Efficient Wireless Communication Research Articles

Overview of Visible Light Communication: Past, Present, and Future

Visible light communication (VLC) is an efficient wireless communication with great development prospects, which is closely related to our daily lives especially for indoor applications. This paper first introduced the development process of VLC, and some significant milestones were emphasized. Then some key technologies, including OOK, VPPM, CSK, OFDM, PWM, were mentioned to provide readers with a deeper understanding of the working principle of VLC. In addition, the paper discussed some prospects of VLC, as well as its practical applications classified based on technical principles. Moreover, the author also pointed out the current difficulties and challenges, specifically mentioning the difficulties faced by OFDM technology in VLC system and its current development process. Some suggestions were proposed for future advancement. With continuous exploration and research, VLC will flourish in future wireless communications.

Application of machine learning algorithms in resource allocation for wireless communications

Abstract. The accelerated advances of wireless communication technologies in recent years has highlighted the necessity of efficient resource allocation in 5G and upcoming 6G networks, particularly in large-scale, high-density network implementations such as the Internet of Things (IoT) and ultra-dense cellular networks. The application of machine learning offers a number of significant advantages over traditional resource allocation algorithms, including enhanced adaptability, robustness, scalability, and predictive power. Therefore, the paper aims to examine the process of selecting the optimal machine learning algorithm for a specific resource management task. To this end, it provides an overview of the fundamental concepts of machine learning, including deep reinforcement learning (DRL), graph neural networks (GNN), and joint learning. Furthermore, this paper examines the potential applications of machine learning in the field of wireless resource management. The research presented in this paper provides a crucial theoretical foundation and guidance for further exploration and application of machine learning capabilities in the domain of wireless communication resource management. Overall, the research elucidates the potential of machine learning in wireless communication resource management and its applications, thereby advancing knowledge in this field and providing valuable references for the development of efficient and intelligent wireless communication networks.

Navigating urban congestion: A Comprehensive strategy based on an efficient smart IoT wireless communication for PV powered smart traffic management system.

Egypt faces extreme traffic congestion in its cities, which results in long travel times, large lines of parked cars, and increased safety hazards. Our study suggests a multi-modal approach that combines critical infrastructure improvements with cutting-edge technologies to address the ubiquitous problem of traffic congestion. Assuring vehicles owners of their timely arrival, cutting down on fuel usage, and improving communication using deep learning approach and optimization algorithm within the potential of IoT enabled 5G framework are the main goals. The traffic management system incorporates detection cameras, Raspberry Pi 3 microcontroller, an Android application, cloud connectivity, and traditional traffic lights that are powered using PV modules and batteries to secure the traffic controllers operation in case of grid outage and assure service continuity. The model examines the difficulties associated with Internet of Things (IoT) communication, highlighting possible interference from device-to-device (D2D) devices and cellular user equipment. This all-encompassing strategy aims to reduce fuel consumption, increase road safety and improve traffic efficiency. The model predicts a significant increase in Egypt's urban mobility by utilizing the possibilities of IoT and 5G technologies, which would improve Egypt's towns' livability and efficiency. The goal of this paper is to modernize Egypt's traffic management system and bring it into compliance with global guidelines for intelligent transportation networks.

Performance improvement of microLED‐to‐microLED visible light communication using reverse bias

AbstractLED‐to‐LED visible light communication (VLC), which uses LEDs not only for the transmitter but also for the receiver, is being studied as an efficient optical wireless communication technology that uses LED lighting infrastructure. In this paper, we investigate microLED‐to‐LED VLC, which uses microLEDs as both the transmitter and receiver. In particular, we conducted a study to improve the performance of microLED‐to‐microLED VLC. For this, we measured the performance depending on the transmitter and receiver LED color combination. In addition, the effects of zero bias and reverse bias at the receiver LED were investigated. We also investigated the improvement in the reverse bias when applying a transimpedance amplifier to the receiver LED. Finally, we experimentally demonstrated a data rate of 360 kbps in the microLED‐to‐microLED VLC.

