Wi-Fi System Research Articles

Pattern Reconfigurable Antenna for VANET, Wi-Fi, and WiMAX Wireless Communication Systems

This work presents the design and analysis of a beam switching antenna for VANET, Wi-Fi, and WiMAX wireless communication systems. The proposed reconfigurable antenna is powered by a coaxial cable and consists of a circular patch, six fish-shaped radiating elements, and a circular planar ground. The antenna was constructed on a Rogers RT5880 substrate. Its dimensions are as follows: 0.81λ0 × 0.81λ0 × 0.03λ0. It performs six reconfigurable operating states, at the same frequency, by controlling the activation and deactivation of six PIN diodes to change the beam’s direction. A theoretical equivalent circuit model of the antenna is extracted. A progressive analysis of improving the antenna characteristic performances is provided. The bandwidth of the proposed antenna is 9.07% (measured), 9.62% (simulated), and 9.31% (theoretical). The designed antenna has a maximum gain of 9.57 dB for all pattern states and a superior efficiency ratio from 85% to 95% over the operating range (5.54 GHz–6.10 GHz). The proposed reconfigurable antenna is fabricated. Measured, simulated, and theoretical results are given and show good agreement, including reflection coefficient (S11) and radiation patterns.

Analysis of international traveler mobility patterns in Tokyo to identify geographic foci of dengue fever risk

Travelers play a role in triggering epidemics of imported dengue fever because they can carry the virus to other countries during the incubation period. If a traveler carrying dengue virus visits open green space and is bitten by mosquitoes, a local outbreak can ensue. In the present study, we aimed to understand the movement patterns of international travelers in Tokyo using mobile phone data, with the goal of identifying geographical foci of dengue transmission. We analyzed datasets based on mobile phone access to WiFi systems and measured the spatial distribution of international visitors in Tokyo on two specific dates (one weekday in July 2017 and another weekday in August 2017). Mobile phone users were classified by nationality into three groups according to risk of dengue transmission. Sixteen national parks were selected based on their involvement in a 2014 dengue outbreak and abundance of Aedes mosquitoes. We found that not all national parks were visited by international travelers and that visits to cemeteries were very infrequent. We also found that travelers from countries with high dengue prevalence were less likely to visit national parks compared with travelers from dengue-free countries. Travelers from countries with sporadic dengue cases and countries with regional transmission tended to visit common destinations. By contrast, the travel footprints of visitors from countries with continuous dengue transmission were focused on non-green spaces. Entomological surveillance in Tokyo has been restricted to national parks since the 2014 dengue outbreak. However, our results indicate that areas subject to surveillance should include both public and private green spaces near tourist sites.

Forecasting Crowd Counts With Wi-Fi Systems: Univariate, Non-Seasonal Models

Recently, event organizers and researchers have advocated the development of novel technologies supporting crowd control, notably for public events. This paper presents a crowd monitoring system based on probe requests (PRs), which are Wi-Fi packets smartphones send periodically. By estimating the global rate at which nearby smartphones send PRs, Wi-Fi sensors can estimate crowd counts. The core contribution of this paper is a computationally tractable method that forecasts crowd counts up to thirty minutes in the future, with forecasts becoming available as soon as two hours of data are available. The forecasting method relies on autoregressive integrated moving average (ARIMA) models. Contributions also include two methods that compute prediction intervals associated with the forecasts, one of which is based upon generalized autoregressive conditional heteroskedasticity (GARCH) models. Recent real-world data from Winter Wonders 2018/2019 (an event that took place in Brussels, Belgium) notably demonstrate that the proposed forecasting method outperforms its immediate variations as well as baseline models (i.e., random walk models).

WI-FI Access Point (WAP) OPTIMAL Placement in an Indoor Location

Abstract: The popularity of location based applications is undiminished today. They require accurate location information which is a challenging issue in indoor environments. Wireless technologies can help derive indoor positioning data. Especially, the WiFi technology is a promising candidate due to the existing and almost ubiquitous Wi-Fi infrastructure. The already deployed WiFi devices can also serve as reference points for localization eliminating the cost of setting up a dedicated system. However, the primary purpose of these Wi-Fi systems is data communication and not providing location services. This accuracy can be increased by carefully placing the Wi-Fi access points to cover the given territory properly. This method is based on simulated annealing which finds the optimal number and placement of Wi-Fi access points with regard to indoor positioning and investigate its performance in a real environment scenario via simulations. Keywords: Wi-fi access point (WAP), simulated annealing, router, wireless, placement, locationing.

