Telecom, Volume 5, Issue 4 (December 2024) – 17 articles

The vision of the sixth generation of communication systems, commonly known as 6G, entails a connected world that provides ubiquitous connectivity and fosters the digital transformation of society. As the number of devices, services, and users continues to grow, intelligent solutions are expected to facilitate this transformation. This paper considers meta-learning as a pivotal paradigm for 6G systems, detailing its principles, algorithms, and theoretical underpinnings. The methodology involves integrating meta-learning with three potential 6G technologies: RF-based communication systems, optical communication systems, and molecular communication systems. The findings reveal the distinct characteristics of these technologies and demonstrate the potential benefits and challenges of incorporating meta-learning algorithms. Practical implications highlight how meta-learning can enhance the efficiency and adaptability of 6G systems, addressing the growing demand for intelligent and seamless communication networks. Full article

This paper presents a unified performance metric for evaluating the chronological wild geese optimization (CWGO) algorithm in wireless sensor networks (WSNs). The metric combines key performance factors—energy consumption, delay, distance, and trust—into a single measure using Lagrange interpolation, providing a more comprehensive assessment of WSN algorithms. We evaluate CWGO against E-CERP, EECHIGWO, DUCISCA, and DE-SEP across static and dynamic sensor node configurations in various wireless technologies, including LoRa, Wi-Fi, Zigbee, and Bluetooth low energy (BLE). The results show that CWGO consistently outperforms the other algorithms, especially in larger node configurations, demonstrating its scalability and robustness in static and dynamic environments. Moreover, the unified metric reveals significant performance gaps with EECHIGWO, which underperforms all wireless technologies. DUCISCA and DE-SEP show moderate and fluctuating results, underscoring their limitations in larger networks. While E-CERP performs competitively, it generally lags behind CWGO. The unified metric offers a holistic view of algorithm performance, conveying clearer comparisons across multiple factors. This study emphasized the importance of a unified evaluation approach for WSN algorithms and positions CWGO as a superior solution for efficient cluster head selection and routing optimization in diverse WSN scenarios. While CWGO demonstrates superior performance in simulation, future research should validate these findings in real-world deployments, accounting for hardware limitations and in a highly dynamic environment. Further optimization of the unified metrics’ computational efficiency could enhance its real-time applicability in larger, energy-resource-constrained WSNs. Full article

Digital terrestrial television is now implemented in many countries worldwide and is now mature. Digital Video Broadcasting-Terrestrial, second generation (DVB-T2) is the European standard adopted or deployed by European and African countries which uses Orthogonal Frequency-Division Multiplexing (OFDM) modulation to achieve good throughput performance. However, its main particularity is the number of subcarriers operated for OFDM modulation which varies from 1024 to 32,768 subcarriers. Also, mobile reception is planned in DVB-T2 in addition to rooftop antenna and portable receptions planned in DVB-T. However, the main challenge of DVB-T2 for mobile reception is the presence of a carrier frequency offset (CFO) which degrades the system performance by inducing an Intercarrier Interference (ICI) on the DVB-T2 signal. This paper evaluates the system performance in the presence of the CFO when Gaussian noise and a TU6 channel are applied. Universal Filtered Multicarrier (UFMC) and non-uniform constellations (NUCs) have previously demonstrated good performance in comparison with OFDM and Quadrature Amplitude Modulation (QAM) in DVB-T2. The impact of CFO on the UFMC- and NUC-based DVB-T2 system is additionally investigated in this work. The results demonstrate that the penalties induced by CFO insertion in UFMC- and NUC-based DVB-T2 are highly reduced in comparison to those for the native DVB-T2. At a bit error rate (BER) of ${10}^{-3}$, the CFO penalties induced by the native DVB-T2 are $0.96$$\mathrm{d}$$\mathrm{B}$ and 4 $\mathrm{d}$$\mathrm{B}$, respectively, when only Additive White Gaussian Noise (AWGN) is used and when TU6 is additionally considered. The penalties are equal to $0.84$$\mathrm{d}$$\mathrm{B}$ and $0.2$$\mathrm{d}$$\mathrm{B}$ for UFMC/NUC-based DVB-T2. Full article

This paper addresses the problem of side lobe interference in 5G networks by proposing a unique collaborative beamforming strategy based on Deep Q-Network (DQN) reinforcement learning. Our method, which operates in the sub-6 GHz band, maximizes beam steering and power management by using a two-antenna system with DQN-controlled phase shifters. We provide an OFDM cellular network environment where inter-cell interference is managed while many base stations serve randomly dispersed customers. In order to reduce interference strength and improve signal-to-interference-plus-noise ratio (SINR), the DQN agent learns to modify the interference angle. Our model integrates experience replay memory with a long short-term memory (LSTM) recurrent neural network for time series prediction to enhance learning stability. The outcomes of our simulations show that our suggested DQN approach works noticeably better than current DQN and Q-learning methods. In particular, our technique reaches a maximum of 29.18 dB and a minimum of 5.15 dB, whereas the other approaches only manage 0.77–27.04 dB. Additionally, we significantly decreased the average interference level to 5.42 dB compared to competing approaches of 38.84 dB and 34.12 dB. The average sum-rate capacity is also increased to 3.90 by the suggested strategy, outperforming previous approaches. These findings demonstrate how well our cooperative beamforming method reduces interference and improves overall network performance in 5G systems. Full article

