Dr. Avik Banerjee

@mits.ac.in

Assistant Professor in the department of Electronics and Communication Engineering
Madanapalle Institute of Technology and Science

Dr. Avik Banerjee


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https://researchid.co/avikbanerjee

RESEARCH INTERESTS

Cognitive radio, Cooperative Spectrum Sensing, Energy Harvesting, Physical Layer Security.
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Scopus Publications

Scopus Publications

  • Residual Energy Maximization in RIS Aided Cooperative Spectrum Sensing with PUEA: Relative Performance in PS and TS Mode
    Avik Banerjee, Santi P. Maity, Veerapu Goutham
    IEEE Access, 2025
    In this work, a performance comparison on radio frequency (RF) energy harvesting (EH) in power splitting (PS) and time switching (TS) modes in reconfigurable intelligent surfaces (RIS) aided cooperative spectrum sensing (CSS) is made. CSS model considers multiple primary users (PUs), however, one of them seems to be operative or not at a time along with a single PU emulation attacker (PUEA) node. Time frame comprises of sensing-reporting slots in CSS accompanied by EH. A distant dependent model of channel gain in RIS reflector is developed for calculating the harvested residual energy (RE). The primary objective is to maximize the total RE while meeting a predefined detection and false alarm probabilities of PU along with the individual secondary user’s (SU’s) energy causality constraint. The optimal values of sensing duration, power splitting factor (in PS) and amplifying gain are calculated through Lagrange method. Simulation results show the efficacy of the proposed work due to RIS on total RE highlighting a gain of 45% and 38.97% for PS and TS mode compared to the existing work while maintaining the above mentioned constraints. Performances of RE with the change in the placement of RIS near/far to PU (in presence or absence of PUEA) and the same near/far to PUEA are analyzed for both PS and TS mode. If PU transmit power is increased, the maximum value of RE for PS mode (both in presence and absence of PUEA) is achieved when RIS is placed near to the SU transmitter. The maximum value of RE for both PS and TS modes are found to be at the middle when RIS is moved from the latter position to nearer to the PUEA.
  • A Multi-Stage Hybrid Image Denoising Approach: A Comparative Study with Wavelet Transform and Edge Preservation
    Shreya, R Chithra, Sanchitha Y M, Avik Banerjee
    2025 9th International Conference on Computational System and Information Technology for Sustainable Solutions Csitss 2025, 2025
    Digital image denoising is a significant challenge in image processing. It affects visual quality and the tasks that follow. This paper introduces a new multi-stage hybrid image denoising method. We compare it with the Enhanced Discrete Wavelet Transform (EDWT) method by Tuba and Zivkovic. Our approach starts with spatial filtering, then uses ensemble wavelet denoising, follows with residual refinement, and ends with edgeaware blending. We carried out experiments on standard images that were corrupted by both Gaussian and Salt & Pepper noise at different levels. We evaluated performance using Peak Signal-to-Noise Ratio (PSNR), Structural Similarity Index Measure (SSIM), and Mean Squared Error (MSE), among other quality metrics. The results show that our multi-stage hybrid method consistently performs better in denoising. Specifically, it achieves an average PSNR of over 41 dB. It maintains an average SSIM of over 98% compared to the original image. Additionally, it reduces the MSE by more than 98% across all tested images and noise conditions. This method effectively preserves image details and structural integrity.
  • Secrecy Performance Analysis of UAV Jammer based Full-Duplex Relay assisted Overlay Cognitive Radio Network
    Jayanta Kumar Bag, Chanchal Kumar De, Avik Banerjee, Abhijit Chandra
    Proceedings of 2025 IEEE 4th Conference on Applied Signal Processing Aspcon 2025, 2025