Bringing Time-Sensitive Networking to Wireless Professional Private Networks

Private professional environments such as manufacturing industry, warehouses, hospitals, airports, among others, increasingly rely on end-to-end connected solutions to support and to improve their daily operational performance. This comes with a demand for real-time and deterministic communication, without evading the flexibility offered by wireless communication. Currently, wireless networks are lacking time-sensitive networking (TSN) features, making them only suitable for non-time-critical communication. To support end-to-end wireless-wired deterministic communication in these private professional environments, it is necessary to introduce TSN features to the wireless network segments. In this paper, we list a number of considerations that have to be addressed before such communication may become a reality, including accurate time synchronization and fine-grained scheduling. Based on these considerations, we present a proof-of-concept realization of a TSN-capable Wi-Fi system, which enables end-to-end wireless-wired deterministic communication.

Tri-Band, Stable and Compact Patch Frequency Selective Surface Optimized via Hybrid Bioinspired Computing for Applications at 2.4, 3.5 and 5.8 GHz

This work addresses the synthesis of a multi-band frequency selective surface (FSS) through bioinspired computing and a general regression neural network (GRNN). This hybrid computational method, which utilizes the multi-objective cuckoo search algorithm combined to a GRNN, determine the best physical dimensions of the FSS in order to achieve a multi-band filtering at the 2.4, 3.5 and 5.8 GHz spectrums. Therefore, the results are to be applied to aid the propagation of Wi-Fi, WLAN, WiMAX and future sub-6 GHz 5G systems. The resonant frequencies were measured and a -10 dB cutoff value has been considered for the transmission coefficient. The triple rectangular loop conductor geometry of the device is printed upon a glass epoxy (FR-4) substrate. Measurements were made for different wave incidence angles, from 0° up to 45°, to demonstrate how signal incidence would affect the device’s functioning. The agreement between simulated and measured data display satisfactory results.

An Enhanced Approach to Imaging the Indoor Environment Using WiFi RSSI Measurements

Indoor device-free localization (DFL) using radio frequency (RF) signals has many important applications including navigation, security and inventory control. One of the most common approaches to indoor DFL is Radio Tomographic Imaging (RTI) which is based on line-of-sight (LOS) signal models and often utilizes WiFi signals. In this work, we propose a new extended Rytov phaseless imaging (xRPI) technique for indoor imaging that can image the shape and refractive index of objects in the indoor environment using WiFi RSSI measurements. Estimation of refractive index can be used to distinguish different object types within the environment. In addition, methods to reduce the number of RSSI measurements required for indoor imaging are also developed and these use a strong spatial sparsity constraint which directly arises from imaging change in the environment. Theoretical developments that support these contributions include increasing the validity range of the Rytov approximation by using a high frequency approximation to the total field, incorporating temporal background subtraction, incorporating electric field sensing using directional antennas, and utilization of Fresnel zones. Experimental demonstration of the performance of the proposed method is provided using a 20 node WiFi system. The results show that xRPI provides considerable improvement over RTI in accurately imaging shapes of different objects in an indoor environment. It also provides an estimate of the refractive index which is not possible with RTI or other Wi-Fi based indoor imaging techniques.

Adaption Of Construction Management Modelling System Through The Use Of Internet Of Things (IoT)

This paper aims to adapt, implement, and practice the physical use of IoT in the construction management industry as a configuration protocol. The authors describe the general outlines of this field capability as a framework, and they foresaw the opportunities of developing a dominant steam line approach to be incorporated in the construction management side. The challenge is to bond the BMS, SCADA, IoT, smart data “Tags”, green building concepts, smart surveillance, self-moving transportation, and mobile technology in one practical, innovative configuration model. The authors, however, called it “Construction management modelling system” (CMMS). The gap point in this paper is the harnessing of Data Tagging systems along with a smart mobile system via radio frequency and Wi-Fi communication system. The significant effort here is to establish optimum modelling of the IoT system to roll out a product containing all the solutions for the existing and expected obstacles in the construction sites for the different types of projects. The literature review, proposed configuration system, affiliate works, benefits, conclusions, and recommendations have been furnished.

Deep-Learning-Based Wi-Fi Indoor Positioning System Using Continuous CSI of Trajectories.

