Wireless Services Research Articles

Design and Optimization of Higher Education Online English Teaching Utilizing Wireless Network Technology in the Context of 5G

The global demand for wireless communication networks is a result of the widespread use of wireless devices and the related surge of wireless service providers. Data transmission speed, coverage areas, cost-effectiveness, resource utilization, security, scalability, and adaptability are all elements expected to be improved in future 5G wireless networks. Since this rapid development of network communication technology affects the delivery of English education in tertiary contexts, English teachers in colleges and universities should make use of network resources—especially the communication tools embedded in the 5G network. File transfer protocol can utilize the advanced artificial bee colony optimization algorithm (AABCOA) to realize classification, and the system proposed in this article is simulated and tested in Matrix Laboratory (MATLAB). The research results indicate that students are unsatisfied with traditional methods of English pedagogy in higher education and are keen to explore the new learning possibilities provided by 5G integrated wireless network technology.

The Method of Measuring the Occupancy of the Radio Frequency Spectrum, Varying According to the Daily Cycle

Relevance. Management of the use of the radio frequency spectrum requires taking into account the actual occupancy of radio channels and frequency bands. However, the patterns of occupancy change underlying the International Telecommunication Union (ITU-R) Radiocommunication Sector documents do not fully meet the needs of practice. Some of the ITU-R recommendations are focused on estimating local occupancy for short time intervals; other recommendations involve measurements in stationary radio channels, although only a small part of real radio channels can be counted on to have the constant occupancy throughout the time axis. At the same time, the activities of many organizations, and therefore the resources they use, are subject to a daily cycle of activity, which allows us to recommend for consideration a model of occupancy change in accordance with the daily cycle. The aim of the work is to develop a methodology for collecting information and forming an estimate of the daily occupancy change for the analyzed radio channels. Methods used. The development of recommendations for the collection of data for occupancy monitoring is based on the practical approaches of radio monitoring services and classical methods of statistical analysis. Novelty. In this paper, a new model for changing the occupancy of radio frequency channels in accordance with the daily cycle is proposed for use, as well as a statistically justified method for measuring occupancy.Result. The proposed methodology allows us to obtain a practically oriented assessment of occupancy changes, which does not require replacing the fleet of equipment traditionally used by radio monitoring services; the necessary changes can be implemented with relatively simple software modification. The paper provides preliminary recommendations for ensuring the accuracy and reliability of measurements, based on a traditionally used mathematical apparatus, which involves limiting the relative measurement error. This entails the need for very long measurements for the most important low-occupied radio channels. So, it is necessary to look for alternative measurement accuracy requirements that would meet the real needs of radio monitoring services.Practical significance. The acceptance of the developed methodology will eliminate the currently existing contradiction between the theoretical provisions underlying the ITU recommendations and the practice of conducting radio-controlled measurements.

Energy Efficient Multi-Active/Multi-Passive Antenna Arrays for Portable Access Points

This article is about better wireless network connectivity. The main goal is to provide wireless service to several use cases and scenarios that may not be adequately covered today. Some of the considered scenarios are home connectivity, street-based infrastructure, emergency situations, disaster areas, special event areas, and remote areas that suffer from problematic/inadequate network and possibly power infrastructure. A target system that we consider for such scenarios is that of an energy-efficient self-backhauled base station (also called a “portable access point—PAP”) that is mounted on a drone to aid/expand the land-based network. For the wireless backhaul link of the PAP, as well as for the fronthaul of the street-mounted base station, we consider newly built multi-active/multi-passive parasitic antenna arrays (MAMPs). These antenna systems lead to increased range/signal strength with low hardware complexity and power needs. This is due to their reduced number of radio frequency chains, which decreases the cost and weight of the base station system. MAMPs can show a performance close to traditional multiple input/multiple output (MIMO) systems that use as many antenna elements as RF chains and to phased arrays. They can produce a directional beam in any desired direction with higher gain and narrow beamwidth by just tuning the load values of the parasitic elements. The MAMP is designed based on radiation conditions which were produced during the research to ensure that the radiation properties of the array were good.