    This study examines the performance of secrecy outages using the calculation of the secrecy outage probability (SOP) of secondary users in a cognitive radio network (CRN) communicating through a full-duplex relay network, using the overlay protocol. To improve SOP performance, we include an unmanned aerial vehicle (UAV) jammer, which is capable of transmitting jamming signals to resist eavesdroppers from stealing information from secondary transmitting users. The system performance gets enhanced by incorporating full-duplex (FD) relays, uses energy detection circuits to sense RF energy from PUs. The secondary network throughput is enhanced by optimizing the power allocation factors at the secondary transmitter, relay, and UAV-based jammer. A detailed mathematical analysis was carried out to derive closed-form expressions for the SOP and throughput, accounting for all sources of interference within the network. MATLAB simulations validate the analytical results on secrecy outage probability and demonstrate a noticeable variation in SOP performance compared to existing work.
  • SDN-IoCE for Intelligent Self-Powered Gas Sensor Monitoring
    Santi P. Maity, Avik Banerjee, Chinmay Chakraborty, Saranjit Singh
    IEEE Consumer Electronics Magazine, 2025
    Detection of harmful gases and their real-time monitoring in a closed as well as open environment find applications such as safety in industrial setting, health monitoring, air quality tracking, etc. This article discusses the issue in a framework of Internet of Consumer Electronics (IoCE). The model integrates Internet of Things (IoT)-based low cost self-powered sensors deployment for gas sensing, and Software Defined Network (SDN)-driven control, leading to SDN-IoCE. Reliable transmission of gas sensing data is essential and done through reconfigurable intelligent surface (RIS) aided underlay cognitive radio network (CRN). Radio frequency (RF) energy harvesting (EH) to be done for self-powering of sensor nodes. Two deep Q-networks (DQNs) are used where the first one ensures seamless connectivity on gas sensing data transmission while the other one performs its time-critical analysis. The proposed SDN-IoT architecture achieves 33 sec and 46 watt less values in delay/latency and energy consumption, respectively over existing work.
  • Deep Learning Based Optimal RIS Position Analysis for Energy Harvesting in Medical IoT Devices
    Himashree N R, Hamsaveni R, Jeevan T S, Ritik Kumar Singh, Likhitha S, R Likhitha, Avik Banerjee
    2025 9th International Conference on Computational System and Information Technology for Sustainable Solutions Csitss 2025, 2025
    Medical IoT devices for health monitoring require constant power and connectivity, yet they face challenges in complex indoor environments like hospitals due to signal blockages and energy constraints. This paper proposes a deep learning-based approach for determining the optimal position and phase shift of a Reconfigurable Intelligent Surface (RIS) to enhance both energy harvesting and communication throughput. Simulations using OpenEMS and Octave model signal behavior in a hospital-like scenario. A regression-based neural network is trained using TensorFlow to predict the optimal RIS configuration. Results demonstrate a nonlinear, positively correlated relationship between RIS parameters and performance metrics, enabling intelligent optimization of RIS for real-time health IoT applications.
  • Digital Twins for Human Organs Using Bioelectronic Data and CNN
    Manyu A K, Pramukh K, Subramanya G M, Lipika S, Shravan V, Shashank N, Avik Banerjee
    2025 9th International Conference on Computational System and Information Technology for Sustainable Solutions Csitss 2025, 2025
    Digital Twin (DT) technology has emerged as an effective solution to enhance monitoring, forecasting, and control of complex systems. Digital Twins create a virtual representation of physical assets in real-time; by continuously providing feedback, they can add an additional layer of reliability to our systems and minimize undesired or problematic behaviors over the entire life cycle of a system. Initially established as a concept in engineering and manufacturing, the idea has advanced to different domains such as healthcare and smart cities. Within medicine, combining Digital Twins with biofeedback systems can offer precision-based treatment, remote monitoring, and result in improved patient outcomes as we have access to real-time physiological data. In the context of cities, smart services derived from Digital Twin platforms are assuredly citizen centric as they address accessibility, trust, and efficiency in city operations. Therefore smart healthcare, as part of this digital evolution encompasses the integration of AI, IoT, and cloud-based solutions, all of which should enhance decision-making, service delivery, and sustain ability. Industry activity indicates that Digital Twins are heading toward mass adoption leveraged through advances in connectivity, data analytics, and modeling capabilities, but face challenges with limitations in system interoperability, data privacy and security, and achieving real-time synchronization. Regardless, Digital Twins are increasingly essential for smart infrastructures that reflect a future-proof precaution across industries.
