Wi-Fi Transmission Research Articles

Passive Localization of Standard WiFi Devices

Ubiquitous wireless indoor localization can be achieved by leveraging the widespread deployment of WiFi systems. Most existing WiFi-based localization solutions are based on received signal strength (RSS) fingerprinting, which requires a database of the RSS values in the application environment to be built and maintained. The latest 802.11ac WiFi standard offers channels with wide bandwidths, which enables accurate timing-based positioning. This paper presents a passive localization system in which multiple sniffers monitor the WiFi traffic and locate the standard WiFi transmitters based on the time-of-arrival measurements. Multiple implementation issues are addressed, including sniffer clock synchronization and hardware delay calibration. The proposed system is evaluated experimentally using a prototype developed by us. It is shown that the positioning accuracy is significantly improved over existing systems.

WiFi Electromagnetic Field Modelling for Indoor Localization

Abstract The aim of this paper is to develop simplified model for WiFi electromagnetic field propagation. The model can be used in preliminary estimation of WiFi transmitter localization for the purpose of WiFi-based indoor localization. It can be particularly useful when designing structural networks.We have developed a simplified linear model of WiFi electromagnetic field modelling and compared it with the most commonly used, more sophisticated models and with measurement results which were carried out in the laboratory. As demonstrated by the results of measurements conducted using various hardware, the accuracy of this simplified model introduced is similar to the commonly used models, but the number of parameters is lower. Therefore, our model easier to implement in real life conditions. The model presented in this paper enables WiFi electromagnetic field modelling when the exact values of propagation parameters and transmitter characteristics is unknown. This is usually the case at the early stage of structural network design,when exact parameters of building construction materials are not known. As the model is very simple, it does not require much effort to deploy, while its accuracy is sufficient for preliminary WiFi transmitter localization. Simplified models of WiFi electromagnetic field propagation are known, but no comparative research combined with measurements has been done in this field. This paper provides a comparison of different electromagnetic field models which can be applied to WiFi electromagnetic field propagation together with measurement results.

Network Sensor for Brain Wave with Automated Robot Assistance

Human thoughts consists of of a massive variety of interconnected neurons. The examples of collaboration among those neurons are spoken to as issues and enthusiastic states. As indicated through way of the human contemplations, this example will change which thusly produce particular electric powered waves. A muscle compression will likewise create a one in every of a kind electrical sign. a variety of these electric powered waves will be detected by way of the cerebrum wave sensor and it'll change over the records into parcels and transmit thru Bluetooth medium.Level analyzer unit (LAU) gets the thoughts wave crude records and it's going to listen and device the signal using MATLAB level that's seemed in data getting ready unit. At that factor the manage directions may be transmitted to the robotic it truly is the assistive robotic. With this whole framework, we are able to drift a robotic as consistent with the imparting instructions to the robot and it very well can be have become by means of squint problems and it has an inclination to be grew to become by flicker muscle constriction. Electroencephalography (EEG) is the estimation of electrical motion inside the residing mind. in this assignment we applied a brainwave sensor to dissect the EEG alerts . This plan speak about making geared up and recording the crude EEG signal from the thoughts Wave sensor within the MATLAB situation and through WIFI transmission control recommendations can be exceeded to the robotic section. thoughts wave sensors are not utilized in clinical use, however are applied inside the thoughts Brain Control Interface (BCI). The BCI is a prompt correspondence pathway among the cerebrum and an outside framework to offer direct correspondence and control between the human personality and substantial gadgets through disentangling various instances of cerebrum movement into guidelines step by step . This endeavor works of art fuses of a Processor utilizing cerebrum wave sensor and arranged unit block prominence unit as device parts and a fruitful musings signal system utilizing Matlab organize. directly, the proprietor wants to test whether the automated move or never again. on the off hazard that he's a now not strolling, by then the automated will obviously start. Be that as it can, at the off risk that he's ordinary mode, by then the vehicle will run and there's no notice. while the vehicle got gleaming request it will prevent at any rate the spot. what's more, if the owner wants to move the car he has a need to come ordinary mode. this can keep a key good ways from the improvement sooner or later of up close and personal. The present day system isn't having any faraway control leisure activity. depend upon others to work and No muscle withdrawal identifying and the proposed structure is having the mind wave examination for the sign which can be taken from the human cerebrum as appeared in the rectangular chart, is having controlling of the mechanical utilizing Human thoughts, Self

Robot Assisted Brain Wave Sensor Network in Smart Home Environment For Elderly Persons