Identifying QOS impacts on the 4G LTE and 5G FWA integration using 2300 to 2400 MHz band reallocation for high-speed internet alternative to traditional fiber

Although 5G technology has been in development for a considerable time, significant challenges regarding its effective implementation still need to be addressed. A key issue lies in using frequency and ensuring coexistence with previous technologies that continue to serve existing users because users in many countries' late adoption of new technologies does not always progress smoothly. This research paper aims to evaluate 5G Fixed Wireless Access (FWA) utilizing the 2300 to 2400 MHz spectrum that is usually used in 4G LTE previous technology, positioned as a viable alternative to traditional fiber optic networks, and its impact on technology valuation in spectrum usage to solve high-speed alternative traditional fiber in rural and urban areas. The study focuses on Quality of Service (QoS) related to user experience with a standard wireless access service parameter while analyzing payload growth and revenue generation improvements compared to LTE technologies. Through rigorous trials, our results demonstrate that 5G FWA not only preserves the QoS experienced but significantly enhances it as a feasibility analysis of network productivity by combining 4G and 5G technology in one service area. The implementation trial of 5G FWA resulted in notable increases of 50 % in more than 20 Mbps data throughput, contributing to 27 % substantial growth in payload and revenue in an area using only 4G LTE before 5G FWA was implemented. By providing detailed performance metrics, the trials highlighted the potential for 5G FWA to deliver broadband services more efficiently and cost-effectively, particularly in regions where geographical or economic factors constrain the expansion of fiber optics.

Empirical Mode Decomposition Based Amplify and Forward Technique for Cooperative Cognitive Radio System

The rapid growth in the mobile industry due to increase in number of users accessing diverse services causes a high demand for radio spectrum. Nonetheless, the radio spectrum allocated for different wireless communication services is restricted. Cooperative Cognitive Radio (CCR) technique with Amplify and Forward (AF) relaying protocol used to address the problem suffers from noise amplification resulting in poor reception at the destination. Hence, in this paper, Empirical Mode Decomposition (EMD) based AF technique for CCR system was carried out to improve the performance of the existing CCR with AF relaying protocol. The transmitted signal from Primary User (PU) was received at the Secondary User (SU) where SU superimposed its own signal using Exclusive OR (XOR) rule. The combined signal from XOR was made to pass through EMD and amplified using AF by multiplying with the relay gain. The amplified signal was radiated to PU and SU receivers during the second hop transmission. The multiple copies of the receive signal at the SU receiver at different number of path (L = 2, 4) were combined at destination using Maximal Ratio Combiner (MRC). Mathematical expression for Bit Error Rate (BER) and Throughput (TP) were derived using the Probability Density Function (PDF) of the Nakagami-m fading distribution. Extensive simulations using MATLAB R2021a were employed to assess the effectiveness of the proposed technique and evaluated using BER and TP by comparing with the existing AF CCR. The EMD based AF technique proposed gave better performance with 75.2% reduction in BER and 21.86% increase in TP over the existing AF technique for CCR. The proposed technique can be deployed to improve the performance of cooperative cognitive radio system.

Efficient Radio Resource Management in Cell-less Wireless Communication Systems

In this paper, the particle swarm optimization (PSO) method with dynamic generation of biasing factors is used to determine the optimal particle size, maximize cell spectral efficiency (CSE) and balance the load in 5G networks. This work studies two distinct interference scenarios: in the first approach, CSE is calculated with varying numbers of users, when different radio services are used by each tier (when several radio access technologies are used), and when interference is received by the consumer only from the same tier base stations (BSs). In the second approach, interference is created when all levels use the same radio services and interference from BSs belonging to the same tier and other tiers is received by the consumer. Simulation results show that the cell-less network performs better than the cellular network in terms of maximizing CSE and balancing the load.

