Wi-Fi Standards Research Articles

PCA-Based inversion of WiFi signal for robust device-free indoor target detetion

The spatial and frequency diversity introduced by the recent WiFi standards based on orthogonal frequency-division multiplexing is exploited for the robust wireless detection of device-free targets 111 indoor environments. The arising inverse problem is solved by decomposing the channel state information by means of a customized strategy based on the principal component analysis (PCA) for extracting target-dependent, components from the WiFi signal. The experimental validation of the proposed solution pointed out a robust target detection with failure rates lower than 3 [%] using a single wireless link already deployed in a real office test, field.

Compact planar frequency reconfigurable multiple‐input‐multiple‐output antenna with pattern and polarization diversity characteristics for WiFi and WiMAX standards

A compact planar frequency reconfigurable dual-band multiple-input-multiple-output (MIMO) antenna with high isolation and pattern/polarization diversity characteristics is presented in this article for WiFi and WiMAX standards. The MIMO configuration incorporates two symmetrically placed identical antenna elements and covers overall size of 24 mm × 24 mm × 0.762 mm. Reconfiguration of each antenna element is achieved by using a PIN diode which allows antennas to switch from state-1 (2.3-2.4 GHz and 4.6-5.5 GHz) to state-2 (3.3-3.5 GHz and 4.6-5.5 GHz). In state-1, the configuration offers isolation ≥18 dB and 20 dB in lower band (LB) and upper band (UB) respectively; whereas, in state-2, isolation ≥21 dB and 20 dB in LB and UB respectively is achieved. The same decoupling circuit provides high isolation in dual-band of two states, which makes overall size of the proposed design further compact. The antennas are characterized in terms of envelope correlation coefficient, radiation pattern, gain, and efficiency. From measured and simulated results, it is verified that the proposed frequency reconfigurable dual-band multi-standard MIMO antenna design shows desirable performance in both operating bands of each state and compact size of the design makes it suitable for small form factor devices used in future wireless communication systems.

Current Status and Directions of IEEE 802.11be, the Future Wi-Fi 7

While customers rivet their eyes on Wi-Fi 6, in the bowels of the IEEE 802.11 Working Group that creates Wi-Fi standards, the next generation Wi-Fi is being developed. At the very first sight, the new IEEE 802.11be amendment to the Wi-Fi standard is nothing but scaled 11ax with doubled bandwidth and the increased number of spatial streams, which together provide data rates as high as 40 Gbps. A bit deeper dive into the 802.11 activities reveals that 11be will support real-time applications. In reality, 11be introduces many more revolutionary changes to Wi-Fi, which will form a basement for further Wi-Fi evolution. Although by now (May 2020), the development process is at the very early phase without any draft specification, the analysis of the discussion in the 802.11 Working Group gives insights into the main innovations of 11be. In addition to the ones above, they include native multi-link operation, channel sounding optimization that opens the door for massive MIMO, advanced PHY and MAC techniques, the cooperation of various access points. The paper analyzes hundreds of features proposed for the new technology, focusing on the open problems that can be solved by the researchers who want to contribute to the development of 802.11be.

WiWeHAR: Multimodal Human Activity Recognition Using Wi-Fi and Wearable Sensing Modalities

Robust and accurate human activity recognition (HAR) systems are essential to many human-centric services within active assisted living and healthcare facilities. Traditional HAR systems mostly leverage a single sensing modality (e.g., either wearable, vision, or radio frequency sensing) combined with machine learning techniques to recognize human activities. Such unimodal HAR systems do not cope well with real-time changes in the environment. To overcome this limitation, new HAR systems that incorporate multiple sensing modalities are needed. Multiple diverse sensors can provide more accurate and complete information resulting in better recognition of the performed activities. This article presents WiWeHAR-a multimodal HAR system that uses combined Wi-Fi and wearable sensing modalities to simultaneously sense the performed activities. WiWeHAR makes use of standard Wi-Fi network interface cards to collect the channel state information (CSI) and a wearable inertial measurement unit (IMU) consisting of accelerometer, gyroscope, magnetometer sensors to collect the user's local body movements. We compute the time-variant mean Doppler shift (MDS) from the processed CSI data and magnitude from the inertial data for each sensor of the IMU. Thereafter, we separately extract various time- and frequency-domain features from the magnitude data and the MDS. We apply feature-level fusion to combine the extracted features, and finally supervised learning techniques are used to recognize the performed activities. We evaluate the performance of WiWeHAR by using a multimodal human activity data set, which was obtained from 9 participants. Each participant carried out four activities, such as walking, falling, sitting, and picking up an object from the floor. Our results indicate that the proposed multimodal WiWeHAR system outperforms the unimodal CSI, accelerometer, gyroscope, and magnetometer HAR systems and achieves an overall recognition accuracy of 99.6%-100%.

