The evolution of 6G (sixth-generation) with optimization of wireless networks for ultra-reliable, low-latency, high-capacity for communication system. LEO (Low Earth Orbit) satellite systems with non-terrestrial networks (NTN), particularly for enhancing coverage and optimizing networks in dense urban areas. However, signal blockage, multipath propagation, and dynamic channel performance challenges. This paper proposes hybrid deep learning by integrating CNN (Convolutional Neural Networks) with swarm intelligence, including PSO (Particle Swarm Optimization), SSA (Salp Swarm Algorithm), WOA (Whale Optimization Algorithm), GWO (Grey Wolf Optimizer), ABC (Artificial Bee Colony), and ALO (Ant Lion Optimizer). These hybrid models are integrated with beamforming to optimize satellite positioning and transmission parameters in 6G LEO-enabled NTN systems. The performance evaluation considers the communication parameters including propagation delay, BER (bit error rate), EE (energy efficiency), SE (spectral efficiency), channel capacity, SINR (signal-to-interference-plus-noise ratio), and PL (path loss) with urban NLOS (non-line-of-sight), and LOS (line of sight). Simulation result show that hybrid CNN-based optimization enhances the performance compared to standalone algorithms. Among the evaluated algorithm, the ABC-CNN has the best performance in balanced enhancement of reliability, capacity, and EE parameters.The findings show that integrating CNN with swarm optimization provides for beamforming in future 6G LEO satellite networks.

This study investigates seasonal and diurnal variations of surface radio refractivity in a tropical region by comparing real-time derived values from a low-cost automated Global System for Mobile Communication Signal Strength and Radio Climatological (GSM-RC) monitoring device with those modeled by ITU-R P.453-13. The GSM-RC device, installed at 3-m height, provided real-time, in-situ measurements of temperature, pressure, and humidity. Refractivity was derived in real-time from this high-resolution data and compared against model outputs across four months representing distinct climatic phases: January (dry season), April (commencement of rainy season), July (intense rainy season), and October (fading season). Results show a strong correlation between datasets, with seasonal atmospheric dynamics driving clear patterns. The dry season exhibited large diurnal fluctuations due to low humidity and high solar radiation, while the intense rainy season showed minimal variability from persistently high humidity and reduced temperature gradients. Transitional months displayed moderate instability. Although the ITU-R model provided reliable smoothed approximations, real-time derived data proved superior at capturing transient fluctuations, particularly during atmospheric instability. These findings underscore the value of locally-sourced real-time data for capturing dynamic refractivity behaviour and highlight opportunities to enhance climatological propagation models. By linking observed patterns to West African monsoon phases, this work provides valuable insight for telecommunications system design, weather prediction, and regional atmospheric monitoring in tropical environments.

The economic development and economic scale of contemporary society, huge amounts of data, and concise and effective information output have put forward new requirements for an accounting information system (AIS). This study focused on intelligent interactive visualization technology in the construction of the AIS. Firstly, the feasibility of intelligent interactive visualization of an AIS was analyzed, and a mathematical model was established for the data analysis of the accounting platform. Then, a mobile input device and Radio Frequency Identification data acquisition based on a browser and server were introduced. Finally, the data input port on the browser/server mode, the data processing terminal on the data warehouse, and the information output port on the accounting channel and foldable chart were established.