Energy consumption optimization in green cognitive radio networks based on collaborative spectrum sensing

In the realm of green communications, the focus is on achieving high spectrum efficiency and low energy consumption. This paper addresses the crucial goal of reducing energy usage in green cognitive radio networks (CRNs) during communication between secondary users (SUs) and primary users (PUs). This paper proposed an energy consumption optimization model (ECOM) for green CRN utilizing collaborative spectrum sensing thereby minimizing the environmental impact and prolonging the operational lifetime of devices. The collaborative spectrum sensing proved its role in optimizing the energy consumption in the green CRN. An energy-efficient scheduling algorithm is implemented in ECOM, in which the SUs can be scheduled to perform their sensing process in a time-division manner to reduce energy consumption. Applied collaborative spectrum sensing serves as a valuable resource for researchers, network operators, and policymakers seeking to balance the increasing demand for wireless communication services with the imperative of sustainability. The simulation results and mathematical proof emphasize that ECOM demonstrates reduced energy usage and increased average effective throughput when compared to other recent models.

Formal estimation of wireless network services for signal strength and electromagnetic wave association in an International Green University

The United Nations focuses on 17 urgent problems to call for action in all countries. Goal 7 of the 17 urgent problems is based on affordable and clean energy. Since 2017, National Taitung University (NTTU) has dedicated more time and effort to attain the wisdom, health, sustainability and aesthetics as an international green university. To accomplish this, we adhere and construct a safe radiofrequency and electromagnetic wave environment to achieve healthy and sustainable campus objectives. According to the UI GreenMetric World University Rankings, NTTU was ranked 74th in 2021, 67th in 2022 and 58th in 2023. In this study, we propose a formal estimation of wireless network services for classrooms or smart spaces to achieve the goal of safe radiofrequency and electromagnetic waves. Inside classrooms or smart spaces, better wireless signal strength and safer electromagnetic waves are achieved. Moreover, the proposed method can be used to determine the quantity of wireless access points for a given classroom or smart space to avoid unsafe electromagnetic waves and inappropriate energy consumption. The experimental results show that all benchmarks meet the wireless exposure limits of the WHO and physician safe technologies in the NTTU.

Determining the relationship between mobile phone network signal strength and radiofrequency electromagnetic field exposure: protocol and pilot study to derive conversion functions

Mobile phones continuously monitor and evaluate indicators of the received signal strengths from surrounding base stations to optimise wireless services. These signal strength indicators (SSIs) offer the potential for assessing radiofrequency electromagnetic field (RF-EMF) exposure on a population scale, as they can be related to exposure from both base stations and handset devices. Within the ETAIN (Exposure To electromAgnetic fields and plaNetary health) project, an open-access RF-EMF exposure app for smartphones, named "5G Scientist Monitor”, has been developed using citizen science. This paper delineates a measurement protocol for deriving formulas to convert the app SSIs into electric field values to estimate RF-EMF exposure. It presents pilot study results from measurements taken at four locations in Lyon, France (FR), and 14 locations in the Netherlands (NL), using three different phone models and the most common network providers in each country. The measurements were conducted while executing different usage scenarios, such as calls or data transmission. The exposimeter ExpoM-RF4 and on-body electric field probes were used to measure exposure from far-field sources and the handset, respectively. Two-minute aggregates were considered the sample unit for analyses (n=891 in NL and n=395 in FR). Regression analyses showed a positive log-linear relationship between Long Term Evolution (LTE) SSIs and far-field RF-EMF exposure when aggregating data by location (coefficients for the normalised RSSI: 0.91 [95% CI: 0.55 - 1.28] in FR, 1.09 [95% CI: 0.96 - 1.22] in NL). Negative log-linear trends were observed for handset-related RF-EMF exposure at the ear (-0.31 [95% CI: -0.46 - -0.16]) and chest (-0.20 [95% CI: -0.37 - -0.03]) during data transmission scenarios. These results demonstrate that the 5G-Scientist-Monitor app can be implemented for smartphone-based RF-EMF estimation. However, uncertainties in individual measurement points highlight the need for further data collection and analysis to improve the accuracy of exposure estimates.