  • RIS Aided Residual Energy: PS and TS Mode Harvesting in Cooperative Spectrum Sensing
    Avik Banerjee, Prabagarane Nagaradjane, Santi P Maity, Veerapu Goutham
    2024 Asian Conference on Communication and Networks Asiancomnet 2024, 2024
    This work studies performance comparison on radio frequency ($\\mathbf{R F}$) energy harvesting ($\\mathbf{E H}$) in power splitting (PS) and time-switching (TS) modes in reconfigurable intelligent surfaces (RIS)-aided cooperative spectrum sensing (CSS). CSS model considers multiple primary user (PU) nodes and a single PU emulation attacker (PUEA) node. A distant dependent model of reflected channel gain in RIS antenna is developed for calculating the harvested residual energy (RE). The primary objective is to maximize the total RE while meeting a predefined detection and false alarm probabilities of PU along with the individual secondary user’s (SU’s) energy causality constraint. Simulation results show the efficacy of the proposed work due to the involvement of RIS antenna on total RE, as gain of about 45% and 38.97% for PS and TS modes compared to the existing works while maintaining the above mentioned constraints. Performance of RE with the change in the placement of RIS antenna near/far to PU is analyzed for both PS and TS modes.
  • Jamming in Eavesdropping on Throughput Maximization in Green Cognitive Radio Networks
    Avik Banerjee, Santi P. Maity
    IEEE Transactions on Mobile Computing, 2023
    This work considers a cognitive radio (CR) network consisting of a set of CR transmit-receive node pairs, one fusion center (FC), multiple primary user emulation attack (PUEA) nodes, an eavesdropper ( <inline-formula><tex-math notation="LaTeX">$E_{av}$</tex-math></inline-formula> ) node and a set of friendly jammers used for protection of CR data transmission from eavesdropping. At the initial time slot of the frame, simultaneous energy harvesting (EH) and spectrum sensing are done through power splitting (PS) mode. CR transmit nodes then amplify and forward the sensed samples of both the primary user (PU) and the PUEA to the FC for cooperative spectrum sensing (CSS). Based on the CSS decision, CR transmit nodes either perform EH over the entire duration or make an opportunistic data transmission in time division mode. The closed form expressions of the optimal sensing duration, power allocation factor and transmit power for each secondary user (SU) are found. The sum secondary throughput of the network is maximized under the constraints of meeting the sensing reliability of the PU, individual energy causality for each SU and the best selected jammer, interference at the PU receiver, individual secondary and secrecy outage probability. Simulation results show a performance gain on the maximum value of the sum secondary throughput by <inline-formula><tex-math notation="LaTeX">$\sim$</tex-math></inline-formula> 17.56 and <inline-formula><tex-math notation="LaTeX">$\sim$</tex-math></inline-formula> 49.69 percent over the existing works.
  • PUEA Impact on Sensing and Throughput in RF Powered Cognitive Radio Networks
    Avik Banerjee, Santi P. Maity
    Advances in Intelligent Systems and Computing, 2021
  • Jamming on Throughput Improvement in Cognitive Radio Networks
    Avik Banerjee, Santi P. Maity
    International Symposium on Advanced Networks and Telecommunication Systems Ants, 2020
