Wi-Fi Users Research Articles

Legal Protection of Public WiFi Users from Cyber Crime

This research explores the legal protection of public WiFi users from cybercrime, with a focus on public awareness, security standards, and law enforcement. The main findings show that the public's low awareness of public WiFi security risks is caused by a lack of education and information, wrong perceptions of security, and dependence on technology. Additionally, security standards implemented by public WiFi service providers vary and are often inadequate, influenced by a lack of strict regulation, implementation costs, and lack of technical knowledge. Law enforcement against cybercrime has also proven weak, with limited resources, lack of international cooperation, and inadequate regulations as the main causes. This research recommends increasing public education, strengthening security regulations, increasing law enforcement capacity, and better international cooperation. The implementation of these steps is expected to create a safer digital environment and increase legal protection for public WiFi users from the threat of cybercrime.

Improving cache-enabled D2D communications using actor–critic networks over licensed and unlicensed spectrum

Cache-enabled Device-to-Device (D2D) communications is an effective way to improve data sharing. User Equipment (UE)-level caching holds the potential to reduce the data traffic burden on the core network. Licensed spectrum is utilized for D2D communications, but due to spectrum scarcity, exploring unlicensed spectrum is essential to enhance network capacity. In this paper, we propose caching at the UE-level and exploit both licensed and unlicensed spectrum for optimizing throughput. First, we propose a reinforcement learning-based data caching scheme leveraging an actor–critic network to improve cache-enabled D2D communications. Besides, licensed and unlicensed spectrum are devised for D2D communications considering interference from existing cellular and Wi-Fi users. A duty cycle-based unlicensed spectrum access algorithm is employed, guaranteeing the Signal-to-Interference and Noise Ratio (SINR) required by the users. The unlicensed spectrum is prone to data packets collisions. Therefore, Request-to-Send/Clear-to-Send (RTS/CTS) mechanism is utilized in conjunction with Carrier Sense Multiple Access with Collision Avoidance (CSMA/CA) to alleviate both the interference and packets collision problems of the unlicensed spectrum. Extensive simulations are performed to analyze the performance gain of our proposed scheme compared to the benchmarks under different network scenarios. The obtained results demonstrate that our proposed scheme possesses the potential to optimize network performance.

Assessing the Impact of the Burst Size in the FTM Ranging Procedure in COTS Wi-Fi Devices

The wide availability of the Wi-Fi infrastructure together with the recent integration of the IEEE 802.11mc capability in common-off-the-shelf (COTS) devices, have contributed to increasing the interest of the research community in the fine time measurement (FTM) technique, which allows two Wi-Fi devices to estimate distances between each other. However, one of the main issues yet to be solved is how it scales with an increasing number of Wi-Fi devices injecting location-specific traffic in the shared medium. While the recently released IEEE 802.11az standard will still take time before being integrated in COTS devices, this paper aims at assessing the impact of the burst size on the ranging performance of COTS Wi-Fi Android devices running release 12. While increasing the burst size is expected to bring higher stability in the observed distance, on the other hand a longer transmission period for location-only purposes may jeopardize the transmission of data traffic among Wi-Fi users. Several models of smartphones and APs, and different frequency bands, have been considered in order to evaluate the behavior of the FTM procedure in real devices, showing that not always the newest or most expensive ones perform better. Also, it is shown that using the minimum burst size significantly decreases the performance and it is thus not recommended. While bursts longer than 8 may no be always supported by all the models and/or frequency bands, the small improvements in ranging estimations obtained when they are used do not always justify the increased location traffic injected in the network.