Human thoughts consists of of a massive variety of interconnected neurons. The examples of collaboration among those neurons are spoken to as issues and enthusiastic states. As indicated through way of the human contemplations, this example will change which thusly produce particular electric powered waves. A muscle compression will likewise create a one in every of a kind electrical sign. a variety of these electric powered waves will be detected by way of the cerebrum wave sensor and it'll change over the records into parcels and transmit thru Bluetooth medium.Level analyzer unit (LAU) gets the thoughts wave crude records and it's going to listen and device the signal using MATLAB level that's seemed in data getting ready unit. At that factor the manage directions may be transmitted to the robotic it truly is the assistive robotic. With this whole framework, we are able to drift a robotic as consistent with the imparting instructions to the robot and it very well can be have become by means of squint problems and it has an inclination to be grew to become by flicker muscle constriction. Electroencephalography (EEG) is the estimation of electrical motion inside the residing mind. in this assignment we applied a brainwave sensor to dissect the EEG alerts . This plan speak about making geared up and recording the crude EEG signal from the thoughts Wave sensor within the MATLAB situation and through WIFI transmission control recommendations can be exceeded to the robotic section. thoughts wave sensors are not utilized in clinical use, however are applied inside the thoughts Brain Control Interface (BCI). The BCI is a prompt correspondence pathway among the cerebrum and an outside framework to offer direct correspondence and control between the human personality and substantial gadgets through disentangling various instances of cerebrum movement into guidelines step by step . This endeavor works of art fuses of a Processor utilizing cerebrum wave sensor and arranged unit block prominence unit as device parts and a fruitful musings signal system utilizing Matlab organize. directly, the proprietor wants to test whether the automated move or never again. on the off hazard that he's a now not strolling, by then the automated will obviously start. Be that as it can, at the off risk that he's ordinary mode, by then the vehicle will run and there's no notice. while the vehicle got gleaming request it will prevent at any rate the spot. what's more, if the owner wants to move the car he has a need to come ordinary mode. this can keep a key good ways from the improvement sooner or later of up close and personal. The present day system isn't having any faraway control leisure activity. depend upon others to work and No muscle withdrawal identifying and the proposed structure is having the mind wave examination for the sign which can be taken from the human cerebrum as appeared in the rectangular chart, is having controlling of the mechanical utilizing Human thoughts, Self controlled and working office for not to rely on others to work. This endeavor at Matlab, explains that tranquil speakme inside the sentiment of this stage is "discerning effort to express a word, portrayed through unpretentious advancements of inner talk organs without unquestionably voicing it." The way gets markers from the cerebrum to the muscle bunches while the client purposely vocalizes inside. The device later companions such banner with an out of entryways preparing framework. Like talk affirmation structures, it allows the customer to make solicitations to such gadgets, however without reporting anything.

FreeTrack: Device-Free Human Tracking With Deep Neural Networks and Particle Filtering

Human tracking is of key importance to a variety of applications. Different from the previous approaches requiring the targets to carry electronic devices, this paper proposes a device-free tracking method based on WiFi channel state information (CSI) through deep neural networks (DNN) and particle filtering (PF). In the area covered with WiFi, human movements may cause observable variations of WiFi signals. By analyzing the CSI fingerprint patterns and modeling the dependency between CSI fingerprints and locations through DNN, the proposed method is able to localize the targets according to the measured CSI fingerprints through DNN regression. Localization with DNN is accurate for static targets, yet unable to form reasonable trajectories of moving targets. This paper proposes to apply PF on DNN localization results and form the walking trajectories of the targets. To avoid the trajectories to cross obstacles, map matching is integrated to constrain the unreasonable transfer of particles, which further improves the precision of trajectories. To combat with environmental variants, fine tuning on DNN is proposed to enhance the adaptivity of the method. Extensive evaluations in two representative scenarios with only one pair of WiFi transmitter and receiver achieve the high accuracy of around half a meter and precise trajectories as well as adaptation to environmental variants.

Indoor Localization System Using Wi-Fi Technology

Recently, indoor localization has witnessed an increase in interest, due to the potential wide range of using in different applications, such as Internet of Things (IoT). It is also providing a solution for the absence of Global Positioning System (GPS) signals inside buildings. Different techniques have been used for performing the indoor localization, such as sensors and wireless technologies. In this paper, an indoor localization and object tracking system is proposed based on WiFi transmission technique. It is done by distributing different WiFi sources around the building to read the data of the tracked objects. This is to measure the distance between the WiFi receiver and the object to allocate and track it efficiently. The test results show that the proposed system is working in an efficient way with low cost.