In a Wi-Fi indoor positioning system (IPS), the performance of the IPS depends on the channel state information (CSI), which is often limited due to the multipath fading effect, especially in indoor environments involving multiple non-line-of-sight propagation paths. In this paper, we propose a novel IPS utilizing trajectory CSI observed from predetermined trajectories instead of the CSI collected at each stationary location; thus, the proposed method enables all the CSI along each route to be continuously encountered in the observation. Further, by using a generative adversarial network (GAN), which helps enlarge the training dataset, the cost of trajectory CSI collection can be significantly reduced. To fully exploit the trajectory CSI’s spatial and temporal information, the proposed IPS employs a deep learning network of a one-dimensional convolutional neural network–long short-term memory (1DCNN-LSTM). The proposed IPS was hardware-implemented, where digital signal processors and a universal software radio peripheral were used as a modem and radio frequency transceiver, respectively, for both access point and mobile device of Wi-Fi. We verified that the proposed IPS based on the trajectory CSI far outperforms the state-of-the-art IPS based on the CSI collected from stationary locations through extensive experimental tests and computer simulations.

Array Design of 300 GHz Dual-Band Microstrip Antenna Based on Dual-Surfaced Multiple Split-Ring Resonators.

To meet the increasing need of high-data-rate and broadband wireless communication systems, the devices and its circuits R&D under Millimeter, Sub-Millimeter, or even Terahertz (THz) frequency bands are attracting more and more attention from not only academic, but also industrial areas. Most of the former research on the THz waveband (0.1–10 THz) antenna design is mainly focused on realizing high directional gain, such as horn antennas, even though the coverage area is very limited when comparing with the current Wi-Fi system. One solution for the horizontally omnidirectional communication antenna is using the structure of multiple split-ring resonators (MSRRs). Aiming at this point, a novel 300 GHz microstrip antenna array based on the dual-surfaced multiple split-ring resonators (DSMSRRs) is proposed in this paper. By employing the two parallel microstrip transmission lines, different MSRRs are fed and connected on two surfaces of the PCB with a centrally symmetric way about them. The feeding port of the whole antenna is in between the centers of the two microstrip lines. Thus, this kind of structure is a so-called DSMSRR. Based on the different size of the MSRRs, different or multiple working wavebands can be achieved on the whole antenna. Firstly, in this paper, the quasi-static model is used to analyze the factors affecting the resonance frequency of MSRRs. Simulation and measured results demonstrate that the resonant frequency of the proposed array antenna is 300 GHz, which meets the design requirements of the expected frequency point and exhibits good radiation characteristics. Then, a dual-band antenna is designed on the above methods, and it is proved by simulation that the working frequency bands of the proposed dual-band antenna with reflection coefficient below −10 dB are 274.1–295.6 GHz and 306.3–313.4 GHz.

Reliable Wi-Fi Indoor Localization in Case of AP Loss by Using Integrated Model Based on Signal Anomaly Detector and Signal Distance Corrector

When developing a Wi-Fi indoor positioning system in a real-world environment, the problems we have to face are that some access points’ signal strength fluctuates extensively or even loses contact due to the cybersecurity threats, leading to the fact that the indoor location system cannot get reliable application in a real-world environment. To solve this problem, we propose a new integrated model based on signal anomaly detector and signal distance corrector to provide reliable position estimation when the access points’ signal is lost under cybersecurity threats. The signal anomaly detector improves recognition capability of the uncertain signal and noise, while the signal distance corrector improves the robustness and fault tolerance of the highly variable Wi-Fi signals. To fully reflect the performance of the proposed method, experiments have been carried out in the real environment of indoor parking lots. The results show that the proposed integrated model successfully provides reliable position estimation when the access points are lost under cybersecurity threats.

Unlocking the Beamforming Potential of LoRa for Long-range Multi-target Respiration Sensing

Despite extensive research effort in contact-free sensing using RF signals in the last few years, there still exist significant barriers preventing their wide adoptions. One key issue is the inability to sense multiple targets due to the intrinsic nature of relying on reflection signals for sensing: the reflections from multiple targets get mixed at the receiver and it is extremely difficult to separate these signals to sense each individual. This problem becomes even more severe in long-range LoRa sensing because the sensing range is much larger compared to WiFi and acoustic based sensing. In this work, we address the challenging multi-target sensing issue, moving LoRa sensing one big step towards practical adoption. The key idea is to effectively utilize multiple antennas at the LoRa gateway to enable spatial beamforming to support multi-target sensing. While traditional beamforming methods adopted in WiFi and Radar systems rely on accurate channel information or transmitter-receiver synchronization, these requirements can not be satisfied in LoRa systems: the transmitter and receiver are not synchronized and no channel state information can be obtained from the cheap LoRa nodes. Another interesting observation is that while beamforming helps to increase signal strength, the phase/amplitude information which is critical for sensing can get corrupted during the beamforming process, eventually compromising the sensing capability. In this paper, we propose novel signal processing methods to address the issues above to enable long-range multi-target reparation sensing with LoRa. Extensive experiments show that our system can monitor the respiration rates of five human targets simultaneously at an average accuracy of 98.1%.

