European Journal of Electrical Engineering and Computer Science

Adaptive User Association through Signal and Power Threshold Adjustments between Sub-6 GHz and MmWave Bands

2025-01-27T14:44:15+01:00

In order to satisfy the various coverage and capacity needs of next-generation wireless networks, the sub-6 GHz and millimeter-wave (mmWave) frequency bands must be integrated. However, because of their different propagation characteristics, it is still difficult to ensure effective user association between various bands. In order to dynamically balance users across sub-6 GHz and mmWave tiers, this article suggests an adaptive user association approach based on Signal and Power Threshold Adjustments (SPTA). The suggested approach maximizes network performance and minimizes service delays by optimizing user distribution using a mathematical model that takes path loss, received signal strength (RSS), and power control into account. The path loss equation is used to model the signal quality. Higher data speeds are ensured by using a threshold-based decision strategy, in which users are assigned to the mmWave band if the received power surpasses a predetermined threshold. For broader coverage, they stay in the sub-6 GHz rung otherwise. There is an expression for the utility function that maximizes system throughput while minimizing user discontent. According to simulation data, the suggested SPTA strategy outperforms static association methods in terms of throughput by an average of 35%. Additionally, while maintaining acceptable delay levels, mmWave utilization increases by 40% in high-traffic scenarios. In order to balance network load, the adaptive thresholding system dynamically reallocates users, showing notable gains in network efficiency, user satisfaction, and resource utilization. This work highlights the potential of adaptive user association driven by signal and power thresholds to support seamless connectivity in hybrid 5G and future 6G networks.

Understanding the Predictive Relationship Between Wireless Network Experience and Customer Churn

2025-04-10T19:09:14+02:00

Wireless networks have transformed society, and their evolving capabilities support numerous economic and social goals. Continued investments in wireless technologies and network coverage by mobile network operators (MNOs) depends on their achieving a favorable return on investment. Retaining existing customers by reducing churn is the most financially efficient means to improve economic returns, however the causes of customer churn are not fully understood due to the lack of studies on the relationship between wireless network quality and customer churn. This quantitative study leveraged existing secondary data from one MNO containing nine network quality factors, which formed three network quality constructs in the model, measured in 646 counties for one month in combination with a partial least squares structural equation modeling methodology to evaluate the predictive value of the network quality factors on customer churn. The study further assessed the degree to which the predictive value varies based on the population density of each county. The surprising findings suggest that network quality does not predict a meaningful amount of customer churn (p < 0.001), but that the relationship between the network quality factors and customer churn differs meaningfully depending on population density. These findings suggest ways that MNOs may fine-tune their network investments to achieve improvements in customer churn and financial results.

Enhancing Vulnerability Assessments for Electronic Voting Systems through an Augmented CVSS 3.1 Model

2025-03-22T19:04:58+01:00

This paper explores the application of the Common Vulnerability Scoring System (CVSS) to electronic voting systems, highlighting how unique considerations in these environments can be more accurately captured with an enhanced model. By incorporating criteria from the Voluntary Voting System Guidelines (VVSG), this research addresses the limitations of traditional IT-based evaluations in assessing vulnerabilities within electronic voting systems. The enhanced model was validated using a dataset of real-world vulnerabilities, showing significant improvements in accuracy and prioritization through statistical analyses. The findings offer a repeatable and extensible method for cybersecurity practitioners and election officials to assess operational risks and implement mitigation strategies to protect electrical integrity.

Dynamic Modeling of on Grid-Connected Photovoltaic Setup in Pakistan using MATLAB

2025-03-18T19:03:04+01:00

This research presents a computational modeling and simulation framework for grid-connected photovoltaic (PV) systems in Pakistan utilizing MATLAB/Simulink. Employing a Perturb and Observe (P&O) MPPT algorithm, the research develops a detailed model of a 7.5 kW PV installation in Lahore, analytically examining power generation dynamics, inverter efficiency, and grid interaction. The simulation demonstrates the system’s capability to mitigate grid dependency, with results showing effective power optimization and smooth transitions between solar generation, grid supply, and battery storage. The study bridges knowledge gaps by providing empirical insights into real-time PV system electrical characteristics, presenting a methodological approach for optimizing renewable energy system design and deployment. By quantitatively analyzing power flow, inverter performance, and battery efficiency, the research contributes valuable computational strategies for enhancing solar energy integration in regions with high solar irradiation potential.

Low-Power 5G Protocols for Sustainable Communication in Rural and Remote Networks

2025-02-23T18:54:12+01:00

While 5G technology has the ability to offer unparalleled connectivity and data speeds, high power consumption prevents its usage in rural and remote areas, where energy resources are often scarce and infrastructure is minimal. This paper provides a set of low-power 5G protocols designed to improve energy efficiency while maintaining reliable communication standards in under-served localities. Our proposed protocols incorporate adaptive protocol layering, energy-efficient modulation techniques, and advanced power-saving mechanisms, such as sleep modes and intelligent wake-up functionalities. This helps to reduce overall energy demand without compromising network performance. The findings suggest that, combined with renewable energy sources, these protocols offer a viable solution for extending 5G coverage to rural and remote areas, promoting greater digital inclusion and aligning with the aim of global sustainability.