Communication Technology Systems Research Articles

Self‐attention convolutional neural network optimized with Remora Optimization Algorithm for energy aware resource management in Non‐orthogonal Multiple Access networks

SummaryNon‐orthogonal multiple access (NOMA) is an efficient technology for future wireless communication systems. The resource management on NOMA networks is flattering for improving energy efficiency (EE) of systems. Therefore, self‐attention convolutional neural network (SACNN) optimized with Remora Optimization Algorithm (ROA) for energy aware resource management in NOMA network (SACNN‐ROA‐EE) is proposed in this paper for solving user allocation, channel allocation, and power allocation problems. The Matching‐Coalition approach is considered to face the user allocation issue, and the SACNN is considered to face the channel allocation and power allocation problems. SACNN does not adopt any optimization methods to determine the optimal parameters in channel allocation and power allocation. Therefore, the ROA is applied to optimize the SACNN weight parameters. The proposed technique is activated in MATLAB, and its efficacy is analyzed with under performances metrics, such as minimum user rate, sum rate, energy, and spectral performance. The proposed SACNN‐ROA‐EE attains 24.35%, 27.84%, and 38.58% better sum rate and 27.45%, 43.28%, 30.56% better EE compared with existing methods, such as EE utilizing communication deep neural network optimized with power allocation optimization (PAO‐CDNN‐EE), EE under deep transfer deterministic policy gradient along deep deterministic policy gradient approach (DPPGA‐DTDPPG‐EE), and EE utilizing deep reinforcement learning with baseline algorithms (BA‐DRL‐EE), respectively.

Improving care pathways through BPM and telemedicine: an Italian study

PurposeThe future increase of chronic diseases in the world requires new challenges in the health domain to improve patients' care from the point of view of the organizational processes, clinical pathways and technological solutions of digital health. For this reason, the present paper aims to focus on the study and application of well-known clinical practices and efficient organizational approaches through an innovative model (TALIsMAn) to support new care process redesign and digitalization for chronic patients.Design/methodology/approachIn addition to specific clinical models employed to manage chronic conditions such as the Population Health Management and Chronic Care Model, we introduce a Business Process Management methodology implementation supported by a set of e-health technologies, in order to manage Care Pathways (CPs) digitalization and procedures improvement.FindingsThis study shows that telemedicine services with advanced devices and technologies are not enough to provide significant changes in the healthcare sector if other key aspects such as health processes, organizational systems, interactions between actors and responsibilities are not considered and improved. Therefore, new clinical models and organizational approaches are necessary together with a deep technological change, otherwise, theoretical benefits given by telemedicine services, which often employ advanced Information and Communication Technology (ICT) systems and devices, may not be translated into effective enhancements. They are obtained not only through the implementation of single telemedicine services, but integrating them in a wider digital ecosystem, where clinicians are supported in different clinical steps they have to perform.Originality/valueThe present work defines a novel methodological framework based on organizational, clinical and technological innovation, in order to redesign the territorial care for people with chronic diseases. This innovative ecosystem applied in the Italian research project TALIsMAn is based on the concept of a continuum of care and digitalization of CPs supported by Business Process Management System and telemedicine services. The main goal is to organize the different socio-medical activities in a unique and integrated IT system that should be sustainable, scalable and replicable.

Adoption of Contemporary Technologies Among Hotels in Zimbabwe: A Case of City Hotels in Harare

Numerous studies have shown that leading hotels of the world take a lead in implementing the latest trends in Information Communication Technologies (ICTs) systems. However, most of the hotels in Zimbabwe are usually reactive with the pace at which they are embracing and using the ICT systems. Hence, the study explores extant literature using the scoping review approach to explain the current technological developments shaping the hotel sub-sector. This research explores the tourism and hospitality industry from a global point of view, highlighting the pros and cons brought about by the hotel industry embracing modern technologies. The following objectives specifically guided the research: to explore level of adoption of new technologies usage in Harare hotels, to establish the merits and hindrances encountered by hoteliers in the adoption of new technologies by Harare hotels. Strategies that can be adopted by hotels in Zimbabwe to enhance the contribution of new technologies have been suggested. Hotels in Zimbabwe are aware of the benefits that are obtained through the adoption of new technologies such as: value creation, improved communication, low cost of production, and improved productivity among others. The findings of the study indicate that there is underutilization of ICT by Harare hotels due many challenges that include: limited investments in ICT applications, expensive ICT infrastructure, lack of expertise and technical know-how in new technologies and software, and limited telecommunications infrastructure. The study came up with the following recommendations to the hoteliers: to be transparent when implementing new technologies, to involve employees, to socialize and capacitate all key stakeholders in order to ensure that they are ready to embrace new technologies. Also the management must give all the necessary support to the employees and equip them with the essential skills.

