Orin Nano demonstrates real-time suitability, confirming the models effectiveness for UAV-based 6G wireless networks.
Passive metasurface reflector for 6G wireless signal coverage enhancement in indoor environment: Design and experimental demonstrations
Sunanda Mukhopadhyay, Abhishek Sarkhel, Partha Pratim Sarkar, Satyendra Singh Yadav
Physical Communication, 2025
Deep Learning Based Channel Estimation for UAVs: A Modified U-Net Approach
C. GUPTA, S. S. YADAV
Advances in Electrical and Computer Engineering, 2025
A stable and reliable communication link is crucial for unmanned aerial vehicle (UAV) applications. Key challenges include the UAV's high mobility (10-100 km/h) and an unstable data link. Orthogonal frequency division multiplexing (OFDM) enables higher data rate transmission with improved bandwidth efficiency, while minimizing channel effects on the received signal and enhancing bit error rate (BER) performance. This article proposes a deep learning based channel estimation (CE) for 802.11ac OFDM systems considering the mobility of the receiver. The proposed CE algorithm is a two-step process. The first step uses an especially developed deep neural network built on the U-Net model for denoising the signal received, followed by least squares (LS) estimation in the next step. The simulation results show that the proposed model has improved the BER by 50% and 40%, the data rate by 10% and 7% and outage probability by 10% and 7%, respectively, when compared to the conventional LS estimator and machine learning based LS estimator. The proposed model has also been evaluated for three different modulation schemes, i.e., QPSK, 16-QAM, and 64-QAM and the complexity analysis has been done to strengthen our studies further.
A Wideband Digitally Coded Metasurface Using Staggering Tuning Mechanisms for Beam Steering Application in 6G mm-Wave Communication
Sunanda Mukhopadhyay, Abhishek Sarkhel, Satyendra Singh Yadav
Signals and Communication Technology, 2025
Low-RCS Wideband Absorber Based on Symmetry Frequency Selective Surfaces for Next-Generation Stealth Applications
Debojyoti Chattapadhyay, Satyendra Singh Yadav, Abhishek Sarkhel
Indiscon 2025 IEEE 6th India Council International Subsections Conference Proceedings, 2025
This paper presents a wide-band absorber incorporating a compact frequency-selective surface (FSS) element specifically designed for operation across the $\mathrm{C}, \mathrm{X}, \mathrm{Ku}$, and K-bands $(6.65-21.71 \mathrm{GHz})$. The proposed structure comprises a symmetric FSS with a central metallic square, extended meandered arms, and resistive patches to regulate absorption. Its symmetric configuration ensures polarization insensitivity, achieving a wide absorption bandwidth of 106.21% along with a minimum of 92% absorption efficiency. The absorber exhibits stable electromagnetic performance under oblique incidence angles up to 50° across orthogonal polarization states. The proposed absorber’s design is significantly smaller in size, $0.199 \lambda_{L} \times 0.095 \lambda_{L}$. Additionally, it effectively reduces the radar cross-section (RCS), enhancing stealth capability by mitigating backscattered signals. The combination of wideband absorption, polarization insensitivity, and the overall reduction of RCS makes this absorber an excellent challenger for stealth and radar applications.
Differently Shaped Beams Analysis of Reconfigurable Intelligent Surface for 6G FR1 Band Signal Coverage Extension in Indoor Environment
Sunanda Mukhopadhyay, Abhishek Sarkhel, Satyendra Singh Yadav
2025 IEEE Microwaves Antennas and Propagation Conference Mapcon 2025, 2025
In the field of 6 G wireless propagation, reconfigurable intelligent surfaces (RISs) have currently attracted a lot of interest. However, due to the increasing number of obstacles, direct line-of-sight (LoS) propagation has been restricted. Therefore, the extension of signal coverage for the FR1 band in the indoor environment is an essential requirement. Despite the growing demand for RIS on 6G FR1 band wireless signal coverage extension, a limited number of research works have been reported. In this article, the differently shaped beam of RIS has been analyzed through the phase gradient profile developed on top of the RIS layer for the 6 G FR1 band application. Thereafter, two customized corridors with different configurations have been designed. Finally, these differently shaped beams have been located inside the indoor environment to evaluate the expansion of signal coverage.