Revolutionizing MANET Route Discovery with INTSM: An Innovative Load Balancing Approach

Communication challenges in ad hoc networks arise due to the mobility of nodes, causing frequent changes in connections and locations. Maintaining network equilibrium to prevent node overload and underutilization is crucial. However, imposing static behaviors on nodes to improve performance can lead to delays, especially in core nodes. Addressing these issues, this research proposes the Intermediate Node Traffic Sharing Model (INTSM) for ad hoc networks. INTSM prioritizes congestion control and load balancing during route discovery, aiming to optimize network resource utilization and traffic distribution, thereby reducing packet delays. The model employs dynamic traffic sharing algorithms that consider real-time network conditions, enabling nodes to adjust their behaviour adaptively. This approach minimizes congestion by distributing traffic loads more evenly across the network, preventing bottlenecks at central nodes. Additionally, INTSM incorporates predictive analysis to foresee potential congestion points and reroute traffic proactively, enhancing overall network stability and performance. Extensive simulations demonstrate that INTSM significantly reduces average packet delay and improves throughput compared to traditional routing protocols. The results highlight the model's efficacy in diverse scenarios, including high mobility and varying traffic loads, proving its robustness and scalability. The primary objective of this study is to enhance navigation and equilibrium mechanisms to improve the performance of ad hoc networks, contributing to more reliable and efficient wireless communication systems. The findings of this research have significant implications for the design of future ad hoc networks, particularly in applications requiring high reliability and quick adaptation to changing network conditions, such as disaster recovery, military operations, and mobile sensor networks. By addressing the critical challenges of congestion control and load balancing, INTSM offers a promising solution to enhance the resilience and efficiency of ad hoc networks.

Enhancing Detection Frequency and Reducing Noise Through Continuous Structures via Release-Controlled Transfer Toward Light-Based Wireless Communication.

Organic photodetectors (OPDs) have received considerable attention owing to their superior absorption coefficient and tunable bandgap. The introduction of bulk-heterojunction (BHJ) structure aims to maximize charge generation, however, its response speed is constrained by the random distribution of donor and acceptor. Herein, a multiple-active layer design consisting of a single acceptor layer and a bulk-heterojunction layer (A/BHJ structure) is introduced, which combines the benefits of both the planar junction and the BHJ, improving photo-sensing. A transfer process is employed for this structure, which involves calculating the energy release rate at each interface, considering temperature and velocity. Consequently, the OPD with the A/BHJ structure is successfully fabricated through transfer printing, resulting in reduced dark current, superior detectivity (1.06 × 1013 Jones), and rapid response, achieved by creating a high hole injection barrier and suppressing trap sites within the interfaces. By thoroughly investigating charge dynamics in the structure, the A/BHJ structure-based OPD attains large bandwidth detection with high signal-to-noise. An efficient wireless data communication system with digital-to-analog conversion is showcased using the A/BHJ structure-based OPD.

Research on extremely low frequency electromagnetic wave model and simulation in wellbore communication

Over recent years, as digitalization and intelligence in oil wellbore have increased, so have the stricter requirements for wireless communication technology in terms of distance, accuracy, and portability. As a result, it’s necessary to rely on more advanced and efficient wireless communication technologies to meet the industry’s needs. However, traditional communication technologies such as cables and optical fibers have inherent shortcomings in construction, data interpretation, and cost. ELF electromagnetic waves are an ideal solution for communication in complex wellbore conditions due to long-distance communication and strong penetration capabilities, making it a highly effective option. Based on the theory of network splitting, this paper establishes a polygonal multiple-delays uncertainty coupled complex network model of ELF electromagnetic waves propagating through the casing in layered media and designs a controller, including expressions for the intensity of the magnetic and electric fields in different directions, and the propagation and distribution characteristics in different media. We determined that the optimal transmitting frequency of ELF electromagnetic waves under general conditions is 12.7 Hz. Based on field experiments, we verified that ELF electromagnetic waves can enable wireless wellbore communication within 1500 m without relays. We also analyzed the impact of casing thread deformation on ELF electromagnetic wave propagation due to high-temperature and high-pressure environments. We used simulation experiments to solve the distribution relationship between the electric and magnetic fields of the solenoids through casing and strata, as well as the coupling coefficients between the transmitting and receiving solenoids, and explore how different transmitting frequencies affect the efficiency of signal propagation. Both theories and experiments have verified the correctness of the model, and have also demonstrated the reliability and continuity of using ELF electromagnetic waves to achieve wireless wellbore communication, which provides a theoretical basis and feasibility for subsequent engineering applications.