Using ML to Predict User Satisfaction with ICT Technology for Educational Institution Administration

Effective and efficient use of information and communication technology (ICT) systems in the administration of educational organisations is crucial to optimise their performance. Earlier research on the identification and analysis of ICT users’ satisfaction with administration tasks in education is limited and inconclusive, as they focus on using ICT for nonadministrative tasks. To address this gap, this study employs Artificial Intelligence (AI) and machine learning (ML) in conjunction with a survey technique to predict the satisfaction of ICT users. In doing so, it provides an insight into the key factors that impact users’ satisfaction with the ICT administrative systems. The results reveal that AI and ML models predict ICT user satisfaction with an accuracy of 94%, and identify the specific ICT features, such as usability, privacy, security, and Information Technology (IT) support as key determinants of satisfaction. The ability to predict user satisfaction is important as it allows organisations to make data-driven decisions on improving their ICT systems to better meet the needs and expectations of users, maximising labour effort while minimising resources, and identifying potential issues earlier. The findings of this study have important implications for the use of ML in improving the administration of educational institutions and providing valuable insights for decision-makers and developers.

Computer‐aided experimental studies for adaptive beamforming algorithms and array processing in engineering education

AbstractSmart antenna and digital antenna systems are considered as a crucial technology for current and future communication systems supporting 5G/6G and nonterrestrial‐networks communications. Based on the information of the received signal/s, smart antenna systems toward the radiation pattern to the desired direction/s. This technique is known as adaptive beamforming. The theories and the applications of adaptive beamforming are taught in engineering educational courses. This paper proposes a set of real‐time interactive experiments for adaptive beamforming algorithms in antenna array processing subject. The proposed experiments can be performed with the computer‐aided experimental studies tool prepared in the MATLAB® environment. The users can easily make comparisons and can perform trade‐offs between different types of adaptive beamforming algorithms, scenarios, and antenna architecture. This is used as a teaching tool for a graduate course on adaptive beamforming algorithms.

Vehicle to Vehicle Communication Using Li-Fi Technology

Abstract: Vehicle-to-vehicle (V2V) communication has emerged as a pivotal technology in the automotive industry, enabling enhanced safety, efficiency, and convenience on the roads. This abstract explores the integration of Light Fidelity (LiFi) technology in V2V communication systems. LiFi, utilizing visible light communication (VLC), offers high-speed wireless connectivity by using light-emitting diodes (LEDs) to transmit data. By harnessing LiFi's unique advantages such as increased bandwidth, low latency, and immunity to radio frequency interference, V2V communication systems can facilitate real-time exchange of critical information between vehicles, including traffic conditions, collision warnings, and cooperative driving maneuvers. This paper delves into the technical aspects, challenges, and potential applications of LiFi-enabled V2V communication, shedding light on its promising role in revolutionizing the future of smart and connected transportation systems

Principles, applications, and challenges of digital predistortion technology

A power amplifier plays a crucial role in the transmitter end of wireless communication systems. Despite enhancing operational efficiency, it inadvertently introduces nonlinear distortion, leading to signal degradation and spectral regrowth. This occurrence necessitates the incorporation of additional linearization techniques in transmitter terminals to optimize both efficiency and linearity concurrently. Among these, Digital Pre-Distortion (DPD) technology stands out as a well-researched and extensively employed strategy for alleviating the nonlinear distortion induced by power amplifiers. This paper embarks on a comprehensive exploration of DPD technology, offering insight into its evolutionary path and elaborating on its foundational principles and essential techniques. The discussion extends to elucidate the significant technical challenges and the burgeoning trends within the DPD technology landscape. The narrative underscores the significance of DPD in enhancing the performance and efficiency of wireless communication systems, particularly in the context of burgeoning technological advancements and escalating demands for superior communication quality and broader bandwidth. Through a meticulous examination of the DPD technology paradigm, this paper contributes to the ongoing discourse and research, shedding light on prospective developmental avenues and potential enhancements that could further augment the efficacy and reliability of DPD technology in contemporary communication systems.