Automated PIM Detection in Wireless Networks via Smart Data-Driven Techniques

As the number of base stations keeps increasing due to ever-growing wireless services and pervasive connectivity, the operational costs for network service providers rises proportionally. In addition, with the evolution of wireless technologies and the development of next generation networks such as 5G and 6G, network operators are inevitably expected to encounter more complex challenges. One such network issue is the Passive Intermodulation (PIM) problem that is observed in both 4G and 5G networks. It degrades the user experience and radio resource efficiency while leading to an operational overhead for detecting and mitigating it on the operator side. Although there is a significant body of work regarding PIM detection and cancellation methods, the majority of such studies depends on hardware solutions and manual investigation by network engineers, which is costly in terms of time and labor. In this paper, we propose two methods using unsupervised and semi-supervised Machine Learning (ML) approaches, namely a time-series-based anomaly detection technique and an autoencoder-based one, for identifying PIM problems in network sites. The proposed solutions utilize a set of Key Performance Indicator (KPI) data of base stations obtained from network management systems for a significantly long time interval and detect possible PIM problems without the need for a human in the loop. We measure and analyze the performance of our solutions, with the guidance of experienced network engineers, on our collected dataset.

Analysis and Classification Of Wireless LAN Network Service Quality Using The Naive Bayes Algorithm In The Department Of Informatics and Computer Engineering, Faculty Of Engineering, State University Of Makassar

This study aims to determine the Quality of Service outcomes and the classification results of the Naive Bayes Algorithm on the Wireless LAN network quality in the Department of Informatics Engineering and Computer Faculty of Engineering at Makassar State University. This study uses the Action Research method with a quantitative approach. It conducts 54 tests using Wireshark in two different sessions to be compared for each time conducted during the research. The results of the research indicate that the status of the Wireless LAN network in the Department of Informatics Engineering and Computer Faculty of Engineering at Makassar State University falls into the "Good" category with the highest value of 59.26% , with an algorithm accuracy of 65.43%. Both testing sessions, morning session from 08:30 to 09:00 and afternoon session from 13:30 to 14:00, are categorized as "Good" according to the TIPHON standardization category as well as based on the Naive Bayes Algorithm classification results. Based on the research findings, it is recommended that the measurement of network service quality can utilize software other than Wireshark and increase the amount of test data to improve the accuracy of the Naive Bayes algorithm.

Deep learning‐based spectrum sharing in next generation multi‐operator cellular networks

SummaryOwing to the exponential increase in wireless network services and bandwidth requirements, sharing the radio spectrum among multiple network operators seems inevitable. In wireless networks, enabling efficient spectrum sharing for resource allocation is quite challenging due to several random factors, especially in multi‐operator spectrum sharing. While spectrum sensing can be useful in spectrum‐sharing networks, the chance of collision exists due to the inherent unreliability of wireless networks, making operators reluctant to use sensing‐based mechanisms for spectrum sharing. To circumvent these issues, we utilize an alternative approach, whereby we propose an efficient spectrum‐sharing mechanism leveraging a spectrum coordinator (SC) in a multi‐operator spectrum‐sharing scenario assisted by deep learning (DL). In our proposed scheme, before the beginning of each timeslot, the base station of each operator transmits the number of required resources based on the number of packets in the base station's queue to SC. In addition, base stations also transmit the list of available channels to SC. After gathering information from all base stations, SC distributes this collected information to all the base stations. Each base station then utilizes the DL‐based spectrum‐sharing algorithm and computes the number of resources it can use based on the number of packets in its queue and the number of packets in the queues of other operators. Furthermore, by leveraging DL, each operator also computes the cost it must pay to other operators for using their resources. We evaluate the performance of the proposed network through extensive simulations. It is shown that the proposed DL‐based spectrum‐sharing mechanism outperforms the conventional spectrum allocation scheme, thus paving the way for more dynamic and efficient multi‐operator spectrum sharing.