This research aims to evaluate the reliability indices of a public address system (PAS) through the Markovian approach. Many organizations and businesses use this system to address or broadcast a message or pass on important information to the huge gatherings assembled at big premises. This system is the nerve of these organizations and businesses. The major components of a PAS are a microphone, mixer, amplifier, and speaker. These components should work in harmony with one another to execute the intended task. Any failure in these components leads to big issues for the public, and they may miss very important information. Therefore, the reliability assessment of this system is of utmost importance. The authors used the Markovian decision process to model the PAS by analyzing the various failure rates and repairs of the components. The explicit expressions for reliability, availability, and MTTF have been obtained for clear understanding about the PAS behavior with time as well as different failures. The sensitivity analysis of reliability is performed as well to determine the critical components of the system. The obtained results show that the reliability of the PAS at 2000 operated hours is 0.8. Also, the finding reflects that the PAS reliability is much sensitive with the failure rate of microphone, mixer, and amplifier. Full article

In the past few years, one of the largest industries in the world, the agriculture sector, has faced many challenges, such as climate change and the depletion of limited natural resources. Smart Agriculture, based on IoT, is considered a transformative force that will play a crucial role in the further advancement of the agri-food sector. Furthermore, in IoT-based Smart Agriculture systems, radio wave propagation faces unique challenges (such as attenuation in vegetation and soil and multiple reflections) because of sensor nodes deployed in agriculture fields at or slightly above the ground level. In our study, we present, for the first time, several models (Multi-slope, Weissberger, and COST-235) suitable for planning radio coverage in a cornfield for Smart Agriculture applications. We received signal level measurements as a function of distance in a corn field (R3 corn stage) at 0.9 GHz and 2.4 GHz using two transmitting and two receiving antenna heights, with both horizontal and vertical polarization. The results indicate that radio wave propagation in a corn field is influenced not only by the surrounding environment (i.e., corn), but also by the antenna polarization and the positions of the transmitting and receiving antennas relative to the ground. Full article

The intense diversity of the Next-Generation Networking environments like 6G and the forthcoming deployment of immersive applications with varied user-specific requirements transform the efficient allocation of resources into a real challenge. Traditional solutions like the shortest path algorithm and mono-constraint methodologies are inadequate to handle customized user-defined performance parameters and effectively classify physical resources according to these intricate demands. This research offers a new evaluation mechanism to successfully replace the aforementioned traditional path ranking and path selection techniques. Specifically, the proposed framework is integrated with optimization-oriented metrics, each indicating a unique aspect of performance for evaluating candidate network paths. The deployed metrics are then algebraically synthesized to provide a distinctive multidimensional description of the examined substrate resources. These primary and composite metrics adhere to the fundamental monotonicity and isotonicity properties of a Path Algebra; hence, the validity and optimality of the proposed evaluation mechanism is guaranteed by design. To tackle the complexity created by the variety of human-centric customization, a novel methodology that analyzes and determines the weighted influence of the synthesized metrics depending on the characteristics of the served user-centric application is also introduced. The chosen suitable weights address performance-oriented mission-critical tailored objectives for adaptive optimizations. Its innovative algebraic design allows it to successfully describe and rank candidate paths in a versatile way, whether in legacy or modern architectures. The experimental data of the first scenario show that 62.5% and 50% of highlighted path evaluations proposed by the shortest path and unidimensional constraint strategies, respectively, suffer from moderate performance-oriented values compared to the proposed framework. Likewise, the results of the second examined scenario reveal that the proposed composite metric yields more suitable path rankings by 50% in contrast to its traditional counterparts, rendering the contested evaluation mechanisms obsolete. Full article

This paper aims to provide a general review of the fundamental ideas, varieties, methods, and experimental research of the most advanced frequency selective surfaces available today. Frequency-selective surfaces are periodic structures engineered to work as spatial filters in interaction with electromagnetic (EM) waves with different frequencies, polarization, and incident angles in a desired and controlled way. They are usually made of periodic elements with dimensions less than the operational wavelength. The primary issue examined is the need for more efficient, compact, and adaptable electromagnetic filtering solutions. The research method involved a comprehensive review of recent advancements in FSS design, focusing on structural diversity, miniaturization, multiband operations, and the integration of active components for tunability and reconfigurability. Key findings include the development of highly selective miniaturized FSSs, innovative applications on flexible and textile substrates, and the exploration of FSSs for liquid and strain sensing. The conclusions emphasize the significant potential of FSS technology to enhance wireless communication, environmental monitoring, and defense applications. This study provides valuable insights into the design and application of FSSs, aiming to guide future research and development in this dynamic field. Full article