Application of Improved HF-DBSCAN Algorithm in Analyzing Complex Trajectory Data of Wi-Fi Users in Smart Campus

ABSTRACT With the development of wireless network technology and the increasingly widespread application of mobile intelligent terminals, a large amount of wireless network data has been generated in smart campuses. By analyzing the trajectory data through clustering algorithms, more valuable user data information can be obtained. However, current clustering algorithms have high computational difficulty, long running time, and poor clustering accuracy for complex trajectories. Based on this background, the study proposes a spatial clustering of Application with Noise by Density-Based Spatial Clustering of Application with Noise combining Hausdorff and Frechet. The method is denoted as (Hausdorff and Frechet-Density Based Spatial Clustering of Application with Noise, HF-DBSCAN). DBSCAN denotes the Density Based Spatial Clustering of Application with Noise. In the experimental results, compared to the AH-DBSCAN, DBSCAN, and FD-DBSCAN algorithms, the running time of HF-DBSCAN algorithm in complex trajectory cluster analysis is reduced by 59.33%, 39.82%, and 35.12%, respectively, and the contour coefficient is closer to 1; the Davies-Boldin Index (DBI) values decreased by 59.24%, 64.42%, and 68.24%, respectively. The experiment shows that the optimized HF-DBSCAN algorithm has lower computational difficulty, better clustering performance, and higher clustering accuracy, which verifies the effectiveness of this study.

On the Integration of Standard Deviation and Clustering to Promote Scalable and Precise Wi-Fi Round-Trip Time Positioning

Recently, the use of fingerprinting has been proposed for positioning using the Wi-Fi RTT estimations gathered by IEEE 802.11mc devices. Wi-Fi RTT poses a challenge on scalability due to the location-specific traffic injected in the network, which may limit the data traffic transmissions of other Wi-Fi users. In this respect, fingerprinting has been regarded as a promising scalable technique, compared to multilateration. While coupling other metrics should bring relief to the system, reducing the number of APs to which RTT measurements are requested alleviates the burden in specific cells. But how far may we go? This paper assesses several methods aimed at reducing the Wi-Fi RTT overhead while preserving the precision of the calculated position. The use of the Wi-Fi RTT standard deviation is assessed for the first time, being especially useful when the number of RTT procedures is minimized. The application of clustering can also improve position estimates while leveraging bandwidth for other users’ purposes.

Resource and trajectory optimization for UAV-assisted MEC communication systems over unlicensed spectrum band

The new radio unlicensed (NR-U) technology is proposed by 3GPP to extend NR to the unlicensed spectrum because of the shortage of the licensed spectrum. Different from the ground and fixed communication equipment-based unlicensed spectrum access scheme, the unmanned aerial vehicle (UAV) mobile platform-based unlicensed spectrum access scheme is not only related to incumbent users but also its trajectory and resource allocation. Therefore, this paper proposes a hybrid unlicensed spectrum access scheme for the UAV-assisted unlicensed mobile edge computing (MEC) communication (UAUM) system, where each flight time slot of the UAV is divided into two parts: power free (PF) and power controlled (PC) stages. In the PF stage, the transmit power is only restrained by the unlicensed spectrum regulations, and thus the UAV can provide high-rate services for real-time downlink users (RDUs) and uplink computing users (UCUs). In the PC stage, the transmit power of the UAV is mainly restrained by the interference to WiFi devices, and thus UAV can be allowed to provide low-rate services for non-realtime downlink users (NDUs) without affecting WiFi users. Based on the proposed scheme, a multi-variable optimization problem regarding trajectory, bandwidth, transmit power, and duty cycle is formulated to maximize the total offloaded computing bits on the premise of ensuring the quality of experience of RDUs, NDUs, and WiFi users under the maximum energy budget. To solve this problem efficiently, we propose an iterative algorithm based on the block coordinate descent method and successive convex approximation technique to decompose the original problem into four optimization subproblems of trajectory, bandwidth, transmit power and duty cycle, which are then solved alternatively in an iterative manner. A large number of simulation results demonstrate that in terms of spectrum efficiency and total offloaded computing bits, the proposed algorithm outperforms other unlicensed spectrum access schemes and optimization algorithms. The other performances of the proposed algorithm are deeply evaluated to prove its effectiveness and feasibility.