Phase Gradient Profile and Target Deviation Error Analysis of 3-Bit Angle Insensitive Intelligent Reflecting Surface for 6G FR1 Band Application
Sunanda Mukhopadhyay, Abhishek Sarkhel, Satyendra Singh Yadav
4th Wireless Antenna and Microwave Symposium Wams 2025, 2025
Comparative Analysis of OTFS and OFDM for UAV Assisted Wireless Network
Chirag Gupta, Satyendra Singh Yadav, Ramani Kumar Das
7th International Conference on Energy Power and Environment Icepe 2025, 2025
Polarization-Insensitive Triple-Band Millimeter-Wave Absorber for 6G Radar Communication
Debojyoti Chattapadhyay, Soumendu Ghosh, Satyendra Singh Yadav, Abhishek Sarkhel
Signals and Communication Technology, 2025
SVD Assisted Agglomerative Clustering Based Framework for Video Summarization and Captioning
Arjun Verma, Deepak Kumar, Vishal Kumar, Vipin Pal, Satyendra Singh Yadav
International Conference on Artificial Intelligence and Emerging Technologies Icaiet 2025, 2025
GTTR: A Game Theory-Based TOPSIS Optimized Routing Protocol for WSNs
Saumitra Gangwar, Ikkurthi Bhanu Prasad, Yogita, Satyendra Singh Yadav, Vipin Pal, Neeraj Kumar
IEEE Sensors Journal, 2025
GANCE: Generative Adversarial Network Assisted Channel Estimation for Unmanned Aerial Vehicles Empowered 5G and Beyond Wireless Networks
Chirag Gupta, Ramani Kumar Das, Rabindra K. Barik, Shahazad Niwazi Qurashi, Diptendu Sinha Roy, Satyendra Singh Yadav
IEEE Access, 2025
Performance Evaluation of ML-Based Classifiers for IRS-Aided NOMA-Based 6G Cognitive Radio Networks
Debbarni Sarkar, Satyendra Singh Yadav, Vipin Pal, Yogita, Sarat Kumar Patra
Wireless Personal Communications, 2024
IRS-aided NOMA-based communication architecture for 6G wireless networks: An enhanced error-control and reliable data transmission
Debbarni Sarkar, Vipin Pal, Satyendra Singh Yadav, Sarat Kumar Patra
Physical Communication, 2024
HSCR: Hierarchical structured cluster routing protocol for load balanced wireless sensor networks
Saumitra Gangwar, Ikkurthi Bhanu Prasad, Yogita, Satyendra Singh Yadav, Vipin Pal, Sarat Kumar Patra
Software Practice and Experience, 2024
HCM: a hierarchical clustering framework with MOORA based cluster head selection approach for energy efficient wireless sensor networks
Ikkurthi Bhanu Prasad, Saumitra Gangwar, Yogita, Satyendra Singh Yadav, Vipin Pal
Microsystem Technologies, 2024
A Comprehensive Survey on IRS-Assisted NOMA-Based 6G Wireless Network: Design Perspectives, Challenges and Future Directions
Debbarni Sarkar, Yogita, Satyendra Singh Yadav, Vipin Pal, Neeraj Kumar, Sarat Kumar Patra
IEEE Transactions on Network and Service Management, 2024
GTFR: A Game Theory-Based Fuzzy Routing Protocol for WSNs
Saumitra Gangwar, Yogita, Ikkurthi Bhanu Prasad, Satyendra Singh Yadav, Vipin Pal, Neeraj Kumar
IEEE Sensors Journal, 2024
Enhancing Face Recognition Accuracy: A Novel Approach Using EfficientNet B7 and Triplet Loss Learning
Saurav Gupta, Shruti Sharma, Ronit Kumar Sarkar, Satyendra Singh Yadav
Lecture Notes in Electrical Engineering, 2024
A Framework for Enhancing Accuracy in AI Generated Text Detection Using Ensemble Modelling
Kush Aggarwal, Sahib Singh, Parul, Vipin Pal, Satyendra Singh Yadav
2024 IEEE Region 10 Symposium Tensymp 2024, 2024
Optimizing Power Allocation to Maximize User Fairness in IRS-Aided NOMA Networks
Debbarni Sarkar, Yogita, Vipin Pal, Satyendra Singh Yadav, Sarat Kumar Patra
2024 IEEE 21st India Council International Conference Indicon 2024, 2024