This work presents an in-depth evaluation of the telecommunications landscape in Mexico from 2015 to 2023. The study’s primary focus is on the disparities in broadband access, telecommunications infrastructure, and digital inclusion across various regions, particularly between urban and rural areas. By employing predictive models and correlation analysis, the paper identifies key factors influencing technology adoption and service bundling in households. A significant contribution of this research lies in its identification of strong correlations between broadband access, GDP growth, and the penetration of multiple telecommunication services such as fixed telephony, broadband internet, and television. The predictive models developed offer crucial insights into the regional inequalities of digital access, revealing patterns that policymakers can use to prioritize infrastructure investments. The findings underscore the essential role of public policy innovation in promoting digital inclusion, particularly in underdeveloped regions, and provide a robust analytical framework for understanding how advanced telecommunications services contribute to socio-economic development. Through this analytical approach, the study demonstrates the critical relationship between telecommunications infrastructure and regional economic performance, offering data-driven recommendations to bridge the digital divide and enhance connectivity in underserved areas. The results offer significant value for future research and policy initiatives aimed at fostering equitable access to Information and communication technologies, promoting economic growth, and ensuring broader societal inclusion in the digital age. Full article

This study presents a novel approach to enhancing the design and performance of OFDMA (Orthogonal Frequency Division Multiple Access) networks, with a particular focus on WiMAX (Worldwide Interoperability for Microwave Access) for Best Effort (BE) services. The proposed method integrates a robust Markovian analytical model with four advanced scheduling algorithms: throughput fairness, resource fairness, opportunistic scheduling, and throttling. A sophisticated simulator was developed, incorporating an ON/OFF traffic generator, user-specific wireless channels, and a dynamic central scheduler to validate the model’s accuracy and evaluate its robustness by dynamically allocating radio resources per frame. The validation study showed that the proposed model reduced simulation time by over 90%, completing analytical calculations in just 15 min, compared to nearly 2 days for simulations using conventional scheduling algorithms. Performance metrics such as the average number of active users and resource utilization closely matched those from the validation study, confirming the model’s accuracy. In the robustness study, the model consistently performed well across diverse traffic distributions (exponential and Pareto) and channel conditions. The proposed architecture increased network throughput by up to 25% and reduced latency under dynamic conditions, demonstrating its scalability, adaptability, and efficiency as a crucial solution for next-generation wireless communication systems. Full article

Technological developments within the maritime sector are resulting in rapid progress that will see the commercial use of autonomous vessels, known as Maritime Autonomous Surface Ships (MASSs). Such ships are equipped with a range of advanced technologies, such as IoT devices, artificial intelligence (AI) systems, machine learning (ML)-based algorithms, and augmented reality (AR) tools. Through such technologies, the autonomous vessels can be remotely controlled from Shore Control Centres (SCCs) by using real-time data to optimise their operations, enhance safety, and reduce the possibility of human error. Apart from the regulatory aspects, which are under definition by the International Maritime Organisation (IMO), cybersecurity vulnerabilities must be considered and properly addressed to prevent such complex systems from being tampered with. This paper proposes an approach that operates on two different levels to address cybersecurity. On one side, our solution is intended to secure communication channels between the SCCs and the vessels using Secure Exchange and COMmunication (SECOM) standard; on the other side, it aims to secure the underlying digital infrastructure in charge of data collection, storage and processing by relying on a set of machine learning (ML) algorithms for anomaly and intrusion detection. The proposed approach is validated against a real implementation of the SCC deployed in the Livorno seaport premises. Finally, the experimental results and the performance evaluation are provided to assess its effectiveness accordingly. Full article

Massive MIMO deployments have been traditionally based on dedicated links in the front-haul, i.e., between the central processing units and the Access Points (APs). Recently, cell-free massive Multiple-Input Multiple-Output (MIMO) systems based on serial front-haul links have been discussed to simplify the deployments, among other reasons. However, the power consumption models currently used for cell-free massive MIMO deployments typically assume dedicated front-haul links. This paper highlights the inaccuracy of these models when applied to serial front-hauls and proposes simple adaptations to achieve more realistic results. The results obtained for an exemplary scenario show that the front-haul power would represent 61.73% of the total consumed power with the original models. In contrast, with the proposed adaptations, it could be as low as 1.59% of the total consumed power for some serial front-haul configurations. Additionally, the impact of considering APs with lower power consumption is studied, in which case, the percentages above would become 93.15% and 11.96%, respectively. Hence the importance of having power models that fit the front-haul topology. Full article