Влияние электромагнитных излучений на ориентировочно-исследовательскую активность и когнитивные функции крыс с контрастной возбудимостью нервной системы

In recent years, the mechanisms of influence that technogenic sources of electromagnetic radiation and the change in the natural electromagnetic field have on biological objects have been actively investigated. Nevertheless, the role of ancestral conditional characteristics of the nervous system in susceptibility towards and resilience against electromagnetic field oscillations has been virtually ignored. The objective of our research is to investigate the impact of the UHF band radiation emitted by a standard Wi-Fi router and the impact of external magnetic and electric fields weakened by shielding on animals’ innate behaviour which reflects orientational and exploratory activity and emotional response in an Open Field Test, and also on the cognitive functions (retention of the conditioned response of passive avoidance) of male rats from two selected strains: HT and LT — with high and low thresholds of nervous system excitability, and control Wistar rats. The outcomes of the study confirm the negative impact of weak external electric and magnetic fields, as well as EMR of the UHF band, on innate behaviour and memory in rats regardless of the selected strain, although HT rats were more sensitive to changes in magnetic and electric fields and electromagnetic radiation in comparison with LT rats.

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.

A Ubiquitous WiFi-Based Fine-Grained Gesture Recognition System

We present WiGest: a system that leverages changes in WiFi signal strength to sense in-air hand gestures around the user's mobile device. WiGest uses standard WiFi equipment, with no modifications, and requires no training for gesture recognition. The system identifies different RSS change primitives, from which we construct mutually-independent gesture families. These families can be mapped to distinguishable application actions. More fine-grained features can also be recognized for the detected primitives using CSI. WiGest addresses various challenges including cleaning the noisy signals, gesture type and attribute detection, reducing false positives due to interfering humans, and adapting to changing signal polarity. We implement a proof-of-concept prototype using off-the-shelf devices and extensively evaluate the system in two different environments. Our results show that WiGest detects the basic primitives with an accuracy of 87.5 percent using one AP, including through-the-wall non-line-of-sight scenarios, which increases to 96 percent using three overheard APs. Additionally, when evaluating the system using a multi-media player application, we achieve an accuracy of 96 percent. This accuracy is robust to the presence of other interfering humans, highlighting WiGest's ability to enable future ubiquitous hands-free gesture-based interaction with mobile devices.

An SDR implementation of WiFi receiver for mitigating multiple co-channel ZigBee interferers

Machine-to-machine (M2M) communication is one of the vertical sectors that will benefit from 5G communication systems, but today, these systems are still dominated by technologies such as ZigBee and WiFi. An M2M scenario will experience dense deployment of ZigBee and WiFi nodes in order to route the data from one end to the other. In the 2.4 GHz industrial, scientific, and medical (ISM) band, both of the technologies perform co-channel overlapped operation and hence face severe cross technology co-channel interference (CCI). In contrast to cellular systems, which solve the CCI by centralized coordination through the base station, addressing CCI in the ISM band is non-trivial due to heterogeneous wireless technologies and the lack of centralized coordination. In this work, we first present interference mitigating receiver architectures for OFDM-based WiFi using single and multiple antennas. Our single antenna work is based on the localized estimation of excess noise caused by single and multiple co-channel narrowband interferers and scaling the log-likelihood ratios (LLRs) of the affected WiFi subcarriers. The simulation shows our method achieves a significant gain in SNR compared to the conventional method for a given packet error rate (PER) criterion. Next, we discuss maximal ratio combiner with LLR scaling (MLSC), which is a multi-antenna extension to our previous work. The simulation shows MLSC achieves diversity gain apart from the gain in SNR. Further, we propose soft-bit maximal ratio combiner with LLR scaling (SB-MLSC). SB-MLSC is an easy to implement version of MLSC. However, diversity combining in SB-MLSC is performed by combining the LLRs. Nonetheless, simulations show equivalence in performance by SB-MLSC and MLSC. Finally, as a significant part of this work, we implemented all our methods using a software-defined radio (SDR) and performed over-the-air (OTA) testing in the 2.4-GHz ISM band using standard WiFi and ZigBee frames. Results of OTA tests fall in complete agreement with our simulations indicating the practical applicability of our methods. Our methods apply to all the standards and related radio transmission techniques which are based on OFDM and face narrowband co-channel interference. Additionally, since our work focuses only on receiver side modifications, they can be integrated with the existing infrastructure with minimal modifications.