TDRA: Transformer-Based Deep Recurrent Architecture for Automatic Modulation Classification Pertinent to Intelligent-Reflecting-Surface-Assisted Internet of Things Networks
Debbarni Sarkar, Yogita, Satyendra Singh Yadav, Linga Reddy Cenkeramaddi, Om Jee Pandey
IEEE Internet of Things Journal, 2024
Characteristics Analysis of 2-Bit Digitally Time-Coded Programmable Metasurface Using Vector Synthesis Approach
Sunanda Mukhopadhyay, Kartikey Gupta, Anjali Kashyap, Abhishek Sarkhel, Satyendra Singh Yadav
2024 IEEE International Students Conference on Electrical Electronics and Computer Science Sceecs 2024, 2024
An Efficient Ensemble Deep Learning Model-based Signal Detection in 6G Wireless Communication
Vineet Malewar, Tanisha Kant, Debbarani Sarkar, Vipin Pal, Satyendra Singh Yadav
2024 Global Conference on Communications and Information Technologies Gccit 2024, 2024
Maximizing Coverage and Energy Conservation in B5G Networks Using Hexagonal Tiling to Deploy FT-S2ES
Vaibhav Tiwari, Chandrasen Pandey, Satyendra Singh Yadav, Diptendu Sinha Roy, Om Jee Pandey, Linga Reddy Cenkeramaddi
IEEE Open Journal of the Communications Society, 2024
BAT: Barabasi-Albert With Topsis Scale-Free Topology Evolution for Load-Balanced WSNs
Ikkurthi Bhanu Prasad, Yogita, Satyendra Singh Yadav, Neeraj Kumar, Vipin Pal
IEEE Sensors Journal, 2023
Intelligent Reflecting Surface Aided NOMA-HARQ Based IoT Framework for Future Wireless Networks
Debbarni Sarkar, Satyendra Singh Yadav, Vipin Pal, Yogita, Neeraj Kumar
IEEE Transactions on Vehicular Technology, 2023
Performance Evaluation of IRS Assisted HARQ aided MIMO Wireless Network over Different Fading Channels
Debbarni Sarkar, Satyendra Singh Yadav, Vipin Pal, Sarat Kumar Patra
2023 IEEE 20th India Council International Conference Indicon 2023, 2023
Fuzzy Clustering based Cluster Head Selection for IoT enabled WSNs
Proceedings of the 17th Indiacom 2023 10th International Conference on Computing for Sustainable Global Development Indiacom 2023, 2023
Analysis of GFDM in generalized η−μ fading channel: A simple probability density function approach for beyond 5G wireless applications
Shravan Kumar Bandari, Satyendra Singh Yadav, V.V. Mani
AEU International Journal of Electronics and Communications, 2022
Machine Learning-Based Framework to Predict Finger Movement for Prosthetic Hand
Gagan Kumar, Satyendra Singh Yadav, Yogita, Vipin Pal
IEEE Sensors Letters, 2022
Application of machine learning framework for next-generation wireless networks: Challenges and case studies
Satyendra Singh Yadav, Shrishail Hiremath, Pravallika Surisetti, Vijay Kumar, Sarat Kumar Patra
Handbook of Intelligent Computing and Optimization for Sustainable Development, 2022
Efficient Cloudlet Allocation to Virtual Machine to Impact Cloud System Performance
Lizia Sahkhar, Bunil Kumar Balabantaray, Satyendra Singh Yadav
International Journal of Information System Modeling and Design, 2022
Analysis of image forgery detection using convolutional neural network
Chiluveru Gnaneshwar, Manish Kumar Singh, Satyendra Singh Yadav, Bunil Kumar Balabantaray
International Journal of Applied Systemic Studies, 2022
An Optimized Polynomial Perceptron Network based Adaptive Filter for Non-linear Active Noise Control
Shaktinarayana Mishra, Prachitara Satapathy, Satyendra Singh Yadav, P. K. Dash
2nd Odisha International Conference on Electrical Power Engineering Communication and Computing Technology Odicon 2022, 2022
Detecting Sinkhole Attacks in IoT-Based wireless Sensor Networks Using Distance From Base Station