This paper aimed to examine the use of digital technology for disseminating information among fishermen around the Mindu Dam in Morogoro, Tanzania. Informed by the Innovation (DOI) Theory and Wilson’s model of information-seeking behavior, the study used a mixed research approach, involving both quantitative and qualitative methods. While simple random sampling techniques were used, the data collection tools used were questionnaires and key informants’ interviews. Data was collected from 82 fishermen who were randomly selected from the fishing community in Mindu Dam. Data analysis used the Statistical Package for the Social Sciences (SPSS), while content analysis was used for qualitative data. The study found that the most frequently used ICTs by fish farmers in sharing agricultural information were mobile phones, radio, and television. Furthermore, the study revealed that major challenges facing fish farmers in sharing information include unfavorable radio or television broadcast times, high costs of acquiring and maintaining ICT facilities, lack of ICT training, poor network connectivity, and low literacy levels. The research emphasizes the critical role of mobile phones, internet services, and other digital technologies in improving communication, obtaining market information, and executing financial transactions. The study demonstrates notable enhancements in decision-making and general management efficiency by examining how these communities and managers utilize digital technologies. It also delineates obstacles to successful technology adoption, such as resistance to change and a lack of training, and offers strategies to overcome them, including targeted training programs and community engagement initiatives. The findings highlight the capacity of digital technology to enhance sustainable livelihoods and economic development in the fishing sector, hence, cultivating a more resilient and informed community. While the study indicated that fishermen in the Mindu Dam regularly used mobile phones, radios, and televisions to exchange and disseminate information, fishermen encountered multiple challenges in utilizing ICTs for the sharing and dissemination of fishing information. Therefore, the study recommends that the challenges encountered by fishermen in utilizing ICTs be addressed through the pertinent ministry; via its extension personnel, it should incentivize and conduct regular training sessions for these communities on the use of ICTs (mobile phones, radios, and television) to enhance their proficiency and skills in accessing and disseminating fishing information.

Mobile Ad hoc Networks (MANETs) are considered as a paradigm of infrastructure-less mobile wireless communication systems. MANETs are being widely studied and it is the technology that is attracting a large variety of applications. Routing is a critical issue in MANETs, due to the frequently changing network topology, which requires efficient and dynamic routing protocols. In MANETs, routing protocols are classified into three categories: Proactive protocols, Reactive protocols and Hybrid protocol. This paper compares the performance of proactive and reactive routing protocols in MANETs by selecting the DSR, AODV and OLSR protocols under multiple network scenarios and sizes using different performance metrics, considering voice, video and file transfer applications. The simulations were conducted using the OPNET Modeller software. The findings show that the OLSR achieves the lowest delay across all scenarios. While the AODV provides better throughput and network load readings in Small-Scale MANETs and Large-Scale MANETs. Although DSR is considered the least efficient, its performance remains acceptable in Small-Scale MANETs. Keywords: MANETs; OLSR; DSR; AODV; Multi-Application Traffic; OPNET

In Peru, the national immunization schedule includes Bacillus Calmette–Guérin (BCG), Diphtheria–Tetanus–Pertussis (DTaP), Measles–Mumps–Rubella (MMR), and Poliomyelitis (Pol) vaccines. Despite their proven role in reducing infant morbidity and mortality, coverage remains uneven and is potentially influenced by access to communication media. We analyzed data from 37,791 mother–child pairs with children aged 18–24 months from the nationally representative Demographic and Family Health Survey (ENDES) 2021–2024. Using generalized linear models with a Poisson family and log link, we estimated adjusted prevalence ratios (PRa) for associations between complete vaccination and access to various media types (newspaper, radio, television, internet, computer, landline, mobile phone), accounting for the complex survey design through sampling weights, stratification, and clustering. Complete vaccination was reported for 94.1% of children for BCG, 85.5% for DTaP, 86.3% for Pol, and 52.9% for MMR. Mobile phone or smartphone ownership was consistently associated with higher completion across all vaccines, ranging from a 12% increase for BCG (PRa 1.12; 95% CI 1.03–1.21) to a 43% increase for MMR (PRa 1.43; 95% CI 1.15–1.77). Radio access was positively associated with DTaP (PRa 1.03; 95% CI 1.00–1.05) and Pol (PRa 1.04; 95% CI 1.01–1.06). Speaking a language other than Spanish or Quechua was linked to lower coverage, particularly for MMR (PRa 0.67; 95% CI 0.56–0.82) and DTaP (PRa 0.76; 95% CI 0.68–0.86). These findings suggest that expanding culturally and linguistically tailored communication strategies through both traditional and digital media, especially mobile phones and radio, could improve vaccination uptake, particularly for MMR, DTaP, and Pol.