Impact of electromagnetic uhf radiation on genome destabilization in bone marrow cell of rat strains with contrast nervous system excitability

Сhromosomal machinery of highly excited animals with low threshold of the nervous system excitability (LT strain) is more susceptible to the damaging effect of high frequency EMR compared against the animals with high threshold of the nervous system excitability (HT strain). High nervous system excitability determines greater decrease in chromosome aberrations level in the presence of additional reflecting elements Aires Defender Pro resonators under UHF-waves of standard Wi-Fi router. It is shown that the genotype of animals and the functional state of their nervous system affect susceptibility to the UHF EMR and the action of resonators.

A Framework for Enabling Internet Access Using Wi-Fi Peer-to-Peer Links

To realize the vision of ubiquitous computing and reachability, major technological advances have been achieved to make smart portable devices both highly capable and affordable. To facilitate connectivity to the Internet, these smart devices are equipped with different network interface cards (4G, Bluetooth and Wi-Fi). However, such connectivity may become seriously reduced in places with intermittent network services and/or shortage of Wi-Fi coverage. This limitation may be seriously harmful in rescue scenarios during and after a disastrous event, since blocked users may become difficult to reach. In this paper we present a novel framework to overcome such issue by implementing a hot-spot accessible through device-to-device (D2D) links. In this work, Wi-Fi direct (WFD) is used in order to establish multi-hop P2P paths to the hot-spot. WFD has the same features that carries the standard Wi-Fi in terms of range and speed without using the infrastructure. Wi-Fi direct is largely emerging as a network technology standard enabled in the majority of smartphones. By exploiting nearby devices, which have Internet access, our framework enables users to publish contents. Moreover, our model is validated by using different smartphones and through extensive simulation experiments.

A Study on Room-Level Accuracy of Wi-Fi Fingerprinting-Based Indoor Localization Systems

Global positioning system and other outdoor positioning mechanisms are already subject to comprehensive research and development for almost half a century. Conversely, indoor positioning services became a hot topic in the last decade. Since GPS (and. other outdoor solutions) do not work reliably in most indoor environments, researchers and developers are working on accurate positioning solutions, especially tailored for indoor places. However; due to walls, furniture, people and other obstacles, absolute location estimation is very hard and expensive to achieve in indoor places. In addition, accuracy needs depend on the scenario and application. In this study, we have studied the feasibility of room-level location detection in home and office environments. We have focused on examining the quality of room-wise detection accuracy of the fingerprinting method that is applied along with standard Wi-Fi radio infrastructure. We have conducted experiments in a multi-storey office building made of concrete and aerated concrete bricks with many rooms, in which it is significantly hard to accurately estimate the correct place of a thing, using radio signals. To the best of our knowledge, our paper is the first study that investigates the room-level accuracy of Wi-Fi fingerprinting-based indoor localization systems. We have found out that, it is possible to feasibly achieve room-level detection with good accuracy, via a pre-calculated room-specific received signal strength indicator threshold value.

Glucose biosensor based on open-source wireless microfluidic potentiostat

Wireless potentiostats capable of cyclic voltammetry and amperometry that connect to the Internet are emerging as key attributes of future point-of-care devices. This work presents an “integrated microfluidic electrochemical detector” (iMED) three-electrode multi-potentiostat designed around operational amplifiers connected to a powerful WiFi-based microcontroller as a promising alternative to more expensive and complex strategies reported in the literature. The iMED is integrated with a microfluidic system developed to be controlled by the same microcontroller. The iMED is programmed wirelessly over a standard WiFi network and all electrochemical data is uploaded to an open-source cloud-based server. A wired desktop computer is not necessary for operation or program uploading. This method of integrated microfluidic automation is simple, uses common and inexpensive materials, and is compatible with commercial sample injectors. An integrated biosensor platform contains four screen-printed carbon arrays inside 4 separate microfluidic detection chambers with Pt counter and pseudo Ag/AgCl reference electrodes in situ. The iMED is benchmarked with K3[Fe(CN)6] against a commercial potentiostat and then as a glucose biosensor using glucose-oxidising films of [Os(2,2′-bipyridine)2(poly-vinylimidazole)10Cl] prepared on screen-printed electrodes with multi walled carbon nanotubes, poly(ethylene glycol) diglycidyl ether and flavin adenine dinucleotide-dependent glucose dehydrogenase. Potential application of this cost-effective wireless potentiostat approach to modern bioelectronics and point-of-care diagnosis is demonstrated by production of glucose oxidation currents, under pseudo-physiological conditions, using mediating films with lower redox potentials.