BRMECQN: Design of an efficient integration of Bioinspired Routing Model with Energy efficient Clustering for high QoS Wireless Networks

In this dynamic domain of communication in wireless network technology, the need for advanced models that boost the Quality of Service (QoS) parameters concerning energy efficiency, speed, throughput, packet delivery ratio, and minimization of jitter is of prime concern. Traditional routing and clustering methods in wireless networks are often confronted with limitations such as suboptimal resource utilization, reduced energy efficiency, and lower QoS metrics. In this regard, the present work introduces an innovative integration of bioinspired routing models with energy-efficient clustering to enhance the performance of wireless networks. A novel Fan-Shaped Clustering approach is employed in the proposed model for a proper grouping of the network nodes, which can reduce the energy consumption and enhance the load balancing across the network. The model performs a further integration of Elephant Herding Optimization and Bat Optimization algorithms following the clustering. This integration has been done to develop an optimal route finding mechanism between the clustered nodes through its bioinspired approach, to utilize the global search capability of Elephant Herding Optimization, and the proficiency of Bat Optimizations in local searches. The proposed model, when tested empirically on different configurations of networks, presents significant improvements over methods in practice. The results suggest a 10.5% improvement in energy efficiency, an improvement in speed of 8.3%, a rise in throughput of 3.5%, an improvement in Packet Delivery Ratio of 4.5%, and a reduction in jitter of 1.9%. These have been substantial improvements indicating that the proposed model overcomes the limitations of the existing ones and at the same time places a new benchmark in the performance of wireless networks. The impact of this work is immense, providing a scalable and efficient solution for next-generation wireless networks. This integration of bioinspired algorithms in the routing and clustering of the network shall open new avenues for research and development into the field with the potential of more resilient, efficient, and high-performing wireless communication systems. This work, therefore, adds immense impetus to the development of wireless network technologies to uphold higher QoS and better resource management in an era of ever-growing digital communication demands.

Clarity in Wireless Quantum Communication: Exploring Explainable AI for Signal Modulation Classification

The advent of artificial intelligence (AI) and edge computing technologies has ushered in a new era for automatic modulation classification (AMC), with a particular focus on deep learning (DL)-based approaches. These AI-based AMC systems, deployed at edge devices, have shown remarkable advancements in recognizing and classifying a wide range of wireless signals. However, a significant challenge in this domain lies in the lack of adequate explanations for the models employed, which, in turn, hampers model accuracy and training efficiency. Consequently, the practical applications and further enhancements of these models are constrained. To address this limitation, researchers have started to explore interpretable methods for the technical analysis of DL-based AMC systems. In this paper, we delve into the subject, leveraging recent developments in interpretable methods, to provide a comprehensive review of applicable techniques and to outline the existing research challenges in the field of interpretable AMC. Moreover, we introduce a novel interpretable AI-based AMC framework designed to augment the interpretability of AMC outcomes. This framework achieves this by elucidating the contribution of wireless signal features to the training process of DL networks. In addition, we explore the potential impact of quantum computing on AMC systems. Quantum computing, with its ability to process complex computations at unprecedented speeds, offers a promising avenue for enhancing the efficiency and accuracy of AMC. By integrating quantum algorithms with AI-based AMC frameworks, it is possible to significantly improve the performance of wireless signal classification, especially in environments with high signal variability and noise. Our experimental results demonstrate that the proposed approach possesses the capacity to unravel the classification mechanisms hidden within opaque auto-modulated classification networks. Furthermore, it exhibits the potential to facilitate the training of networks on edge devices with reduced energy consumption and enhanced classification accuracy, thereby addressing critical challenges in the field of wireless signal classification. Additionally, the integration of quantum computing techniques holds the promise of further advancing the capabilities of AMC systems, paving the way for more robust and efficient wireless communication technologies.

Passive continuous-variable quantum key distribution based on orthogonal frequency-division multiplexing in the terahertz band

We propose a passive continuous-variable quantum key distribution protocol based on multicarrier multiplexing technology in the terahertz band. In this paper, we realize the superposition of multipath coherent states by inverse Fourier transform and passive modulation. At the receiving end, the coherent states of the subcarriers are separated by quantum Fourier transform, and the keys are obtained in parallel by a homodyne (heterodyne) detector and post-processing. In addition, we derive the security bounds of the protocol and evaluate the performance in indoor environments and intersatellite links. Furthermore, we consider finite-size effects and propose tighter agreement constraints, which are more practical than those obtained in the asymptotic limit. This work will provide an effective way to build efficient wireless quantum communication networks.