Modelling the propagation of properties across services in cyber-physical energy systems

Modern power systems, referred to as cyber-physical energy systems (CPESs), are complex systems with strong interdependencies between power and information and communication technology (ICT) systems. CPESs also have dependencies between the essential grid services. For instance, coordinated voltage control depends on state estimation, which depends on measurement acquisition. Since the operation of CPESs is largely influenced by these grid services, assessing their performance is crucial for assessing the performance of a CPES. Most of these grid services are enabled by the ICT system, i.e., they rely to a high degree on ICT. Hence, properties such as availability, correctness and timeliness, which depend on the involved software, hardware and data of the ICT system, must be considered for assessing the performance of an ICT-enabled grid service. Disturbances and repairs in CPESs impact these properties, which can then propagate and affect the performance of a grid service as well as other dependent grid services. There is, therefore, a need to model the influence of the properties of software, hardware and data on ICT-enabled grid services for single services as well as across several services, resulting in a propagation of these parameters. Current literature lacks such a model, which can used not only to investigate but also to visualise the impact of these properties on the overall perfromance of a grid service as well as other dependent grid services. This paper proposes a meta model for assessing the performance of ICT-enabled grid services, which can be instantiated for different grid services considering their dependencies. A multi-dimensional operational state space, which serves as a visualisation of the performance of grid services in terms of their state trajectory, is also proposed in this paper. The contributions are then demonstrated by a case study with a state estimation service and the widely-used CIGRE medium voltage benchmark power grid augmented with an ICT system. Three scenarios with disturbances are presented to show the benefits of the contributions. Specifically, the performance of the state estimation service considering the disturbances is investigated using the meta model, and the change in performance is visualised as trajectories using the operational state space. These contributions enable new possibilities for planning and vulnerability analyses: property changes in parts of the ICT system can be simulated to investigate their consequences throughout the ICT-enabled grid services. A trajectory representing their performance can then be visualized in the state space based on which measures could be implemented to potentially improve the resilience of the service against the considered disturbances.

A deep learning approach for reduce CSI feedback overhead in massive MIMO

The Massive MIMO system in FDD communication mode is still one of the indispensable technologies in future cellular communication systems. In order to reduce CSI feedback overhead and enhance the quality of CSI channel reconstruction, this paper proposes a RiCsiNet network model and designs an iNetBlock module with larger convolutional kernels and a wider network structure. By connecting parallel convolution kernels of 1 × 1, 3 × 3, 5 × 5, and 7 × 7, both the width of the network and the receptive field are increased simultaneously, enabling calculation of different feature details at each layer. The compressed CSI is accurately estimated through residual connections at the BS end. The network model proposed in this paper, when considering both the model parameter size and the estimated CSI accuracy, outperforms the existing algorithm model in the NMSE index of 70%. In this paper, we verify that using different learning rate decay algorithms to train the model, a good learning rate decay algorithm can effectively improve the quality of the model, the best result is 12% higher than the worst result. Furthermore, we demonstrate that training different network models with varying amounts of data can not only save time but also maximize CSI channel estimation quality on the BS side. Finally, the RiCsiNet model was verified using different SNR under COST2100 channel model. QuaDRiGa data sets with different truncated subcarriers are used to verify the RiCsiNet model. The CSI estimated by the RiCsiNet model all showed high accuracy.

Применение физического уровня 5G NR в космических коммуникациях, оценка эффективности.

The propagation channel is significantly modified in the case of 5th Generation New Radio radio access technology (5G NR) in space communication systems. In particular, large delays occur with respect to the terrestrial propagation channel, and signal attenuation increases, resulting in a lower signal-to-noise ratio (SNR). The Doppler shift of the carrier frequency is also significantly increased due to the high velocity of the spacecraft (SC) relative to the user equipment (UE). The aim of the work is to investigate the decoding capability of the physical channels and signals of the 5G NR system in case of its application in satellite communication systems (SCS), as well as to calculate the performance of such a system to assess the applicability of 5G NR in SCS. The ability to correctly decode signals and channels depending on SNR is evaluated using mathematical modelling of 5G NR signal and channel shaping in conjunction with the Quasi Deterministic Radio Channel Generator (QuaDRiGa) model. The research within the paper draws conclusions on the applicability of 5G NR radio access technology in a space communications environment.

DACNN-aided nonlinear equalizer for a probabilistic shaping coherent optical communication system.