A dual‐mode tunable bandpass filter for GSM, UMTS, WiFi, and WiMAX standards applications

SummaryThis paper presents a dual‐mode tunable bandpass filter (BPF) for global system for mobile communication, universal mobile telecommunications system, wireless fidelity, and worldwide interoperability for microwave access standard applications. The proposed filter consists of a stepped‐impedance resonator, single resonator, and coupled line, which are loaded with varactors. The center frequency and bandwidth of the proposed filter can be tuned with tuning varactors. Furthermore, the measurement results show that the BPF can be tuned over the frequency range of 1.8 to 2.5 GHz. Moreover, the bandwidth can be changed at each certain frequency. Furthermore, using PIN diodes, a bandstop filter is added to the tunable BPF to reduce the out‐of‐band frequencies around the desired frequencies. The values of LC equivalent circuits are calculated, and the results are compared with those obtained from the layout of the proposed structure. Finally, the measurement results justify the simulation results.

A Novel Reconfigurable Orthogonal Frequency Division Multiplexing Transceiver

As the world moves toward 3G/4G there is a need for high data rate and relatively wide bandwidths. OFDM (Orthogonal Frequency Division Multiplexing) a form of multicarrier modulation technique is widely used to achieve high speed efficient data transmission at the rate of several Mbps. It is used in Wi-Fi standards like 802.11a, 802.11n, 802.11ac, broadcast standards like Digital Video Broadcast (DVB) and cellular telecommunications standard LTE. The main advantage of OFDM compared to single carrier modulation is their robustness to channel fading in wireless environment, high baud rates and less inter symbol interference. One major disadvantage is its High PAPR. PTS partial transmit sequences (PTS) and selective mapping are proposed to reduce it. Since FFT is core block of OFDM it must be able to adapt itself to ever changing digital world. A function specific reconfigurable 2k SDF (Single path delay feedback) FFT is proposed. It utilizes less power and can be configured for different FFT sizes ranging from 16-point to 1024-point. The validity and efficiency of the architecture have been verified by simulation in hardware description language VERILOG and targeted on Virtex-6 device. Finally PAPR is estimated by MATLAB simulation.

COMPARATIVE CHARACTERISTICS OF WIRELESS SYSTEMS OF 802.11 STANDARDS FOR CAPACITY AND PERFORMANCE

At present, there is an exponential increase in the total data traffic of mobile networks. Implementation of new technologies, implementation of innovative infrastructure solutions, as well as optimization and increase of efficiency of use of existing networks are necessary to prevent failures and congestion. The most promising way, from a mobile operator's perspective, is to develop a macro level and use Wi-Fi to offload LTE-A (Wi-Fi Offloading). However, the efficiency of the conflict resolution algorithms used in modern Wi-Fi systems is significantly reduced with increasing number of subscribers. Features of the family of the latest Wi-Fi standards (IEEE 802.11n, IEEE 802.11ac, IEEE 802.11ax), which are intended for unloading mobile networks and quality provision of Internet of Things, are considered in the article. A review and comparison of the protocols of the latest IEEE 802.11 standards showed that, technically, Wi-Fi 6 has a data rate that is 37% faster than 802.11ac, but more importantly, the updated specification offers 4 times more bandwidth per user in crowded places, as well as higher energy efficiency, which should increase the battery life of the devices. To achieve these improvements, 802.11ax has made many changes, including several multi-user technologies borrowed from the cellular industry, namely MU-MIMO and OFDMA technologies, which greatly increase bandwidth and productivity through more concurrent connections and more careful use of the spectrum. The results of simulation modeling of the delay in packet transmission, average access point bandwidth and data loss values ​​using different modes of collective access to the IEEE 802.11n network channels: distributed (DCF) and centralized (PCF) access coordination functions. OPNET Modeler, which is radio-oriented and allows you to build models without programming, has been selected to develop the network simulation model.

Wisture: Touch-Less Hand Gesture Classification in Unmodified Smartphones Using Wi-Fi Signals

This paper introduces Wisture, a new online machine learning solution for recognizing touch-less hand gestures on a smartphone (mobile device). Wisture relies on the standard Wi-Fi received signal strength measurements, long short-term memory recurrent neural network (RNN) learning method, thresholding filters, and a traffic induction approach. Unlike other Wi-Fi-based gesture recognition methods, the proposed method does not require a modification of the device hardware or the operating system and performs the gesture recognition without interfering with the normal operation of other smartphone applications. We discuss the characteristics of Wisture and conduct extensive experiments to compare the performance of the RNN learning method against the state-of-the-art machine learning solutions regarding both accuracy and efficiency. The experiments include a set of different scenarios with a change in spatial setup and network traffic between the smartphone and Wi-Fi access points. The results show that Wisture achieves an online gesture recognition accuracy of up to 93% (average 78%) in detecting and classifying three gestures.