Wi-Fi Daq System Helps Rotorcraft Testing

Testing rotorcraft, especially remote acoustic testing, presents several challenges

IOT Based Infant Healthcare Monitoring System

Newborn child needs appropriate consideration for great wellbeing and mental health. These days, families comprise of just guardians and kids. Managing infant youngsters is ambling for grandparents so the chances of giving extra thought and love are diminished. In a family, necessities to really focus on the child’s clinical issue are inevitable. To deal with such issues a system is proposed for the device health watch framework. This will assist a mother or a dad to screen the baby with different boundaries. The framework began getting more altered. These days numerous baby checking frameworks came into the market with different alternatives. This framework keeps newborn children to be in a protected condition by avoiding wet condition utilizing sensors and continue to check the vital health parameters.. IoT is helpful in this angle as it replaces the customary checking frameworks with a more proficient plan, by giving basic data in regards to the state of the patient. This framework utilizes the heartbeat sensor, Temperature sensor, wetness senor and conductivity sensor with Node MCU. The beat sensor is put on the finger and it estimates the pulse and afterward sends the heart rate to android versatile application by means of Bluetooth. A microcontroller is interfaced with the Wi-Fi system to make a straightforward TCP/IP correspondence. The parameters will be checked and downloaded very easily using the android application. The other advantage of the programmability is parents can be aware of their infant’s health status continuously.

Factors Associated With Key Outcomes in Diabetes Related Foot Disease: A Prospective Observational Study

Diabetic foot disease is a serious and common complication of diabetes mellitus. The aim of this study was to assess limb and patient factors associated with key clinical outcomes in diabetic patients with foot ulcers. This was a prospective observational study of diabetic patients with foot wounds admitted to a major tertiary teaching hospital in South Australia or seen at associated multidisciplinary foot clinics between February 2017 and December 2018. Patient demographic and clinical data were collected, including limb status severity assessed by the WIfI system and grip strength. Participants were followed up for 12 months. The primary outcomes were major amputation, death, amputation free survival, and completion of healing of the index wound within one year. A total of 153 participants were recruited and outcome data were obtained for 152. Forty-two participants underwent revascularisation during the research period. Eighteen participants (11.8%) suffered major amputation of the index limb and 16 (10.5%) died during follow up. Complete wound healing was achieved in 106 (70%) participants. There was a statistically significant association between WIfI stage and major amputation (subdistribution hazard ratio [SHR] 2.75), mortality (hazard ratio [HR] 2.60), amputation free survival (odds ratio [OR] 0.32), and wound healing (SHR 0.69). There was also a statistically significant association between time to healing and grip strength (SHR 0.50), and previous amputations (major or minor) (SHR 0.57). This prospective study supports the ability of the WIfI classification system to predict one year key clinical outcomes in a diabetic population with foot ulcers. It also demonstrated that grip strength may be a useful predictor of wound healing.

An Automatized Contextual Marketing System Based on a Wi-Fi Indoor Positioning System.

A complete contextual marketing platform including an indoor positioning system (IPS) for smartphones is proposed and evaluated to later be deployed in large infrastructures, such as malls. To this end, we design and implement a novel methodology based on location-as-a-service (LAAS), comprising all the required phases of IPS generation: mall digital map creation, the tools/procedures for offline calibration fingerprint acquisition, the location algorithm, the smartphone app acquiring the fingerprint data, and a validation procedure. To select an appropriate fingerprint location algorithm, a comparison among K-nearest neighbors (KNN), support vector machine (SVM), and Freeloc is accomplished by employing a set of different smartphones in two malls and assessing different occupancy levels. We demonstrate that our solution can be quickly deployed at shop level accuracy in any new location, resulting in a robust and scalable proposal.