    This work considers a cognitive radio (CR) system model containing a set of transmit-receive node pairs, one fusion center (FC), one primary user emulation attack (PUEA) node, an eavesdropper node (Eav) and a set of jammers. The CR operation is governed by repetitive time frame wherein at the initial time slot, simultaneous energy harvesting (EH) and spectrum sensing (SS) are done through power splitting (PS) mode. Based on SS decision at the FC, CR transmitters and jammers either perform EH from primary user (PU) signal over the remaining slot or make an opportunistic data transmission. The sum secondary throughput is maximized under the constraints of SS reliability, energy causality of SU node and friendly jammer, interference at PU receiver, individual secondary and secrecy outage probability. Simulation results show $\\sim$ 4.5% and $\\sim$ 14.79% gain in sum secondary throughput and residual energy, respectively.
  • Residual Energy Maximization in Cognitive Radio Networks with Q-Routing
    Anal Paul, Avik Banerjee, Santi P. Maity
    IEEE Systems Journal, 2020
  • On Residual Energy Maximization in DF Cognitive Radio Networks with Multiple Eavesdroppers
    Avik Banerjee, Santi P. Maity
    IEEE Transactions on Cognitive Communications and Networking, 2020
  • Cognitive Radio Networks with Energy Harvesting and Eavesdropping-Emulation Resilience
    Avik Banerjee, Santi P. Maity
    2020 International Conference on Communication Systems and Networks Comsnets 2020, 2020
  • On Residual Energy Maximization in Cognitive Relay Networks with Eavesdropping
    Avik Banerjee, Santi P. Maity
    IEEE Systems Journal, 2019
  • On Residual Energy Maximization in Cooperative Spectrum Sensing with PUEA
    Avik Banerjee, Santi P. Maity
    IEEE Wireless Communications Letters, 2019
  • Spectrum sensing in cognitive vehicular networks for uniform mobility model
    Anal Paul, Priyatham Kunarapu, Avik Banerjee, Santi P. Maity
    Iet Communications, 2019
  • Throughput maximisation in cognitive radio networks with residual bandwidth
    Anal Paul, Avik Banerjee, Santi P. Maity
    Iet Communications, 2019
  • Joint cooperative spectrum sensing and primary user emulation attack detection in cognitive radio networks using fuzzy conditional entropy maximization
    Avik Banerjee, Santi P. Maity
    Transactions on Emerging Telecommunications Technologies, 2019
  • On outage minimization in relay assisted cognitive radio networks with energy harvesting
    Avik Banerjee, Santi P. Maity
    Ad Hoc Networks, 2019
  • On Throughput Maximization in Cooperative Cognitive Radio Networks With Eavesdropping
    Avik Banerjee, Santi Prasad Maity, Ritesh Kumar Das
    IEEE Communications Letters, 2019
  • On outage secrecy minimization using jammer selection in energy harvesting cognitive radio
    Avik Banerjee, Ritesh Kumar Das, Santi P. Maity
    Spcom 2018 12th International Conference on Signal Processing and Communications, 2018
  • On optimal sample checkpoint for energy efficient cooperative spectrum sensing
    Avik Banerjee, Santi P. Maity
    Digital Signal Processing A Review Journal, 2018
  • Joint Power Allocation and Route Selection for Outage Minimization in Multihop Cognitive Radio Networks with Energy Harvesting
    Avik Banerjee, Anal Paul, Santi Prasad Maity
    IEEE Transactions on Cognitive Communications and Networking, 2018
  • On outage secrecy minimisation in an energy harvesting relay assisted cognitive radio networks
    Avik Banerjee, Santi P. Maity, Subhabrata Roy
    Iet Communications, 2018
  • Residual energy maximization in cooperative spectrum sensing with energy harvesting
    Avik Banerjee, Santi P. Maity
    2017 23rd National Conference on Communications Ncc 2017, 2017
  • On energy minimization in cooperative spectrum sensing using LRT in presence of emulation attack
    Avik Banerjee, Santi P. Maity
    2016 IEEE International Conference on Advanced Networks and Telecommunications Systems Ants 2016, 2017
  • On residual energy maximization in energy harvesting cognitive radio network
    Avik Banerjee, Santi P. Maity, Subhabrata Roy
    IEEE Wireless Communications and Networking Conference Wcnc, 2017
  • Energy detection based cooperative spectrum sensing using fuzzy conditional entropy maximization
    Avik Banerjee, Santi P. Maity
    2014 IEEE International Conference on Advanced Networks and Telecommunication Systems Ants 2014, 2014
  • Fuzzy c-means clustering in energy detection for cooperative spectrum sensing in cognitive radio system
    Subhankar Chatterjee, Avik Banerjee, Tamaghna Acharya, Santi P. Maity
    Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2014