A highly flexible and low-profile metasurface antenna for wearable WBAN systems

Recent years have witnessed the popularity of wearable devices. These devices use Wireless Body Area Networks (WBANs) for healthcare monitoring, personalized tracking, and various other applications. An important component of these devices is the wearable antenna that provides reliable and efficient wireless communication between body-worn sensors and external devices. This paper presents a novel metasurface-based wearable antenna for WBAN applications. By incorporating metasurfaces into the antenna design, achieving enhanced performance is possible. The design was tested using four flexible substrates: wool, paper, fleece, and felt. The paper substrate was chosen because of its superior performance. The dimensions of the antenna are 30 mm x 20 mm, and a 5 ×3 metasurface is used, whose unit cell comprises a square patch. Simulation and experimental results have been performed to measure the radiation pattern, return loss, and gain. A good corroboration is observed between the measured and simulated results. The antenna resonates at three frequencies and offers wide-band resonance characteristics when backed by the metasurface. The peak gain of the antenna without the metasurface was less than 4 dB, but when backed by the metasurface, the peak gain was enhanced to approximately 6 dB. Also, it has been observed that the designed antenna’s performance is not significantly affected by the radius of curvature, making it ideal for on-body measurements. This design can inspire further research on low-cost paper substrate-based antennas for WBAN applications.

Adaptable Hybrid Beamforming with Subset Optimization Algorithm for Multi-User Massive MIMO Systems.

The exploiting of hybrid beamforming (HBF) in massive multiple-input multiple-output (MIMO) systems can enhance the system's sum rate while reducing power consumption and hardware costs. However, designing an effective hybrid beamformer is challenging, and interference between multiple users can negatively impact system performance. In this paper, we develop a scheme called Subset Optimization Algorithm-Hybrid Beamforming (SOA-HBF) that is based on the subset optimization algorithm (SOA), which effectively reduces inter-user interference by dividing the users set into subsets while optimizing the hybrid beamformer to maximize system capacity. To validate the proposed scheme, we constructed a system model that incorporates an intelligent reflecting surface (IRS) to address obstacles between the base station (BS) and the users set, enabling efficient wireless communication. Simulation results indicate that the proposed scheme outperforms the baseline by approximately 8.1% to 59.1% under identical system settings. Furthermore, the proposed scheme was applied to a classical BS-users set link without obstacles; the results show its effectiveness in both mmWave massive MIMO and IRS-assisted fully connected hybrid beamforming systems.

Behind the Door: Practical Parameterization of Propagation Parameters for IEEE 802.11ad Use Cases

The integration of the 60 GHz band into the IEEE 802.11 standard has revolutionized indoor wireless services. However, this band presents unique challenges to indoor wireless communication infrastructure, originally designed to handle data traffic in residential and office environments. Estimating 60 GHz signal propagation in indoor settings is particularly complicated due to dynamic contextual factors, making it essential to ensure adequate coverage for all connected devices. Consequently, empirical channel modeling plays a pivotal role in understanding real-world behavior, which is characterized by a complex interplay of stationary and mobile elements. Given the highly directional nature of 60 GHz propagation, this study addresses a seemingly simple but important question: what is the impact of employing highly directive antennas when deviating from the line of sight? To address this question, we conducted an empirical measurement campaign of wireless channels within an office environment. Our assessment focused on power losses and distribution within an angular range while an indoor base station served indoor users, simulating the operation of an IEEE 802.11ad high-speed WLAN at 60 GHz. Additionally, we explored scenarios with and without pedestrian movement in the vicinity of wireless terminals. Our observations reveal the presence of significant antenna lobes even in obstructed links, indicating potential opportunities to use angular combiners or beamformers to enhance link availability and the data rate. This empirical study provides valuable information and channel parameters to simulate 60 GHz millimeter wave (mm-wave) links in indoor environments, paving the way for more efficient and robust wireless communication systems.

Research and Application of Visible Light Communication Technology

In recent years, the rapid growth of mobile devices and wireless services has created a significant demand for RF-based technologies. Among the various emerging wireless communication forms, Visible Light Communications (VLC) stands out as a potentially transformative technology that not only complements RF communications but also introduces innovative possibilities for mobile wireless device applications. VLC utilizes visible light for communication, offering high-speed data transmission, improved energy efficiency, and enhanced communication security and privacy. This article thoroughly explores VLC, discussing its core concepts, fundamental principles, and essential technologies that define this rapidly developing field. By providing insights into the intricacies of VLC, readers can gain a better understanding of its mechanisms and capabilities. The exploration also extends to elucidating the diverse application scenarios where VLC can be effectively applied, showcasing its versatility and potential impact on various sectors. This comprehensive survey not only presents the current state of VLC but also predicts future development trends, providing a forward-looking perspective on the evolution of this technology. As the demand for efficient and secure wireless communications continues to rise, VLC emerges as a promising frontier, poised to play a pivotal role in shaping the landscape of communication technologies in the years to come.