Sistem Pembatasan Jaringan Internet Wi-Fi berbasis Voucher menggunakan Perangkat MikroTik

The high mobility in this information technology era has led many people to use wireless (Wi-Fi) internet access media instead of wired media. Devices such as laptops, tablets, PCs, and gadgets are inseparable from wireless technology. This study aims to limit Wi-Fi users and improve the efficiency and performance of the hotspot network. This study implements a voucher system using MikroTik devices and AAA (Authentication, Authorization, and Accounting) functions. The research development method uses a waterfall model consisting of 5 stages: requirements analysis, topology design, system implementation, performance testing, and maintenance. Data collection techniques involve direct observation of hotspot users who use vouchers, recording data on voucher duration, the number of users, and usage time. The collected data is analyzed quantitatively to evaluate the efficiency and performance of the voucher system and to gain insights into user experiences. The research results show successful implementation with 1, 3, 5, 8, 15, and 20 users using vouchers for 30-, 60-, and 120 minutes during morning, afternoon, and evening testing periods. Based on the testing and data analysis, this voucher-based Wi-Fi user restriction system successfully improves the efficiency of the Wi-Fi hotspot network by reducing the risk of illegal access and data theft.

KAJIANSOSIAL-EKONOMI UMKM "WIRELESS FIDELITY (WIFI)" DI PERUM MAESA UNIMA

The purpose of this research is to examine the socioeconomic wireless fidelity (wi-fi) company as one of Perum Maesa Unima's SMEs. The qualitative research technique utilized in this study, also known as scientific research, is research that does not include computations and emphasizes the natural character of data sources. The most significant and fundamental analysis in employing qualitative data, according to Miles and Huberman, is data reduction, presentation, and conclusion. Data collecting methods such as observation, interviews, and documenting. The findings of this study show that students require the internet, that SMEs profit from students as Wi-Fi users, and that students must adapt to the internet as part of the learning process in higher institutions.

On Construction of Precise Positioning System via IEEE 802.11ax

Wireless network stability is critical for organizations. Most companies rely on a solid internet connection for at least part of their day-to-day activities. It is essential to show the fast and high capacity of Wi-Fi. Wireless network management also significantly supplies the user with quality service and helps the system administrator manage and track the network infrastructure. The user must be able to stay connected. The Wi-Fi connection engine was applied in this paper using the Analysis and Locations Engine (ALE). ALE provides the information, including MAC address, location, floor information, and the building where the device belongs. From this data, we presented the web visualization of the Wi-Fi network monitoring system on the map using Cesium. Except for the common information about Wi-Fi users, this work presents the vertical position visualization in the buildings to provide more details about user usage. This work analyzes the user experience of using the proposed system, and latency is the appropriate metric to measure the user experience. The experiment results show that the optimized number of cluster partitions is four, and the latency is less than 1.3 seconds for 4 MB data. Therefore, the system provides a visualization platform with acceptable system response, and Internet managers would consider the proposed system as the management tool.

Performance analysis for MU-MIMO enabled LTE-U networks coexisting with D2D and WiFi network

LTE-Unlicensed (LTE-U) network is a type of cellular communication network operating the unlicensed spectrum. Offloading cellular traffic to WiFi or Device-to-Device (D2D) network can lead to interference among them. Applying Multiple-Input Multiple-Output (MIMO) technology in Cellular Base Station (CBS) and WiFi Access Point (WAP) can effectively reduce interference among D2D, WiFi and cellular networks. To our best knowledge, there is still no literature to explicitly study the characteristics of the traffic offloading in the Multiple-User MIMO (MU-MIMO) enabled network coexisting with D2D and WiFi networks. In this article, we thoroughly investigate the impact of D2D communication and MU-MIMO enabled WAP and CBS on the performance of the LTE-U network. More specifically, we derive the expressions of the downlink rates for cellular users, D2D users, and WiFi users with incomplete Channel State Information (CSI) feedback, and we validate our analysis through Monte-Carlo simulation. Numerous results illustrate the following conclusions. (i) Increasing the number of WiFi users, the length of CSI feedback, and the quantity of D2D pairs that reuse the channel with a single cellular user can increase the total throughput of the heterogeneous network. (ii) The total throughput decreases when more than two users are offloaded to D2D pairs, and increases as the number of offloaded users increases when less than six users are offloaded to WiFi network. (iii) Simultaneously offloading traffic to D2D pairs and WiFi network can obtain higher total throughput than offloading traffic to only one of them.