Nowadays, Wireless Mesh Networks (WMNs) are widely deployed in communication areas due to their ease of implementation, dynamic self-organization, and cost-effectiveness. The design of routing protocols is critical for ensuring the performance and reliability of WMNs. Although there have been numerous experimental works on WMNs in the past decade, only a few of them have been tested in real-world scenarios. This article presents a comparative analysis of three proactive routing protocols, OLSR, BATMAN, and Babel, using Raspberry Pi 4 devices. The evaluation, conducted at Al-Farabi Kazakh National University, covers both indoor and outdoor scenarios, focusing on key metrics such as bandwidth, Packet Delivery Ratio (PDR), and jitter. In outdoor scenarios, OLSR achieved the highest bandwidth at 2.9 Mbps, while BATMAN and Babel lagged. Indoor tests revealed that Babel initially outperformed with the highest bandwidth of 57.19 Mb/s but suffered from scalability issues, while BATMAN and OLSR exhibited significant declines in performance as network size increased. For PDR, BATMAN performed best with a decline from 100% to 42.8%, followed by OLSR with a moderate drop, and Babel with the greatest decrease. For jitter, OLSR showed the most stable performance, increasing from 0.281 ms to 2.58 ms at eleven nodes, BATMAN exhibited moderate increases, and Babel experienced the highest rise. Full article

Airtime fairness has emerged as a key approach to enhancing wireless throughput performance. However, existing research often overlooks the precise calculation of airtime, particularly in relation to TCP acknowledgments. This paper introduces a novel method, implemented on the access point side, for accurately calculating the airtime of TCP and UDP flows. Building on this, we propose a QoS-based scheduling algorithm designed to improve fairness between upload and download traffic. The effectiveness of the algorithm is validated through experiments that accurately measure both throughput and airtime for upload and download traffic. Full article

This paper presents the latest developments regarding the single-feed Quality Wideband Linear (QWL) wire array antenna, known for its broadband and high-gain electromagnetic characteristics and robust design. A systematic review of recent advances in relation to the QWL antenna is provided, covering its driven element, director, reflector, low common-mode current interference connector, and array series-feed configuration. For the first time, an analytical expression and a quick design formula for the input impedance of the QWL antenna’s driven element, the linear Wideband High-gain Electromagnetic Structure (WHEMS) antenna, are presented. Theoretical analysis demonstrates the potential for broadband performance using the WHEMS antenna. The rugged design of the QWL array antenna offers engineering advantages such as simple feeding, low wind resistance, a lightweight construction, low cost, and structural robustness. The QWL antenna has already found applications in various industrial sectors, with potential for broader use in the future, contributing to further advancements in antenna technology. Full article

Users are usually required to share several types of data, including their personal data, as different providers strive to offer high-quality services that are often tailored to end-users’ preferences. However, when it comes to personalizing services, there are several challenges for meeting user’s needs and preferences. For content personalization and delivery of services to end users, services typically create user profiles. When user profiles are created, user data is collected and organized to meet the personalization requirements of the services. In this paper, we provide an overview of current research activities that focus on user profiling and ways to protect user data privacy. The paper presents different types of data that services collect from users on examples of commonly used Internet services. It proposes data categorization as a prerequisite for controlled data sharing between users and Internet services. Furthermore, it discusses how data generalization can be used for anonymization purposes on examples of the proposed data categories. Finally, it gives an overview of the privacy framework being developed and gives guidelines for future work focusing on data generalization methods in order to reduce user privacy risks. Full article

This paper proposes the GD (Geometric Distribution) algorithm, a novel approach to enhance the default Adaptive Data Rate (ADR) mechanism in the Long-Range Wide Area Network (LoRaWAN). By leveraging the Probability Mass Function (PMF) of the GD model, the algorithm effectively addresses biased node distributions encountered in real-world scenarios. Its ability to finely adjust the weight factor (w) or the probability of success in allocating SFs enables the optimization of spreading factor (SF) allocation, thereby achieving the optimal Data Extraction Rate (DER). To evaluate the algorithm’s performance, simulations were conducted using the fixed node pattern derived from actual dairy farm locations in Ratchaburi province, Thailand. Comparative analyses were performed against the uniform random node pattern and existing algorithms, including the ADR, EXPLoRa, QCVM, and SD. The GD algorithm significantly outperformed existing methodologies for both fixed and uniform random node patterns, achieving a 14.3% and 4.8% improvement in DER over the ADR, respectively. While the GD algorithm consistently demonstrated superior DER values across varying coverage areas and payload sizes, it incurred a slight increase in energy consumption due to node allocations to higher SFs. Therefore, the trade-off between DER and energy consumption must be carefully weighed against the specific application. Full article