Design optimization for microstrip antennas based on polymethyl methacrylate (PMMA) substrate and carbon nanotube (CNT) conductive material in sub-6 Ghz band

Abstract Background The rapid expansion of modern smart applications, demanding faster data transfer and extensive bandwidth, has prompted the development of new-generation networks like 5G and 6G. These networks encompass additional frequency bands such as sub-6 GHz, millimeter waves, and terahertz bands to meet the growing bandwidth requirements. However, despite the substantial bandwidth available in these bands, several challenges must be addressed to overcome unfavorable propagation characteristics. Moreover, numerous applications necessitate wireless devices with antennas that exhibit high flexibility and exceptional radiation responses, particularly when subjected to bending effects. This requirement highlights the importance of polymers-based antennas that can adapt to changing conditions while maintaining optimal performance. The present comprehensive study delves into the performance evaluation of rectangular and circular microstrip antennas utilizing PMMA (polymethyl methacrylate) polymer substrate with varying thicknesses. Results Notably, CNTs (Carbon Nanotubes) are employed as an alternative to traditional copper for the conductive part and ground plane. Both PMMA-based antennas, integrated with CNTs, exhibit a compact footprint of 27.8 × 47.8 × 1.5 mm3 for the circular antenna and 22.8 × 39.5 × 1.5 mm3 for the rectangular antenna. Impressively, the realized gain of both antennas surpasses 5 dBi, demonstrating robust performance in both flat and bending scenarios across different substrate thicknesses. Conclusions The rectangular antenna achieves a bandwidth of approximately 200 MHz, while the circular microstrip antenna showcase annotable bandwidth of 500 MHz. These exceptional outcomes position the two microstrip antennas as highly suitable for a diverse range of emerging applications within the sub-6 GHz band (the frequency range below 6 GHz in the radio spectrum). Thus, the combination of PMMA substrate, CNTs and the compact form factor of the antennas presents a compelling solution for meeting the demands of modern applications requiring efficient wireless communication with enhanced performance and bandwidth.

Reconfigurable Intelligent Surfaces for Beamforming in Upcoming Wireless Communications

Reconfigurable Intelligent Surfaces (RIS), also known as Intelligent Reflecting Surfaces (IRS), represent a groundbreaking advancement in wireless communication technology, enabling unprecedented control over electromagnetic (EM) wave propagation. Composed of numerous passive or active elements constructed from metasurfaces, RIS can dynamically alter their electromagnetic responses to optimize signal reflection, refraction, and scattering. These elements, capable of manipulating the phase, amplitude, and polarization of incoming waves, are centrally controlled through sophisticated algorithms that adapt to real-time environmental changes and communication requirements. RIS technology promises significant improvements in wireless communication by extending coverage, enhancing signal quality, managing interference, boosting energy efficiency, and improving security. Additionally, RIS can facilitate precise localization and sensing applications. Despite the high initial implementation costs and the need for complex control mechanisms and infrastructure compatibility, the potential benefits of RIS in creating efficient, secure, and adaptive wireless communication environments underscore its transformative impact on the field.

Performance Analysis of Combining Beamforming and ZF/MMSE-SIC Equalization Techniques for MIMO DWPT-COFDM Systems

Abstract This study explores the enhancement of wireless communication through the integration of OFDM with MIMO and advanced techniques like COFDM, adaptive MIMO, and beamforming. It evaluates a 2×2 and 4×4 MIMO-DWPT-COFDM system, considering modulation (BPSK and QPSK) and equalization (ZF-SIC and MMSE-SIC) over a Rayleigh fading channel. MATLAB results reveal that more antennas, BPSK modulation, and MMSE-SIC equalization significantly improve BER performance. Specifically, for a BER of 10−4, the 2×2 MIMO system requires E b / N 0 values of 10.4 (MMSE-SIC) and 11.4 (ZF-SIC), while the 4×4 MIMO system needs 5.5 (MMSE-SIC) and 5.9 (ZF-SIC). These findings emphasize the need for thoughtful system design and parameter optimization in achieving reliable and efficient wireless communication.