Wideband Active Frequency Selective Surface (AFSS) for Wireless and 5G Mobile Communications

This study presents the design and analysis of a miniature circularly polarized spiral antenna incorporating a frequency reconfiguration mechanism based on two PIN diodes, enabling broadband coverage dedicated to IoT applications below 6 GHz. The antenna is fabricated on a Rogers RT-5880 substrate, selected for its low losses and high electromagnetic performance. Despite the integration of the reconfiguration system, the structure maintains compact dimensions of 16.5 × 12 × 0.79 mm 3 , ensuring easy integration into embedded devices with tight space constraints. The frequency reconfigurability provides dynamic adaptation of the operating band, allowing it to meet the various IoT standards operating in the sub-6 GHz range. The design and performance evaluation were performed using the CST Studio Suite electromagnetic simulation software. The results obtained confirm the proposed antenna's ability to provide effective broadband coverage while maintaining a compact design, making it a relevant solution for IoT, mobile, and low-power wireless communication systems.

Limited access to timely agricultural information remains a major constraint affecting productivity and market participation of smallholder farmers in Sub-Saharan Africa. Information and Communication Technologies (ICTs) provide new opportunities for delivering weather forecasts and market information that support farm decision-making and income improvement. This study examined the impact of ICT-based weather and market information delivery on the income of pepper-producing smallholder farmers in Wera Woreda, Halaba Zone, Ethiopia. A mixed research approach was employed using cross-sectional data collected from 174 randomly selected households consisting of ICT users and non-users. Primary data were gathered through structured household surveys, focus group discussions, and key informant interviews, while secondary data were obtained from institutional reports and published sources. Descriptive statistics and Propensity Score Matching (PSM) were applied to estimate the causal impact of ICT utilization on household income. Results show that mobile phones, radio, and television were the dominant channels through which farmers accessed agricultural information. Logit model results indicate that education level, training exposure, frequency of extension contact, distance to market, and farmers’ behavioral characteristics significantly influenced ICT adoption. The PSM estimation revealed that ICT use increased household income of pepper producers by approximately 54.29 percent compared to non-users. However, several constraints limited effective utilization, including inadequate localized weather forecasts, limited ICT skills, language barriers, high service costs, and weak rural infrastructure. The study concludes that ICT-enabled advisory services significantly enhance farmers’ income by improving market participation and climate-related decision-making. Strengthening rural ICT infrastructure, localized information delivery, and farmer training programs is essential to sustain these benefits.

6G is the next generation of mobile radio communication systems. It aims to have more sustainable and inclusive ubiquitous radio connectivity at lower latencies, faster rates, and a higher bandwidth than 5G radio systems. Usage of sub-THz bands (> 100 GHz) in 6G systems enables performance gains in terms of latency, data rates, transmission bandwidth, signal interference, and network capacity. The main challenges at such higher frequency bands are to have resilient waveforms and capability in handling hardware limitations such as phase noise. Therefore, it is high time to explore the possibilities of design, optimize, and test the signal generation, digital, and radio frequency (RF) hardware. This work is mainly aimed at the imperfections of hardware in handling the candidate 6G orthogonal frequency division modulation (OFDM) signals. The imperfections include non-linearities of the power amplifier, phase noise, and filter characteristics that spread the signal spectrum beyond the channel bandwidth. The system parameters are designed and configured according to ITU-R radio models while quantifying the impairments. The hardware imperfections are demonstrated using adjacent channel power radio (ACPR) and error vector magnitude (EVM) as metrics. ACPR measurements help to study spectral regrowth due to the nonlinearity of power amplifiers.