Resource allocation for device-to-device communications underlaying uplink cellular networks

Underlying cellular networks, device-to-device (D2D) communications are a practical network technology that can increase power efficiency and spectrum usage for close-proximity wireless services and applications. However, D2D link interference, when sharing resources with cellular users (CUs), poses a major challenge in such distribution situations. In this research, we primarily utilize wireless channel data that exhibits slowly shifting large-scale fading to conduct spectrum sharing and power allocation. The overall ergodic capacity of all cellular user equipment (CUE) links is initially considered as the optimization target in order to maximize the overall throughput of CUE links while ensuring the reliability of each D2D link. Then, the expansion of the minimum ergodic capacity is measured to ensure a more consistent capacity performance across all CUE links. We utilized algorithms that are resilient to channel fluctuations and produce optimal resource allocation. We use MATLAB, and the computer simulation validates its intended performance.

Performance analysis of microstrip patch antenna for wireless communication systems

<p>An antenna may be thought of as a temporary tool that directs radio waves for transmission or reception. Aside from being inexpensive, small, easy to manufacture, and compatible with integrated electronics, the microstrip patch antenna (MPA) offers several other benefits as well. These two methods are often seen as low-cost, adaptable, dependable, high-speed data connection choices that promote user mobility. An overview of how MPA have been used throughout the last several decades is provided in this article. It has been suggested that there are many approaches to enhance the performance of MPA, including the use of composite antennas, highly integrated antenna/array and feeding networks, operating at relatively high frequencies, and using cutting-edge manufacturing methods. Dual or multiband antennas are essential for meeting the demands of wireless services in this rapidly evolving wireless communication environment. Here is an overview of the patch antenna literature for wireless local area network (WLAN) and worldwide interoperability for microwave access (WiMAX) applications.</p>

A framework for automated reconstruction of communication towers from terrestrial laser scanning point clouds

ABSTRACT Communication towers provide reliable wireless communication services and play a vital role in modern society. This paper presents an automatic 3D reconstruction framework for communication towers based on point clouds. The antenna is reconstructed by a model-driven method, which constructs an energy function including the data and smoothing terms to evaluate the model accuracy. The parameters of the antenna model are obtained by minimizing energy function with hybrid Genetic Algorithm (GA) and Simulated Annealing (SA). And the predefined model is transformed using these parameters to achieve antenna 3D reconstruction. For tower body reconstruction, the point cloud of the tower body is finely extracted with the region growing followed by piecewise fitting to obtain the model. The performance of the proposed method is evaluated on point clouds from six scenes. The average root-mean-square error (RMSE) of antenna reconstruction is 1.3 cm. The average precision, recall, and F1-score values of the tower body point extraction are 99.9%, 93.5%, and 96.6%, respectively. The average RMSE of tower body reconstruction is 1.2 cm. The experimental results indicate that the method can effectively reconstruct the antenna and tower body with point clouds, providing a feasible framework for the 3D reconstruction of communication towers.

Case Study Using Artificial Intelligence Broadcasters for Broadcasting Programs on Radio Mustang Jakarta

The research focuses on how the use of artificial intelligence (AI) radio broadcaster applications in broadcasting programs that have penetrated the radio business market. This study uses a qualitative method with a case study approach that studies the use of AI radio broadcasters used by traditional media of radio stations. The study examines from various perspectives such as the development of information and communication technology, the innovation of radio programming, the use and process of AI technology in radio, as well as the impact on the radio business of the digital age. Nowadays innovative technologies and distribution methods are beginning to emerge that have a profound effect on how to listen and view radio broadcasts through the internet media. It is for the revolution of radio stations with new opportunities, but also new challenges in addition to conventional radio services available, now available AI technology that has a wide spectrum.