FLAG: Flexible, Accurate, and Long-Time User Load Prediction in Large-Scale WiFi System Using Deep RNN

In this article, we propose <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">FLAG</i> for flexible, accurate, and long-time user load prediction in a large-scale WiFi system. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">FLAG</i> enables prediction customization in both time granularity and prediction length. Under an operating WiFi system with more than 7000 APs, a reference implementation of <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">FLAG</i> is developed, which consists of three major components. For <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">data acquisition</i> , we process 25 074 733 association records contributed by 55 809 users, to extract the ground truth of AP-level user load. For <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">feature extraction</i> , we perform a comprehensive data analytics to mine vital features to label each AP, which are extracted and classified into three categories, i.e., individual features, spatial features, and temporal features. For the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">model design</i> , we design a deep recurrent neural network (RNN) model, which contains two separate RNNs, i.e., the encoder RNN and decoder RNN. Particularly, the sequential feature vectors are injected into the encoder RNN to learn the “semantic” information, based on which the decoder RNN conducts sequential AP-level predictions. As the semantic vector is injected for each time step prediction, it can effectively reduce the accumulated prediction errors, which enable long period of time predictions. Real data set-based experiments corroborate the efficacy of <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">FLAG</i> .

Impact of People’s Movement on Wi-Fi Link Throughput in Indoor Propagation Environments: An Empirical Study

There has been tremendous growth in the deployment of Wi-Fi 802.11-based networks in recent years. Many researchers have been investigating the performance of the Wi-Fi 802.11-based networks by exploring factors such as signal interference, radio propagation environments, and wireless protocols. However, exploring the effect of people’s movement on the Wi-Fi link throughout the performance is still a potential area yet to be explored. This paper investigates the impact of people’s movement on Wi-Fi link throughput. This is achieved by setting up experimental scenarios by using a pair of wireless laptops to file share where there is human movement between the two nodes. Wi-Fi link throughput is measured in an obstructed office block, laboratory, library, and suburban residential home environments. The collected data from the experimental study show that the performance difference between fixed and random human movement had an overall average of 2.21 ± 0.07 Mbps. Empirical results show that the impact of people’s movement (fixed and random people movements) on Wi-Fi link throughput is insignificant. The findings reported in this paper provide some insights into the effect of human movement on Wi-Fi throughputs that can help network planners for the deployment of next generation Wi-Fi systems.

Sistema de classificação da Sociedade de Cirurgia Vascular Wound, Ischemia, Foot Infection (WIFI): caracterização das feridas

Objetivo: Identificar as características e gravidade das feridas em estudos com classificação do Sistema WIfI (Wound; Ischemia; foot Infection). Método: Trata-se de uma revisão integrativa de literatura, de caráter descritivo. Foram realizadas buscas nas bases de dados MEDLINE e Biblioteca Virtual da Saúde (BVS) sendo utilizados os descritores em inglês: “wound healing”, “amputation”, “diabetic foot” e “peripheral vascular disease”. Identificou-se 54 publicações, após análise e aplicação de critérios de inclusão e exclusão permaneceram 12 artigos. Resultados: Houve predominância de estudos com nível de evidência 2B conforme a Classificação de Oxford Centre for Evidence-Based Medicine. O perfil de pacientes predominou aqueles com doença arterial periférica submetidos à revascularização do membro. Foi encontradas perfil de feridas complexas, tamanho médio a extensas, com pouca possibilidade de cicatrização sem uma ação multiprofissional. Conclusão: A pesquisa evidenciou que as principais características sobre as feridas apresentadas em estudos com a utilização da classificação do Sistema WIfI (Wound; Ischemia; foot Infection), foram feridas com exposição óssea e feridas extensas. Assim, é primordial que os profissionais de enfermagem como integrantes da equipe multiprofissional conheçam a classificação WIfI, assim poderá identificar e encaminhar um paciente com isquemia para revascularização mais precocemente.

Coexistence algorithms for LTE and WiFi networks in unlicensed spectrum: performance optimization and comparison

Facing the challenges brought by the surge in the demand for mobile data traffic, many coexistence algorithms for long-term evolution (LTE) and WiFi networks in the unlicensed spectrum have been developed recently. In this article, we investigate, optimize, and compare several solutions to operate LTE in the unlicensed band, which include duty-cycle muting (DCM) mechanism, listen-before-talk (LBT) mechanism, and LTE and WLAN aggregation (LWA) algorithm. We first overview the architecture, working mechanism, coexistence problem with WiFi network, and overall cost of the three different coexistence mechanisms. Their advantages and disadvantages are also compared and analyzed in detail. Then, to maximize the spectrum efficiency of unlicensed band, we optimize the corresponding adjustable variables in the three algorithms. Furthermore, numerical simulations are conducted to compare the performances of DCM, LBT, and LWA explicitly. The results show that DCM can achieve the highest throughput for the LTE network while LBT and LWA have less impact on the WiFi system.