Portable electronic devices have crucial importance in today’s smart world and with the fast developing technology era, battery requirement are increasing to manifold, by virtue of which there is strong need to fulfil the current power requirement and it be could be better option if we make transition towards renewable energy sources to promote environmental sustainability. To solve battery charge problem in an easy and cheap way, renewable energy source of solar power is used to provide sufficient energy for the portable device battery. As energy saving and environmental protection become a global demand and inevitable trend, there is an urgent need to shift our focus to energy efficiency oriented design for the wireless mobile communication networks. Optimizing energy efficiency through alternative energy resources will not only reduce environmental impact, it will also cut costs and help to make wireless mobile technology more affordable for everyone.

As the frequency of natural disasters and cyberattacks increases, ensuring the reliability and resilience of power grid communication systems has become a critical concern. This paper explores the integration of Digital Mobile Radio (DMR) trunking communication systems into Supervisory Control and Data Acquisition (SCADA) systems to improve grid resilience during emergencies. The methodology, based on the work of Md. Shahiduzzaman Rabbi, presents an innovative approach for enhancing the reliability and performance of grid communication by incorporating DMR as a fallback mechanism. Through simulations based on a Texas microgrid testbed, this study demonstrates the effectiveness of DMR in reducing grid restoration times, improving command delivery success rates, and ensuring secure and reliable communication during network disruptions. The results highlight the potential of DMR trunking as a cost-effective, scalable solution for enhancing grid resilience in smart grid environments.

The Information and Communication Technologies (ICT) are significant in uplifting the lives of the rural small landholder farmers because of the challenges it has overcome in adopting the traditional agriculture. ICT contributes to the increase of the demand of novel approaches. It also assists in empowering the rural population through the availability of more natural resources, advanced agricultural technologies, efficient production plans, markets, banking and financial services etc. The role of ICT in agricultural sector is realized in this article. The current study was undertaken to analyze the socio-economic profile, communication behavior and the correlation between the same and the independent variables chosen in relation to the farmers with a structured interview questionnaire. The results showed that most of the respondents were between the middle age, had moderate level of education, small and marginal farmers category with moderate experience in farming and medium sized families. The most prevalent media had been mobile phones (98.33%), televisions (81.67%), and radios (74.67%), whereas mass media exposure, extension contact, information-seeking behavior, cosmopolitanism, and social participation were mostly of medium levels. Correlation results showed that education, extension contact, use of ICT, mass media exposure and information-seeking behavior were strongly and significantly correlated with the dependent variable whereas age was only significantly correlated but negatively. Social participation built a non-significant positive relationship. Some constraints were also discussed to avail ICT tools. The findings indicate that greater efforts toward education, better repair of contact, greater usage of ICT, and greater availability to credible information may help extensively in better realization of agricultural innovations. This evidence is worthwhile to policy makers and extension agencies to come up with specific interventions to satisfy the needs and communication trends of farmers.

This study presents an optimization-driven design of a wireless communications network to continuously transmit environmental variables—temperature, humidity, weight, and water usage—in poultry farms. The reference site is a four-shed facility in Quito, Ecuador (each shed 120m×12m) with a data center located 200m from the sheds. Starting from a calibrated log-distance path-loss model, coverage is declared when the received power exceeds the receiver sensitivity of the selected technology. Gateway placement is cast as a mixed-integer optimization that minimizes deployment cost while meeting target coverage and per-gateway capacity; a capacity-aware greedy heuristic provides a robust fallback when exact solvers stall or instances become too large for interactive use. Sensing instruments are Tekon devices using the Tinymesh protocol (IEEE 802.15.4g), selected for low-power operation and suitability for elongated farm layouts. Model parameters and technology presets inform a pre-optimization sizing step—based on range and coverage probability—that seeds candidate gateway locations. The pipeline integrates MATLAB R2024b and LpSolve 5.5.2.0 for the optimization core, Radio Mobile for network-coverage simulations, and Wireshark for on-air packet analysis and verification. On the four-shed case, the algorithm identifies the number and positions of gateways that maximize coverage probability within capacity limits, reducing infrastructure while enabling continuous monitoring. The final layout derived from simulation was implemented onsite, and end-to-end tests confirmed correct operation and data delivery to the farm’s data center. By combining technology-aware modeling, optimization, and field validation, the work provides a practical blueprint to right-size wireless infrastructure for agricultural monitoring. Quantitatively, the optimization couples coverage with capacity and scales with the number of endpoints M and candidate sites N (binaries M+N+MN). On the four-shed case, the planner serves 72 environmental endpoints and 41 physical-variable endpoints while keeping the gateway count fixed and reducing the required link ports from 16 to 4 and from 16 to 6, respectively, corresponding to optimization gains of up to 82% and 70% versus dense baseline plans. Definitions and a measurement plan for packet delivery ratio (PDR), one-way latency, throughput, and energy per delivered sample are included; detailed long-term numerical results for these metrics are left for future work, since the present implementation was validated through short-term acceptance tests.