An ultra‐low‐power low‐noise amplifier using a combination of current reuse and self‐forward body bias techniques for biomedical applications

SummaryLow‐power low noise amplifiers (LNAs) are critical block in the radio frequency (RF) front‐end of medical device radiocommunications service (MedRadio) receivers for amplifying weak received signals while introducing minimal noise. Despite the inherently low transconductance of MOS transistors, it is possible to achieve low noise, high gain, and good linearity in low power LNAs. This paper presents a combination of techniques to realize an ultra‐low‐power LNA with a compact size and high performance. The proposed LNA utilizes multiple gm‐boosting and self‐forward body bias techniques, with certain transistors operating in weak inversion. Additionally, the Multi‐Objective Inclined Planes System Optimization algorithm is employed to determine the optimal values of the circuit components, thereby achieving the best compromise among the various performance parameters. The proposed LNA with buffer is designed and simulated using an 180 nm CMOS process over the frequency band of 0.3–1 GHz. Simulated results show that the proposed LNA achieves a gain of 19.6 dB, a noise figure of 5.1 dB, good input matching (S11 < −10 dB), and a third‐order intermodulation intercept point (IIP3) of 3.8 dBm. Additionally, it consumes 320 μW (without buffer) from a 1 V power supply, and the chip area is 235 μm × 372 μm. The simulated results demonstrate that the proposed ultra‐low power LNA is a promising candidate for biomedical applications.

WOMAN SAFETY APP

In today’s world, people using smart phones have increased rapidly and hence, a smart phone can be used efficiently for personal security or various other protection purposes. The heinous incident that outraged the entire nation has woken us to go for the safety issues and so a host of new apps have been developed to provide security systems to women via their phones. This project presents, an Android Application for the Safety of Women, this app can be activated by just shaking phone three times, whenever need arises. By just three times shake identifies the location of place through GPS and sends a message comprising this location URL to the registered contacts to help the one in dangerous situations. The unique feature of this application is to send the message to the registered contacts after the phone is shook for three times. Instant location tracking information via SMS helps to find the location of the victim quickly and can be rescued safely. A wide range of tracking systems has been developed for tracking vehicles and displaying their position on a map, applications has been developed which tracks the mobility of a human being. Now a days tracking a person’s mobility has become a crucial issue, specifically in case of women. If tracking a criminal could be implemented as a system which is cost effective and can be used for tracking a human being using a GPS equipped mobile phone rather than using a handheld GPS receiver. The main aim of our project is to develop an application that reduces the overall cost of tracking based on GPS system, which is satellite-based service, and it is available 24X7 everywhere in the whole world. GPS system can be used to get location which includes details like latitude, longitude and altitude values along with the time details, etc. It is a free of cost service available to every individual. In order to track the movement of the person we have used Google maps for mapping the location sent by the mobile phone. The mobile phone fetches the GPS location which communicates with the server using General Packet Radio Service (GPRS). This system is a low-cost service which is wireless data communication system. Mobile phone equipped with GPS receiver are easily available in the market, it is a latest technology. The mobile phone technology has enabled us to communicate across the world. The GPRS is one of the best and cheapest mode of communication available today. Key Words: Android, GPS, URL, Registered Contacts

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

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

Design of a novel compact low specific absorption rate multiple input multiple output antenna for 5G sub-6 GHz terminals

This investigation presents a new design and analysis of a fourteen elements massive multiple input multiple output (MIMO) compact low specific absorption rate (SAR) antenna system for 5G and beyond terminals. The MIMO antennas are realized for sub-6 GHz LTE-band 46 (5.1-5.8 GHz) long-term evolution 5G wireless communication services. The proposed antenna system is designed on an FR-4 dielectric constant 4.3 substrate consisting of the main board and four sideboards. The radiating elements are developed on the sideboards consisting of a monopole antenna and two metamaterial unit cells, as well as the feed line is designed on the principal board. The overall volume of the proposed structure is 150×80×7.5 mm. Through the use of the metamaterial unit cells, the proposed antennas have been arranged in close proximity without developing a strong mutual coupling. The results obtained were very important in terms of impedance matching, isolation among the antennas, and good gain. Even, the SAR analysis at the operating frequency band of 5.5 GHz proves that the proposed MIMO antenna system satisfies safety standards set for human exposure at the international level. Therefore, the proposed massive MIMO antenna structure is a potential solution for future communication applications.