DeWOZ: Rethinking the Schmidl–Cox Algorithm for Detecting Wi-Fi Out of ZigBee Interference

This letter presents detect Wi-Fi signals out of ZigBee (DeWOZ), a clean-slate technique to discern Wi-Fi packets drowning in ZigBee interference. Unlike existing solutions that are restricted to the cases where Wi-Fi signal strength is much higher than ZigBee, Wi-Fi signals only interfere with ZigBee payload, or beforehand clear Wi-Fi transmissions are done to obtain transmitter-specific information, DeWOZ aims at achieving the detection of relatively weak Wi-Fi signal hidden in both ZigBee header and payload portions only based on a single corrupted signal. DeWOZ re-explores the Wi-Fi-oriented Schmidl-Cox algorithm for corrupted signal synchronization followed by two key operations, autocorrelation anomaly detection and adaptive discrete Fourier transform, to sniff Wi-Fi out of ZigBee header and payload, respectively. The feasibility of DeWOZ is validated via practical experiment.

Adverse Effects of Wi-Fi Radiation on Male Reproductive System: A Systematic Review.

Extensive use of Wi-Fi has contributed to radiofrequency electromagnetic radiation (RF-EMR) pollution in environment. Various studies have been conducted to evaluate the effect of RF-EMR emitted by Wi-Fi transmitter on male reproduction health. However, there are conflicting findings between studies. Thus, this review aims to elucidate the possible effects of 2.45 GHz Wi-Fi exposure on both animal and human male reproductive system. A computerized database search performed through MEDLINE via Ovid and PUBMED with the following set of keywords: 'Wi-Fi or WiFi or wireless fidelity or Wi-Fi router or WiFi router or electromagnetic or radiofrequency radiation' AND 'sperm or spermatozoa or spermatogenesis or semen or seminal plasma or testes or testis or testosterone or male reproduction' had returned 526 articles. Only 17 studies conformed to pre-set inclusion criterion. Additional records identified through Google Scholar and reviewed article further revealed six eligible articles. A total of 23 articles were used for data extraction, including 15 studies on rats, three studies on mice, and five studies on human health. Sperm count, motility and DNA integrity were the most affected parameters when exposed to RF-EMR emitted by Wi-Fi transmitter. Unfortunately, sperm viability and morphology were inconclusive. Structural and/or physiological analyses of the testes showed degenerative changes, reduced testosterone level, increased apoptotic cells, and DNA damage. These effects were mainly due to the elevation of testicular temperature and oxidative stress activity. In conclusion, exposure towards 2.45 GHz RF-EMR emitted by Wi-Fi transmitter is hazardous on the male reproductive system.

A Device Monitoring System Based on ARM Upper Computer and WIFI Transmission

With the widespread application of WIFI networks and embedded system technology, the device monitoring system based on Embedded System and wireless network came into being. In this paper, we introduce a device monitoring system based on ARM upper computer and WIFI transmission, and we tested this system on workshop equipment. The hardware adopts ARM Cortex-A8 processor architecture of TI company as the main control chip, using IAC-335X-Kit development board for system design, external USB camera module and WIFI wireless module for video capture and data transmission. The software is based on embedded Linux as the platform. The system will collect production data accurately and objectively, and the statistical analysis. At the same time, the system uses QT to develop the upper computer software GUI interface. Compared with the traditional system based on the wired network, our design is more convenient and flexible, which reduces the implementation restriction and maintenance cost of traditional network cabling.

Enhancing the Coexistence of LTE and Wi-Fi in Unlicensed Spectrum Through Convolutional Neural Networks