WiFO: A hybrid communication network based on integrated free-space optical and WiFi femtocells

Developments in smart home technology and the Internet of Things have significantly increased the demand for high-speed indoor wireless links. Although the majority of the research conducted in this area is still focused on the efficient usage of radio frequency (RF) spectrum, free-space optical (FSO) networks have also been explored as an alternative due to their large bandwidth potentials and low interference. In this paper we present a hybrid FSO and WiFi system (WiFO) that seamlessly integrates optical femtocell architecture with high mobility WiFi networks. Each FSO femtocell in this indoor communication system is capable of transmitting and receiving data at a rate of 50 Mbps over a distance of up to three meters with a field-of-view of ±15°, while still achieving a low bit error rate between 10−6, and 10−4. Reed–Solomon forward error correction codes were also applied to the data stream to further reduce the bit error rate to below 10−7. Different than many other free-space optical communication network using static transceivers, mobility in our WiFO system is achieved through the integration of a WiFi channel in the network protocol. The WiFi channel provides a feedback mechanism and allows for seamless handoffs between FSO femtocells. Additionally, we have experimentally demonstrated the advantage of this WiFO architecture by comparing the throughput of our system with a standard WiFi link in a realistic scenario. Our investigation has shown that the WiFO system presented in this work offers a cost-effective and easy-to-implement approach to significantly increase the capacity of current WiFi networks.

Consistently High MIMO Rates via Switched-Beam Antennas

The demand for wireless bandwidth is rising to unprecedented levels. The industry has responded with the inclusion of advanced PHY techniques, most notably multi-user (MU) MIMO, in the most recent Wi-Fi and LTE standards. However, despite the theoretical promise for large multiplexing gains, in practice the rate gains are modest due to a combination of large overhead to collect channel state information and not-so-well-conditioned channel matrices. In this paper, we propose to replace omni-directional antennas with inexpensive switched-beam antennas to produce well-conditioned channel matrices for MU-MIMO purposes with very low overhead. Remarkably, the experimental results with both software-defined radios and commercial Wi-Fi chipsets show that, when appropriate antenna modes are used, this leads to a $3.5\times-5\times $ average throughput improvement in indoor environments. What is more, our backward compatible protocol extension coupled with an efficient algorithm to select appropriate antenna modes, achieve the aforementioned gains with almost zero overhead.

Privacy-Friendly Wi-Fi-Based Occupancy Estimation with Minimal Resources

Occupancy estimation is becoming an increasingly popular research topic, as solutions can be deployed both to the challenges of demand-driven ambient comfort control applications, and to the challenges of building safety and security. With this article, the authors aim to estimate the number of people in a particular area of a building, using only existing infrastructure. To achieve this, information is collected from the Wi-Fi Access Points installed throughout a building, in such a way that the privacy of the persons using the Wi-Fi resources remains intact. While several approaches have been proposed to address the occupancy question, the main contribution lies in that the solution uses only standard Wi-Fi infrastructure, already deployed in any modern building. In addition, the authors claim that their solution comes at virtually zero cost, as their mechanisms add negligible network traffic, using minimal network and processing resources, and it does not require specialised hardware.

A Study of Delay and Data Traffic of IEEE 802.15.4 ZigBee-Based WSN in a Smart Home

Wireless sensor networks (WSN) play a key role in modern applications, for instance, in smart homes as will be demonstrated in this paper. ZigBee technology provides better support when compared with WiFi, Bluetooth and Ultra Wide Band (UWB) standards regarding transmission range. This paper deals with the use of ZigBee WSN in a domestic application, namely smart home control. This model comprises a smart home with multiple rooms, designed in such a way that each room has sensors comprise for a varied environment. The sensor nodes will be presented by ZigBee end device which transmits the traffic to a master node in the form of a ZigBee coordinator. An OPNET modeler V14.5 was used in this simulation study. This paper presents seven models related to delay and data traffic received to improve WSN performance. Seven different WSN designs variations were utilized according to the number of rooms, sensors, coordinators, and routers. The outcomes demonstrate that one coordinator model causes more delay when compared with multiple coordinator models. Conversely, the presence of a router causes additional delay. This model should help electrical engineers when designing smart homes that utilize WSNs.