The probabilistic shaping (PS) technique is a key technology for fiber optic communication systems to further approach the Shannon limit. To solve the problem that nonlinear equalizers are ineffective for probabilistic shaping optical communication systems with non-uniform distribution, a distribution alignment convolutional neural network (DACNN)-aided nonlinear equalizer is proposed. The approach calibrates the equalizer using the probabilistic shaping prior distribution, which reduces the training complexity and improves the performance of the equalizer simultaneously. Experimental results show nonlinear equalization of 120Gb/s PS 64QAM signals in a 375km transmission scenario. The proposed DACNN equalizer improves the receiver sensitivity by 2.6dB and 1.1dB over the Volterra equalizer and convolutional neural network (CNN) equalizer, respectively. Meanwhile, DACNN converges with fewer training epochs than CNN, which provides great potential for mitigating the nonlinear distortion of PS signals in fiber optic communication systems.

Passive reputation method with hybrid optimized deep model for spectrum sensing in cognitive radio network based on blockchain

SummaryThe discovery of malevolent users in cognitive radio networks (CRNs) is done by using blockchain‐based technique. For diagnosing the availability of frequency resources, the spectrum sensing (SS) plays an essential role in CRN. It is critical to enable cognitive radio (CR) technology in wireless communication systems for the next generation. Due to the increasing demand of the users, some bands are overloaded and others become underutilized. The CR applied models for vigorously assigning unlicensed users. The missed detection problem occurs in the conventional spectrum sensing schemes, which hampers the proper utilization of the spectrum. These motivated the development of a newly devised passive reputation method with an optimized deep model for spectrum sensing in CRN‐based blockchain. The sensing spectrum in CRN is designed using the cooperative spectrum sensing algorithm. The spectrum sensing is done with the decision made using AlexNet where the weights of AlexNet are trained with a hybrid optimization algorithm, named Honey Badger Remora Optimization (HBRO) algorithm. Thus, the output attained from the Alexnet_HBRO algorithm is considered. Meanwhile, the data are recorded in the blockchain, and then, the passive reputation is performed, and the determined output is considered. At last, the spectrum sensing is carried out by fusing AlexNet and passive reputation output where weights are optimally generated using the proposed Snake Honey Badger Remora Optimization (SHBRO) algorithm. The proposed SHBRO offered a high detection probability of 1, false alarm probability of 0.003, sensing time of 551.567s, and computation time of 210.102s.

A Systematic Review of Blockchain Technology Assisted with Artificial Intelligence Technology for Networks and Communication Systems

Blockchain is a very secure, authentic, and distributed technology and is very prominent in areas such as edge computation, cloud computation, and Internet-of-things. Artificial intelligence assists in the completion of activities efficiently and effectively by providing intelligence, analytics, and predicting capabilities. There is an obvious convergence between the two technologies. Artificial intelligence systems can utilize blockchain to establish trust in communication channels, ensuring that messages are securely transmitted and received without the need for a centralized intermediary. By leveraging blockchain, artificial intelligence systems can maintain an immutable record of communications, ensuring transparency and preventing unauthorized modifications. The integration of blockchain and artificial intelligence technologies can enhance the security, transparency, and privacy of communication systems. By leveraging blockchain’s decentralized nature and artificial intelligence’s analytical capabilities, secure and trustworthy communication channels can be established, benefiting various domains such as finance, healthcare, and supply chain. Overall, the integration of blockchain and artificial intelligence has the potential to offer several benefits, and as these technologies continue to evolve, new and innovative applications will continue to emerge.

Applications, challenges, and solutions of unmanned aerial vehicles in smart city using blockchain.

Real-time data gathering, analysis, and reaction are made possible by this information and communication technology system. Data storage is also made possible by it. This is a good move since it enhances the administration and operation services essential to any city's efficient operation. The idea behind "smart cities" is that information and communication technology (ICTs) need to be included in a city's routine activities in order to gather, analyze, and store enormous amounts of data in real-time. This is helpful since it makes managing and governing urban areas easier. The "drone" or "uncrewed aerial vehicle" (UAV), which can carry out activities that ordinarily call for a human driver, serves as an example of this. UAVs could be used to integrate geospatial data, manage traffic, keep an eye on objects, and help in an emergency as part of a smart urban fabric. This study looks at the benefits and drawbacks of deploying UAVs in the conception, development, and management of smart cities. This article describes the importance and advantages of deploying UAVs in designing, developing, and maintaining in smart cities. This article overviews UAV uses types, applications, and challenges. Furthermore, we presented blockchain approaches for addressing the given problems for UAVs in smart research topics and recommendations for improving the security and privacy of UAVs in smart cities. Furthermore, we presented Blockchain approaches for addressing the given problems for UAVs in smart cities. Researcher and graduate students are audience of our article.