Over the last years, the ever-growing wireless traffic has pushed the mobile community to investigate solutions that can assist in more efficient management of the wireless spectrum. Towards this direction, the long-term evolution (LIE) operation in the unlicensed spectrum has been proposed. Targeting a global solution that respects the regional requirements, 3GPP announced the standard of LIE licensed assisted access (LAA). However, LIE LAA may result in unfair coexistence with Wi-Fi, especially when Wi-Fi does not use frame aggregation. Targeting a technique that enables fair channel access, the mLTE-U scheme has been proposed. According to mLTE-U, LTE uses a variable transmission opportunity, followed by a variable muting period that can be exploited by other networks to transmit. For the selection of the appropriate mLTE-U configuration, information about the dynamically changing wireless environment is required. To this end, this paper proposes a convolutional neural network (CNN) that is trained to perform identification of LIE and Wi-Fi transmissions. In addition, it can identify the hidden terminal effect caused by multiple LTE transmissions, multiple Wi-Fi transmissions, or concurrent LIE and Wi-Fi transmissions. The designed CNN has been trained and validated using commercial off-the-shelf LIE and Wi-Fi hardware equipment and for two wireless signal representations, namely, in-phase and quadrature samples and frequency domain representation through fast Fourier transform. The classification accuracy of the two resulting CNNs is tested for different signal to noise ratio values. The experimentation results show that the data representation affects the accuracy of CNN. The obtained information from CNN can be exploited by the mLTE-U scheme in order to provide fair coexistence between the two wireless technologies.

Rectifier Using UWB Microstrip Antenna as Electromagnetic Energy Harvester for GSM, CCTV and Wi-Fi Transmitter

Rectifier Using UWB Microstrip Antenna as Electromagnetic Energy Harvester for GSM, CCTV and Wi-Fi Transmitter

Imaging With WiFi

A new method of creating microwave imagery by capturing the signals emitted by a small set of wireless WiFi transmitters is presented. The imaging technique leverages the fact that the signals emitted by separate WiFi transmitters are sufficiently statistically independent to create a radiation pattern that is spatially incoherent, enabling the use of spatial frequency sampling using a small set of receiving antennas in a sparse array. In contrast to traditional microwave imaging, this method requires no mechanical or electrical beam scanning and no coordination between transmitters and receivers. Furthermore, the WiFi imaging system requires far less receiver gain than passive microwave imagers and significantly less bandwidth. We experimentally demonstrate the 2-D image reconstruction of reflecting metal spheres and an X-shaped reflecting target using three transmitters emitting independent 16-level quadrature amplitude modulated signals at 5.5 GHz matching commercial WiFi protocols 802.11n/ac.

Проектирование цифрового вольтметра с Wi-Fi-передатчиком

Проектирование цифрового вольтметра с Wi-Fi-передатчиком

Impact of LTE’s Periodic Interference on Heterogeneous Wi-Fi Transmissions

The problem of Wi-Fi and LTE coexistence has been significantly debated in the last years, with the emergence of LTE extensions enabling the utilization of unlicensed spectrum for carrier aggregation. Rather than focusing on the problem of resource sharing between the two technologies, in this paper, we study the effects of LTE's structured transmissions on the Wi-Fi random access protocol. We show how the scheduling of periodic LTE transmissions modifies the behavior of 802.11's distributed coordination function (DCF), leading to a degradation of Wi-Fi performance, both in terms of channel utilization efficiency and in terms of channel access fairness. We also discuss the applicability and limitations of a persistent DCF model in analyzing Wi-Fi performance under periodic LTE interference.

A cm-Scale 2.4-GHz Wireless Energy Harvester With NanoWatt Boost Converter and Antenna-Rectifier Resonance for WiFi Powering of Sensor Nodes

The widespread use of WiFi in the 2.4-GHz ISM band creates the potential for RF powering using WiFi radios. This paper presents the design of a cm-scale RF-energy harvester including antenna, rectifier, and dc–dc boost converter for RF powering in the 2.4-GHz ISM band. The rectifier and boost converter are designed while considering cold-start operation and nanowatt-scale available power from the rectifier for RF incident power $\times $ and ~2 $\times $ improvement in range compared to prior art. Measurements using a commercial WiFi TX demonstrate the ranges of up to 1.25 m for 14-dBm output power with 1.3% TX duty-cycling in WiFi access-point mode, demonstrating the feasibility of powering sensors from RF power beacons in the 2.4-GHz ISM band as well as from background WiFi transmissions.

Dense Deployment of BLE-Based Body Area Networks: A Coexistence Study

The issues of cross-technology interference and coexistence in the unlicensed 2.4-GHz spectrum band among various technologies including WiFi, ZigBee, and classic Bluetooth have been studied extensively. However, it remains relatively understudied for Bluetooth low energy (BLE), especially in densely deployed scenarios. In this paper, we develop a testbed to conduct our experimental studies, focusing on BLE and its coexistence capabilities when being deployed in a dense environment, under possible interference from WiFi and ZigBee/IEEE 802.15.4. One scenario of interest is a network of several co-located BLE-based BANs, each of which is designed in a star topology with one gateway and multiple BLE sensor nodes. The second scenario represents a highly heterogeneous network where each BAN now carries both BLE and ZigBee sensors, while being exposed to interference from external WiFi transmission. Experiments are carried out on our testbed, which are built based on low-cost, light-weight off-the-shelf components and state-of-the-art BAN protocols. Our results show that the performance of BLE is relatively robust to interference from other BLE transmissions as well as those from nearby ZigBee and WiFi devices. In addition, the deployment of the testbed on human bodies results in no performance degradation for the network.