Koushik Mondal, Satyendra Singh Yadav, Vipin Pal, Akhilendra Pratap Singh, Yogita Yogita, Mangal Singh
International Journal of Information System Modeling and Design, 2022
HLBC: A Hierarchical Layer-Balanced Clustering Scheme for Energy Efficient Wireless Sensor Networks
Ikkurthi Bhanu Prasad, Yogita, Satyendra Singh Yadav, Vipin Pal
IEEE Sensors Journal, 2021
Analysis of the universal gates based on the comparative factors of delay propagation, average power dissipation and logical effort
Vedanshu Kuwal, Satyendra Singh Yadav, Anup Dandapat
2021 2nd International Conference for Emerging Technology Incet 2021, 2021
A Node Overhaul Scheme for Energy Efficient Clustering in Wireless Sensor Networks
Jaspreet Singh, Satyendra Singh Yadav, Vinay Kanungo, Yogita, Vipin Pal
IEEE Sensors Letters, 2021
Performance Evaluation of Visible Light Communication System based on Optical Power Distribution with Channel Delay Spread and SNR
Mangal Singh, Saurav Gupta, Satyendra Singh Yadav, Vipin Pal, Sarat Kumar Patra
2021 Advanced Communication Technologies and Signal Processing Acts 2021, 2021
Retraction:An Ensemble Deep Learning Model for Automatic Modulation Classification in 5G and Beyond IoT Networks
Chirag Roy, Satyendra Singh Yadav, Vipin Pal, Mangal Singh, Sarat Kumar Patra, G. R. Sinha
Computational Intelligence and Neuroscience, 2021
Fast block distributed CUDA implementation of the Hungarian algorithm
Paulo A.C. Lopes, Satyendra Singh Yadav, Aleksandar Ilic, Sarat Kumar Patra
Journal of Parallel and Distributed Computing, 2019
Parallel Resource Allocation and Subcarrier Assignment for Downlink OFDMA
Satyendra Singh Yadav, Paulo Alexandre Crisóstomo Lopes, Sarat Kumar Patra
IETE Technical Review Institution of Electronics and Telecommunication Engineers India, 2019
Hungarian algorithm for subcarrier assignment problem using GPU and CUDA
Satyendra Singh Yadav, Paulo Alexandre Crisóstomo Lopes, Aleksandar Ilic, Sarat Kumar Patra
International Journal of Communication Systems, 2019
WSN assisted modulation detection with maximum likelihood approach, suitable for non-identical Rayleigh channels
Sudhanshu Arya, Satyendra Singh Yadav, Sarat Kumar Patra
International Conference on Recent Innovations in Signal Processing and Embedded Systems Rise 2017, 2018
A low-complexity suboptimal algorithm for joint subcarrier assignment in downlink OFDMA system
Satyendra Singh Yadav, Paulo A C Lopes, Sarat Kumar Patra
International Conference on Recent Innovations in Signal Processing and Embedded Systems Rise 2017, 2018
Computational complexity analysis of PTS technique under graphics processing unit
Satyendra Singh Yadav, Prasanta Kumar Pradhan, Sarat Kumar Parra
Proceedings of the 2015 3rd International Conference on Computer Communication Control and Information Technology C3it 2015, 2015
Performance evaluation of STBC-OFDM WiMAX system using graphics processing unit (GPU)
Satyendra Singh Yadav, Sarat Kumar Patra
2014 International Conference on High Performance Computing and Applications Ichpca 2014, 2015
PAPR reduction in OFDM systems
Prasanta Kumar Pradhan, Satyendra Singh Yadav, Sarat Kumar Patra
11th IEEE India Conference Emerging Trends and Innovation in Technology Indicon 2014, 2015
LTE physical layer implementation using GPU based high performance computing
Sangeeta Bhattacharjee, Satyendra Singh Yadav, Sarat Kumar Patra
Proceedings of 2014 IEEE International Conference on Advanced Communication Control and Computing Technologies Icaccct 2014, 2015

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