WIRELESS TRAFFIC AND ROUTING ENHANCEMENT USING EMPEROR PENGUIN OPTIMIZER GUIDED BY CONDITIONAL GENERATIVE ADVERSARIAL NETS

The escalating demand for efficient wireless communication systems has prompted researchers to explore innovative solutions to optimize traffic flow and routing. The existing wireless communication infrastructure faces challenges such as congestion, latency, and suboptimal routing, impeding the seamless transmission of data. Traditional optimization approaches fall short in adapting to dynamic network conditions, necessitating the exploration of advanced methodologies. Despite recent advancements in optimization techniques, a notable research gap exists in the integration of bio-inspired algorithms like the Emperor Penguin Optimizer with machine learning models such as Conditional Generative Adversarial Nets for the purpose of wireless traffic and routing enhancement. Bridging this gap is crucial for achieving adaptive and robust wireless communication systems. This study addresses the challenges posed by the dynamic nature of wireless networks, aiming to enhance their performance through the synergistic application of the Emperor Penguin Optimizer (EPO) and Conditional Generative Adversarial Nets (CGANs). This research leverages the inherent strengths of the EPO, inspired by the collective foraging behavior of emperor penguins, to dynamically optimize the wireless network parameters. Concurrently, CGAN are employed to intelligently learn and adapt routing strategies based on real-time network conditions. The symbiotic integration of these two methodologies creates a powerful framework for adaptive wireless traffic and routing. The results indicate a significant improvement in traffic flow, reduced latency, and optimized routing paths in comparison to conventional methods. The EPO-CGAN framework demonstrates adaptability to varying network conditions, showcasing its potential to revolutionize wireless communication systems.

Design and Simulation of Elliptical Shaped Microstrip Patch Antenna Using HFSS

Abstract: The elliptical patch antenna presents a comprehensive study on the design, fabrication, and performance analysis of an operating at 2.4 GHz, employing FR4 substrate material. The elliptical shape is chosen for its unique radiation characteristics and compact form factor, making it suitable for integration into modern wireless communication systems. The design process involves careful consideration of key parameters, including patch dimensions, feedline structure, and ground plane geometry. Advanced simulation tools, such as electromagnetic simulators, are employed to optimize the antenna's performance, achieving desirable characteristics such as low return loss and enhanced bandwidth. Utilizing FR4 as the substrate material offers several advantages, including costeffectiveness, ease of procurement, and compatibility with standard PCB manufacturing processes. The dielectric properties of FR4 are thoroughly analyzed and incorporated into the antenna design process to ensure accurate simulation results. The proposed elliptical patch antenna has promising applications in various wireless communication systems, including Wi-Fi, Bluetooth, and IoT devices, operating in the 2.4 GHz frequency band. Its compact size and robust performance make it a compelling choice for space-constrained and high-performance wireless communication applications. This contributes valuable insights into the design and optimization of patch antennas, particularly those using FR4 substrates, and serves as a foundation for the development of efficient and cost-effective wireless communication solutions in the 2.4 GHz spectrum.

Error resilient wireless video transmission via parallel processing using puncturing rule enabled coding and decoding

The innovation in wireless video transmission lies in the methodology's holistic approach, which combines parallel processing, puncturing rule-enabled coding, comprehensive error correction, and focused video frame reconstruction. The methodology includes several stages, including video frame processing, channel coding, error simulation, and Viterbi decoding, all of which are optimized for improved performance. Parallel processing is used at each stage to improve computational efficiency. Convolutional encoding is used concurrently, with a puncturing rule to tailor the encoding process for individual packets. Following that, a binary symmetric channel model is used to simulate bit errors, allowing the system's error-resilient characteristics to be evaluated. Beyond the analysis performed on previously studied videos, the proposed approach is thoroughly evaluated across three distinct video datasets. Furthermore, the study delves into BER analysis, encompassing various error probabilities and employing incremental redundancy. This investigation sheds light on the system's robustness in correcting errors in a variety of error scenarios. Throughput measurements provide important information about the achieved data transmission rate during successful receptions, whereas the elapsed time metric measures the overall efficiency of the transmission process. Furthermore, the proposed method assesses Mean Squared Error (MSE) at 0.48 and Peak Signal-to-Noise Ratio (PSNR) at 51.30 dB across the entire operational process. The combined findings highlight the proposed approach's superiority, positioning it as a promising solution for robust and efficient wireless video communication. This results in a more stable and efficient gearbox system, distinguishing it from existing system.