On development of security monitoring system via wireless sensing network

Visual signal detection and data transmitting are key issues in the fields of security monitoring. In this work, aiming at recognizing the object in real time, cameras are employed for image detection. Based on WiFi transmission principle, the communication path of data is therefore built up. Visual signals are delivered to the host computer and processed automatically. In order to facilitate the processing, analysis for identifying the surveillance from current collection are carried out, considering the properties of targets and bounding boxes. Specifically, to improve the working performance, detection model is developed by revising the state-of-the-art algorithm SSD (Single Shot Detector). Experimental resulting representation satisfies the detection accuracy in a quantitative form. In addition, the deploying configuration of the system is illustrated, allowing a straightforward construction of the security monitoring system.

Use of a low-cost telecytopathology method for remote assessment of thyroid FNAs.

Rapid on-site evaluation is a great tool for optimizing the adequacy and quality of cytologic samples. The objective of the current study was to analyze a low-cost telecytopathology method for the remote assessment of thyroid fine-needle aspiration biopsies (FNABs), with comparison of the primarily rendered adequacy and diagnosis with the final conventional analysis. Material collected from thyroid FNABs was immediately smeared onto glass slides and stained with Diff-Quik. A conventional microscope attached to a smart device was operated on-site by either a medical student or a pathology resident for Wi-Fi transmission of the images by Skype. The cytopathologist would remotely guide the screening of the slides, zooming in and out of areas of interest. Remote assessment included an analysis of material adequacy and a preliminary diagnosis. The quality of the transmission and the number of slides also were recorded. After a washout period of 3 weeks, final diagnosis and adequacy were assigned by conventional microscopy. The final agreement rate for adequacy between remote and conventional analysis was 90.5%. For diagnosis, the final agreement rate was 83.3%. The diagnosis agreement rate varied, depending on the quality of transmission: there was 88% agreement when the quality was excellent, 77.8% agreement when it was good, and 62.5% agreement when it was poor. Low-cost telecytopathology is an efficient method for the remote assessment of thyroid FNAB adequacy and diagnosis. The wide use of such technology in low-resource or remote centers may have a positive impact on the number of adequate or satisfactory samples, optimizing the management of patients who have thyroid nodules.

Uplink NOMA Scheme for Wi-Fi Applications

Non-Orthogonal Multiple Access (NOMA) with Successive Interference Cancellation (SIC) is one of the promising techniques proposed for 5G systems. It allows multiple users with different channel coefficients to share the same (time/frequency) resources by allocating several levels of (power/code) to them. In this article, a design of a cooperative scheme for the uplink NOMA Wi-Fi transmission (according to IEEE 802.11 standards) is investigated. Various channel models are exploited to examine the system throughput. Convolutional coding in conformance to IEEE 802.11a/g is applied to evaluate the system performance. The simulation results have been addressed to give a clear picture of the performance of the investigated system.

Foliage motion under wind, from leaf flutter to branch buffeting.

The wind-induced motion of the foliage in a tree is an important phenomenon both for biological issues (photosynthesis, pathogens development or herbivory) and for more subtle effects such as on wi-fi transmission or animal communication. Such foliage motion results from a combination of the motion of the branches that support the leaves, and of the motion of the leaves relative to the branches. Individual leaf dynamics relative to the branch, and branch dynamics have usually been studied separately. Here, in an experimental study on a whole tree in a large-scale wind tunnel, we present the first empirical evidence that foliage motion is actually dominated by individual leaf flutter at low wind velocities, and by branch turbulence buffeting responses at higher velocities. The transition between the two regimes is related to a weak dependence of leaf flutter on wind velocity, while branch turbulent buffeting is strongly dependent on it. Quantitative comparisons with existing engineering-based models of leaf and branch motion confirm the prevalence of these two mechanisms. Simultaneous measurements of the wind-induced drag on the tree and of the light interception by the foliage show the role of an additional mechanism, reconfiguration, whereby leaves bend and overlap, limiting individual leaf flutter. We then discuss the consequences of these findings on the role of wind-mediated phenomena.