Sixth-Generation Nonterrestrial Networks: Where Standards and Technology Are Heading [Mobile Radio

This paper introduces a navigation system, and a data processing algorithm tailored for a handheld groundpenetrating radar (GPR), along with results from real-world tests conducted using a physical model. Handheld GPR systems are indispensable for scanning challenging and inaccessible terrains, particularly to detect buried landmines and other explosive remnants of war, where vehicle-mounted GPR systems cannot operate effectively. Building on previous research, which focused on a system designed with stationary and mobile ultrawideband radio transceivers tested via simulations, this study addresses practical challenges encountered in a real-world physical model. A novel data processing algorithm is proposed to handle key issues, including a variable number of distance measurements per estimation step and the presence of measurement outliers. Furthermore, the methodology and results of the real-world testing of the positioning system, conducted using an industrial robot for controlled experimentation, are presented and discussed.

The article proposes a method of intelligent decision-making support in control systems of programmable mobile radio communication. In the course of the work, the most common architectures of the management system, types of management system structures, levels of management were considered, an overview of the latest research was conducted, and the relevance of the development of the specified methodology was determined. The process of supporting decision-making in management systems, the process of functioning of the decision-making support system, the list of ways and methods of information technologies that can be used in the functioning of the decision-making support system were also considered. Since modern decision support approaches increase the mathematical complexity of the system, taking into account the goal and requirements for developing the methodology, it is proposed to use a neural network. The essence of the developed methodology is: in the systematization of the process of managing programmable mobile radio communications, the use of initial data that has a connected nature between all the functions of the control system and the characteristic application of programmable mobile radio communications, when using proven mathematical tools to improve indicators of the effectiveness of support decision-making by the control system using neural networks. The proposed technique includes stages that correspond to the sequence of application of appropriate methods and methods in the control system of programmable mobile radio communication devices, namely: data collection and determination of the control goal; construction of a knowledge representation subsystem; classification and clustering of states; selection and application of a neuroalgorithm assessment of conditions; assessment and selection of optimal and alternative solutions; implementation of solutions and their support. The proposed method, thanks to the correct formulation of the research task and the use of a proven mathematical apparatus, allows self-learning of the neural network, taking into account the peculiarities of the functioning of programmed mobile radio communication devices, increasing the speed and accuracy of decision-making based on the intellectualization of decision-making support.