Pengaruh Faktor Budaya, Faktor Sosial Dan Faktor Pribadi Terhadap Keputusan Pembelian Jasa Pada PT. Telkom Kota Metro

In line with the rapid economic growth of Indonesia, the demand for telecommunicationsservices is also increasing, so that PT Telkom Indonesia must be able to serve the needs ofthe community by increasing the number of connection units and the quality oftelecommunication facilities. This improvement effort has been carried out by implementingPT Telkom's policies, namely, the best service, the best image and the best results. All aredirected to customer satisfaction of PT Telkom service users. This study aims to determine 1)To determine whether cultural factors influence purchasing decisions. 2) To find out whetherthere is an influence of social factors on purchasing decisions. 3) To find out whether there isan influence of personal factors on purchasing decisions. 4) To find out whether there is aninfluence of cultural factors, cultural factors, personal factors, social factors together onpurchasing decisions. The survey method was chosen as the primary data source. The surveymethod focuses on collecting data from respondents who have certain information, thus enabling researchers to solve problems. Data collection was carried out using a questionnaireor questionnaire instrument. Based on the estimated time and limitations, the population inthis study were all wifi users from Telkom Indonesia on metrp. then the population is takenbased on the largest number of buyers in a year in 2020, which is as many as 133 buyers. Theresults show that 1) there is a positive and significant influence between cultural factors onpurchasing decisions 2) there is a positive and significant influence between social factors onpurchasing decisions. 3) there is a positive and significant influence between personal factorson purchasing decisions 4) there is a positive and significant influence between personalfactors on purchasing decisions. positive and significant influence between cultural factors,personal factors, social factors on purchasing decisions.

The Effect of Personal Selling and Advertising on Purchasing Decisions with Brand Awareness as an Intervening Variable

This study aims to determine the effect of personal selling on purchasing decisions, the effect of advertising on purchasing decisions, the effect of brand awareness on purchasing decisions, the effect of personal selling on purchasing decisions mediated by brand awareness, and the influence of advertising on purchasing decisions mediated by brand awareness. This research was conducted on My Republic WiFi users in Surabaya with 150 respondents. The sampling technique of this study uses probability sampling using random sampling, in which the researcher determines without regard to the existing strata in the population. Data collection techniques in this study used a questionnaire. Data analysis technique using Process Macro Hayes. The results of this study indicate that the personal selling variable has a significant positive effect on purchasing decisions. Advertising variable has a significant positive effect on purchasing decisions. The brand awareness variable has a positive and significant effect on purchasing decisions. Brand awareness mediates the relationship between personal selling and purchasing decisions. Brand awareness mediates the relationship between advertising and purchasing decisions.

Contention or Symbiosis: The Model-Based and Model-Less Transmission Mode Selections for Internet of Things in Unlicensed Band

In this work, we investigate a spectrum-sharing network, where an Internet-of-Things (IoT) system and a WiFi system coexist in the unlicensed band. The IoT devices can actively transmit signal by contending for the channel with the WiFi users. Alternatively, they can also convey information by passively backscattering the ambient WiFi signal, and thus form symbiosis with the WiFi during the transmission. Since the active and the passive transmission mode have their own merits under specific circumstances, how to select one of them adaptively and efficiently with guaranteeing the normal service of the WiFi system is of high importance. To solve this problem, we firstly investigate the effective throughput of the IoT system from the cross-layer perspective. Then, by jointly considering the effective throughput and the power consumption of the IoT system, we formulate the transmission mode selection problem. Two solutions are given depending on whether the signaling between the two systems is available. By entailing the inter-system parameter sharing, the model-based transmission mode selection scheme is proposed, which gives the closed-form optimal solution. When the inter-system parameter sharing is absent, the model-less transmission mode selection scheme is proposed by using deep reinforcement learning (DRL) technique. Extensive simulation results validate the theoretical analysis, and demonstrate the effectiveness of the proposed transmission mode selection schemes.