Sustainable Digital Evolution: Transforming the Ukrainian Customs Service

The evolving landscape of information technologies has spurred a profound digital revolution across cultural, societal, organizational, and governmental domains. This article examines the transformative impact of Information and Communications Technology (ICT) and electronic systems within Ukrainian customs operations and their broader societal implications. At the core of this exploration lies the pivotal role of ICT integration in modernizing the Ukrainian Customs Service amidst global challenges, exemplified by the COVID-19 pandemic. The study assesses the benefits, challenges, and implications of “electronic customs” and IT-driven reforms, focusing on the three pillars of sustainability, customs operations, and digital culture. Objectives encompass an evaluation of ICT’s significance in enhancing border management efficiency, addressing challenges, and leveraging opportunities through technology-driven customs initiatives. Synthesizing academic publications and governmental reports, the article provides comprehensive insights into the transformative potential of technology in customs management. Notably, the implementation of anti-corruption measures, particularly through the Single Window system, emerges as a successful endeavor in curbing malpractices while streamlining customs procedures. However, challenges persist, including swift adoption, cyber fraud risks, and systemic issues within customs authorities, necessitating phased implementation and continuous improvement. Ethical reflections on technology integration into governance mechanisms, educational reforms, and inclusivity discussions underscore the broader societal and philosophical shifts catalyzed by electronic customs. This sustainable digital evolution emphasizes ongoing ethical considerations to navigate the evolving role of technology in shaping governance, societal integration, sustainable customs operations, and the inherent alignment of digital technologies with the key objectives of sustainable development.
 Keywords: customs operations, digital culture, sustainable development, Single Window, cybersecurity, Information and Communication Technology, societal impact, ethical framework, cultural shifts

ZAKAT MANAGEMENT TO BUILD COMMUNITY WELFARE IN BENGKALIS REGENCY, RIAU PROVINCE

This study aims to determine the strategy for managing zakat funds to improve people's welfare at the Bengkalis Regional Zakat Agency (BAZNAS).The research was conducted using a qualitative approach with descriptive methods, in which the data were obtained through interviews, observation, documentation, and a literature review. The results showed that the strategy for managing zakat funds used by the Amil Zakat Agency of Bengkalis Regency was to increase cooperation with various agencies, including government agencies, often by conducting socialization through seminars on zakat. They were growing the competence of Amil Human Resources (HR), the Zakat Collection Unit (UPZ), and volunteers and developing an information and communication technology (ICT) system for managing zakat. While the obstacles are the lack of public understanding of zakat and the lack of public trust in the Amil Zakat Agency, Bengkalis Regency. The solutions implemented by BAZNAS Bengkalis Regency to overcome obstacles include BAZNAS having to carry out transparency in management, modernization of control, and publication of zakat management. The Bengkalis Regency National Amil Zakat Agency (BAZNAS) needs to involve government and private institutions in programs that can assist mustahik in using zakat funds. As well as, the role of local government in improving the management of zakat can increase people's motivation to pay zakat. There needs to be in-depth research on zakat in the regions, and Bengkalis Regency has a different program from the other areas in Indonesia.

An Efficient Matching Game Approach to Association Formation in UAV-Enabled Hierarchical Distributed Learning.

Distributed machine learning has emerged as a promising data processing technology for next-generation communication systems. It leverages the computational capabilities of local nodes to efficiently handle large datasets, creating highly accurate data-driven models for analysis and prediction purposes. However, the performance of distributed machine learning can be significantly hampered by communication bottlenecks and node dropouts. In this article, a novel unmanned aerial vehicle (UAV)-enabled hierarchical distributed learning architecture is proposed to support machine learning applications, e.g., regional monitoring. Multiple UAV receivers (URs) are introduced as wireless relays to improve the communication between the UAV transmitters (UTs) and the cloud server. Our objective is to identify the optimal UT-UR association to maximize the social welfare of the network, which is distinctly different from the existing works that focus on the unilateral profit-maximizing problem. We formulate a two-side many-to-one matching game to model the UT-UR association problem, and a two-phase many-to-one matching algorithm is designed to identify the stable matching. The validity of our proposed scheme is verified through in-depth numerical simulations.