Analysis of the military experience of the Russian-Ukrainian war and the situation in the world as a whole indicate that information advantage is a determining condition for victory on the battlefield. To ensure advantage, a mobile, reliable and resilient information and communication network is necessary. A representative of such a network is a radio network of the MANET class, which has the ability to self-recover, self-organize and is able to function in conditions of limited resources and constant topology changes. For effective management of this complex system and ensuring the optimal level of operation of its nodes, coordination of target functions of control systems is important as a criterion by which the quality of the node and network operation is assessed. The article proposes a variant of applying the multi-criteria optimization method, namely the method of successive concessions in the process of coordinating target functions of nodal control systems in tactical mobile radio networks of the MANET class. The method is proposed to be used at the stage of forming the controlling influence of the coordinator node. The method of coordinating objective functions using fuzzy logic is taken as a basis, while the mobile network is considered as a complex hierarchical system. The key feature of using the method of successive concessions in this article is that a non-iterative version is used, which replaces the iterative process of determining the concession, which is necessary in classical methods of multi-criteria optimization. This allows you to reduce the time that the coordinator node spends on forming a fuzzy subset of admissible solutions and, as a result, the entire coordination process is accelerated. It is proposed to introduce typical scenarios of events in a mobile radio network, which will allow you to give priority to objective functions in accordance with each scenario. This will help prevent conflict situations in the network when objective functions contradict each other. The introduction of the method of successive concessions into the coordination process will allow you to obtain a clearer system objective function.

Water is an essential resource for the survival of humans, animals, and plants. However, despite its critical importance, clean and safe water is not always readily available for drinking, household needs, or industrial applications. A variety of factors—including industrial activities, mining operations, pollution, and natural environmental processes—can influence water quality by introducing contaminants or altering its physicochemical properties. These changes directly affect the suitability of water for human consumption or general usage. To regulate this, the World Health Organization (WHO) provides guidelines that specify acceptable threshold levels for various water quality parameters used for drinking and irrigation.Metrics such as the Water Quality Index (WQI) and the Irrigation Water Quality Index (IWQI) consolidate these parameters into single numerical indicators to evaluate overall water quality. However, the traditional process of collecting samples from diverse sources, transporting them under controlled conditions, measuring multiple parameters, and comparing results with established standards is labor-intensive, time-consuming, and operationally challenging.To address these limitations, this study introduces a real-time monitoring framework that integrates a distributed network architecture with machine learning (ML) techniques to automatically assess the suitability of water samples for drinking and irrigation. The proposed network utilizes LoRa communication technology and is designed with consideration of land topology. Simulation results generated using Radio Mobile identified a partial mesh topology as the most effective structure for data transmission.Due to the lack of comprehensive public datasets for drinking and irrigation water quality, custom datasets were created to train ML models. Three algorithms—Random Forest (RF), Logistic Regression (LR), and Support Vector Machine (SVM)—were evaluated for water classification tasks. Experimental findings revealed that LR achieved the highest accuracy for drinking water classification, while SVM proved most effective for irrigation water assessment. Additionally, recursive feature elimination was applied in conjunction with these models to identify the most influential water quality parameters contributing to classification performance.

Access to reliable lighting remains a critical yet unmet need in many off-grid and low-income rural communities across the Global South. Meanwhile, the accelerating growth of electronic waste (e-waste) poses a mounting environmental challenge. Paradoxically, much of this discarded material-such as LEDs, lithium-ion batteries, and robust plastic housings-can be salvaged and repurposed into affordable, energy-efficient lighting devices. This paper examines the potential of transforming e-waste into durable flashlights, addressing both environmental and energy access gaps. The core concept is to address the dual challenges of energy poverty and e-waste accumulation by transforming discarded electronics into affordable, durable lighting solutions. Essential components like lithium-ion batteries, LEDs, and PCBs can be salvaged from common e-waste, including old mobile phones, radios, and broken flashlights. This recovered technology is then combined with readily available and recycled materials-including bamboo, PVC pipes, scrap plastic, and Aluminium foil-to create the flashlight's structure and optical elements, making the production process highly cost-effective and environmentally sustainable. The financial and technical feasibility is demonstrated by case studies from countries such as Kenya and Ghana, where models have been developed to produce flashlights at a fraction of the commercial cost, designed for local repairability. Furthermore, this process is organized into a localized ecosystem covering collection, assembly, sales, and servicing. This approach represents a powerful “waste-to-wealth” strategy that fosters micro-entrepreneurship, provides skill development for women and youth, and enhances community resilience, thereby contributing to global goals for clean energy and responsible consumption.