Dynamic Pricing for Intelligent Transportation System in the 6G Unlicensed Band

The use of an unlicensed band has significantly boosted the capacity of cellular technology via LTE in unlicensed band, license assisted access, and new radio in unlicensed band. Likewise, cellular vehicle to everything in the shared band is also gaining momentum for intelligent transportation systems. Nevertheless, the cellular operator has to wisely decide the proper allocation of this unlicensed band as well as its licensed band, to its users. As the cellular operator cannot guarantee the quality of service in the unlicensed band, motivating the users to offload into the unlicensed band is one of the challenging tasks for the operator. In this paper, we propose an economical approach to encourage users to offload in the unlicensed band while maximizing the utility function for the users and revenue for the operator. Under the proposed scheme, fairness with legacy WiFi users operating in common channel is considered. We investigate the interaction between the operator and the user using a Stackelberg game. We derive the best response function for both operator and user to maximize its utility under complete information, such as service contract and usage pattern. However, it is not always practical to know the comprehensive knowledge of the user in a highly dynamic environment. Thus, a various multi-armed bandit algorithms are used and compared to drive convergence towards an optimal solution. Simulation results have been presented to compare and verify the performance of our proposed scheme.

Enhanced Resource Allocation in D2D Communications With NOMA and Unlicensed Spectrum

Device-to-device (D2D) communications with non- orthogonal multiple access (NOMA) have been proved in enhancing the network capacity and reducing the burden of the traditional cellular network. Due to reusing the same resources, the underlying D2D communication may cause high interference to cellular users, and thus reducing the network throughput. To alleviate this issue, we consider moving D2D users to the unlicensed band. In this case, D2D users can reuse the resources in cellular networks or share the unlicensed band with WiFi users. However, a critical question is how to effectively perform NOMA user clustering and determine D2D pairs that should use unlicensed band and how to guarantee the quality service of users at both networks. Our objective is to maximize the network throughput by investigating a joint resource allocation problem of user clustering, power control, and D2D mode selection. Since the formulated problem is a mixed-integer nonlinear programming problem, finding an optimal solution is a great challenge. To solve this problem, we propose to use a swarm intelligence approach, namely whale optimization algorithm in solving our optimization problem with an efficient solution. Through simulation results, we show that our proposed scheme attains a better performance than other alternative schemes.

Portable Spectroscopy System for Environmental Monitoring: An SO2 Case Study

In this work, a compact, portable, extended operating life, maintenance-free and remotely operable apparatus for optical absorbance measurements in the ultraviolet region is proposed. The system is useful for concentration measurement of chemical species or biological agents that exhibit ultraviolet light absorption. An apparatus prototype was developed using a commercial LED as photons source at the desired wavelength and a photo-detector with low noise, high sensitivity and visible blindness, opportunely fabricated using Silicon Carbide technology. A suitable electronic for handling the very low-level current of the detector has been designed and built to be robust, portable, low-power, low-cost and with a WiFi user interface. The ultraviolet spectroscopy apparatus application to which this work is aimed, is the low-level concentration measurement of SO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> in volcanic environment, while it can be easily adapted to other molecules detection and higher concentration level. While in previous Authors’ work the system feasibility has been explored using laboratory instrumentation, in this work the focus is to design a system that can be used in real harsh volcanic environment, where system lightweight, endurance and chemical strength against aggressive compounds are paramount. Resolution of approximately 1 ppm, compactness, robustness and insensitivity to humidity and temperature variations are required for this kind of environment. The performed laboratory tests and calibration for SO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> monitoring, are reported and discussed. The system shows good sensitivity as high as 8 pA/ppm, a resolution < 1 ppm for SO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> detection and low cross-sensitivity to main components usually present in volcanic gases.

Modeling Classroom Occupancy Using Data of WiFi Infrastructure in a University Campus

Universities worldwide are experiencing a surge in enrollments, therefore campus estate managers are seeking continuous data on attendance patterns to optimize the usage of classroom space. As a result, there is an increasing trend to measure classrooms attendance by employing various sensing technologies, among which pervasive WiFi infrastructure is seen as a low cost method. In a dense campus environment, the number of connected WiFi users does not well estimate room occupancy since connection counts are polluted by adjoining rooms, outdoor walkways, and network load balancing. In this paper, we develop machine learning based models to infer classroom occupancy from WiFi sensing infrastructure. Our contributions are three-fold: (1) We analyze metadata from a dense and dynamic wireless network comprising of thousands of access points (APs) to draw insights into coverage of APs, behavior of WiFi connected users, and challenges of estimating room occupancy; (2) We propose a method to automatically map APs to classrooms using unsupervised clustering algorithms; and (3) We model classroom occupancy using a combination of classification and regression methods of varying algorithms. We achieve 84.6% accuracy in mapping APs to classrooms while the accuracy of our estimation for room occupancy is comparable to beam counter sensors with a symmetric Mean Absolute Percentage Error (sMAPE) of 13.10%.