Notice of Violation of IEEE Publication Principles: An Efficient Nonlinear Quantized Constant Envelope Precoding for Massive MU-MIMO Systems

Notice of Violation of IEEE Publication Principles <BR><BR>"An Efficient Nonlinear Quantized Constant Envelope Precoding for Massive MU-MIMO Systems," <BR>by R. Liang, H. Li, W. Zhang, C. Liu and Y. Guo, <BR>in IEEE Systems Journal, Early Access <BR><BR>After a careful and considered review of the content and authorship of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE’s Publication Principles. <BR><BR>This paper contains content from the papers cited below. Credit notices were used, but due to the absence of quotation marks or offset text, the copied content is not clearly referenced or specifically identified. <BR><BR>"VLSI Design of a 3-bit Constant-Modulus Precoder for Massive MU-MIMO," <BR>by O. Castañeda, S. Jacobsson, G. Durisi, T. Goldstein and C. Studer, <BR>in the Proceedings of the IEEE International Symposium on Circuits and Systems (ISCAS), May 2018 <BR><BR>"Quantized Precoding for Massive MU-MIMO," <BR>by S. Jacobsson, G. Durisi, M. Coldrey, T. Goldstein and C. Studer, <BR>in IEEE Transactions on Communications, vol. 65, no. 11, pp. 4670-4684, November 2017 <BR><BR> <br/> Massive multiuser multiple-input&#x2013;multiple-output (MU-MIMO) systems are foreseen as the key technology in next-generation wireless communication systems. However, many radio-frequency (RF) chains will require high power consumption and lots of hardware cost. One of the practical solutions is using low-resolution discrete phase shifters (PSs) for each antenna and RF chain. This article designs a nonlinear quantized constant envelope precoding algorithm for MU-MIMO systems with low-resolution discrete PS at the base station. In this algorithm, the quantized constant envelope precoding problem is presented as a nonconvex optimization problem. The multiuser interference is minimized by solving the optimal precoded vector and the associated precoding factors. First, we consider relaxing the nonconvex constraint on the 1-bit quantized constant envelope precoding to a continuous set of convex constraints on the unit circle. Afterwards, the semidefinite relaxation method is used to tackle the equivalent 1-bit quantized precoding problem. We further extend the algorithm to provide multi-bit quantized constant envelop precoding. Finally, the simulations are carried out under various conditions and compared with the most advanced precoding methods. The results demonstrate that this algorithm achieves a comparable performance to the existing precoding methods. At the same time, the corresponding performance-complexity tradeoff is more conducive to the expansion of the proposed algorithm to the multibit case.

An Overview of Key Machine Learning Technologies in 6G-Oriented Terahertz Wireless Communication Systems (Invited)

An Overview of Key Machine Learning Technologies in 6G-Oriented Terahertz Wireless Communication Systems (Invited)

DESIGN AND IMPLEMENTATION OF MULTIPLE-IN, MULTIPLE-OUT ANTENNA FOR S-BAND SATELLITE APPLICATIONS

The popularity of multiple-in, multiple-out (MIMO) technology in wireless communication systems has increased due to its ability to enhance system capacity, coverage, and reliability, leading to a rising interest in designing and implementing MIMO antennas for various frequency bands, such as the S-band. However, mutual coupling between multiple antennas can pose a significant challenge in the performance analysis of MIMO systems. In this study, we introduce a novel approach involving the utilization of an L-shaped slot in a patch element placed on an economical FR4 epoxy material with a relative permittivity of 4.4 and a loss tangent of 0.02. Multiple antennas are strategically positioned in an orthogonal arrangement to minimize coupling effects. Our proposed antenna design successfully achieves an impedance bandwidth that aligns with the -10 dB reference over a frequency range from 2.78 GHz to 2.66 GHz, making it suitable for S-band satellite applications. Furthermore, by employing a four-element MIMO antenna setup, we achieve excellent isolation characteristics, with values below -20 dB. To ensure excellent MIMO performance, we consider some diversity parameters such as envelope correlation coefficient (ECC) and diversity gain (DG), which we investigate and find to be within standard limits (ECC &amp;#60; 0.04, DG &amp;#61; 10 dB). Our study offers valuable insights into designing and optimizing MIMO antennas for S-band satellite applications and can serve as a useful reference for future research in this area.