Spatial-Reuse-Based Efficient Coexistence for Cellular and WiFi Systems in the Unlicensed Band

With the increasing data traffic in the fifth-generation (5G) communication system, the 5G new radio extended to unlicensed bands (5G NR-U) has become a promising approach to relieve the heavy pressure on the cellular system. To achieve the efficient coexistence with the WiFi system and improve the efficiency of temporal, spectral and spatial resource utilization, we first divide the transmission space into two subspaces by leveraging spatial reuse, where the data transmitted by cellular user equipments (UEs) falls into one subspace and the data transmitted by Internet of Things (IoT) devices coexisting with WiFi users through power control is in the other subspace. Then, the coexistence among cellular UEs, IoT devices, and WiFi users is formulated as an optimization model with the aim of maximizing the cellular system throughput via the joint power and subchannel allocation under the interference constraint. Although the resulting optimization problem is a mixed-integer nonlinear programmming, we decompose it into two subproblems and develop an alternating iterative approach to effectively solve them. Also, the closed-form allocations of the power and subchannels are obtained. Simulation results confirm that the proposed scheme can improve the cellular system performance and guarantee the coexistence in the unlicensed band.

A Tutorial on Trusted and Untrusted Non-3GPP Accesses in 5G Systems—First Steps Toward a Unified Communications Infrastructure

Fifth-generation (5G) systems are designed to enable convergent access-agnostic service availability. This means that 5G services will be available over 5G New Radio air interface and also through other non-Third Generation Partnership Project (3GPP) access networks, e.g., IEEE 802.11 (Wi-Fi). 3GPP has recently published the Release 16 that includes trusted non-3GPP access network concept and wireless wireline convergence. The main goal of this tutorial is to present an overview of access to 5G core via non-3GPP access networks specified by 3GPP until Release 16 (i.e., untrusted, trusted, and wireline access). The tutorial describes aspects of the convergence of a 5G system and these non-3GPP access networks, such as the authentication and authorization procedures and the data session establishment from the point of view of protocol stack and exchanged messages between the network functions. In order to illustrate several concepts and part of 3GPP specification, we present a basic but fully operational implementation of untrusted non-3GPP access using WLAN. We perform experiments that demonstrate how a Wi-Fi user is authorized in a 5G core and establishes user plane connectivity to a data network. Moreover, we evaluate the performance of this access in terms of time consumed, number of messages, and protocol overhead to established data sessions.

Optimizing intra-facility crowding in Wi-Fi environments using continuous-time Markov chains

Various measures have been devised to reduce crowdedness and alleviate the transmission of COVID-19. In this study, we propose a method for reducing intra-facility crowdedness based on the usage of Wi-Fi networks. We analyze Wi-Fi logs generated continually in vast quantities in the ever-expanding wireless network environment to calculate the transition probabilities between the nodes and the mean stay time at each node. Subsequently, we model this data as a continuous-time Markov chain to determine the variance of the stationary distribution, which is used as a metric of intra-facility crowdedness. Therefore, we solved the optimization problem by using stay rate as a parameter and developed a numerical solution to minimize the intra-facility crowdedness. The optimization results demonstrate that the intra-facility crowding is reduced by approximately 30%. This solution can practically reduce intra-facility crowdedness as it adjusts people’s stay times without making any changes to their movements. We categorized Wi-Fi users into a set of classes using the k-means method and documented the behavioral characteristics of each class to help implement class-specific measures to reduce intra-facility crowdedness, thus enabling facility managers to implement effective countermeasures against crowdedness based on the circumstances. We present a detailed description of our computing environment and workflow used for the basic analysis of vast quantities of Wi-Fi logs. We believe this research will be useful for analysts and facility operators because we have used general-purpose data for analysis.