The provision of Wireless Fidelity (Wi-Fi) service in an indoor environment is a crucial task and the decay in signal strength issues arises especially in indoor environments. The Line-of-Sight (LOS) ...is a path for signal propagation that commonly impedes innumerable indoor objects damage signals and also causes signal fading. In addition, the Signal decay (signal penetration), signal reflection, and long transmission distance between transceivers are the key concerns. The signals lose their power due to the existence of obstacles (path of signals) and hence destroy received signal strength (RSS) between different communicating nodes and ultimately cause loss of the packet. Thus, to solve this issue, herein we propose an advanced model to maximize the LOS in communicating nodes using a modern indoor environment. Our proposal comprised various components for instance signal enhancers, repeaters, reflectors,. these components are connected. The signal attenuation and calculation model comprises of power algorithm and hence it can quickly and efficiently find the walls and corridors as obstacles in an indoor environment. We compared our proposed model with state of the art model using Received Signal Strength (RSS) and Packet Delivery Ratio (PDR) (different scenario) and found that our proposed model is efficient. Our proposed model achieved high network throughput as compared to the state-of-the-art models.
Recently, using Wi-Fi devices as sensing technology has garnered significant attention and found numerous applications. This trend has given birth to what is known as Wi-Fi sensing. This innovative ...approach has been made possible by analyzing the Channel State Information (CSI) of the Wi-Fi communication channel, which can be calculated from the frame preamble. CSI captures multipath effects, attenuations, and phase shifts in signal propagation, among other fading effects caused, for example, by reflection with objects or a person. Extensive research in this field has revealed that these effects can be utilized for sensing purposes, supposing that the cause of the effects is a person, leading to the development of Wi-Fi sensing applications such as Activity Recognition, Gesture Recognition, and Vital Signs monitoring. This Survey highlights recent works and advances in Wi-Fi sensing applications, identifying and exposing significant applications. For each paper selected, the following sections have been emphasized: Data Collection, Data Preprocessing, Detection Algorithm, Performance, and Application, as these are part of the methodology followed for the functioning of Wi-Fi sensing systems. Furthermore, the techniques and tools commonly used in Wi-Fi sensing are described. Finally, the current challenges associated with Wi-Fi as a wireless sensing technology and possible ways to address these challenges are discussed.
Wi-Fi sensing: applications and challenges Khalili, Abdullah; Soliman, Abdel-Hamid; Asaduzzaman, Md ...
Journal of engineering (Stevenage, England),
March 2020, Volume:
2020, Issue:
3
Journal Article
Peer reviewed
Open access
Wi-Fi technology has strong potentials in indoor and outdoor sensing applications; it has several important features which makes it an appealing option compared to other sensing technologies. This ...study presents a survey on different applications of Wi-Fi-based sensing systems such as elderly people monitoring, activity classification, gesture recognition, people counting, through the wall sensing, behind the corner sensing, and many other applications. The challenges and interesting future directions are also highlighted.
A deep neural network (DNN)-based Wi-Fi/pedestrian dead reckoning (PDR) indoor positioning system using an adaptive robust factor-graph model is proposed in this study for the indoor positioning of ...smartphones. In Wi-Fi positioning, the authors use a DNN to extract robust features from fluctuant Wi-Fi signals in the off-line phase, and obtain more accurate positioning results by computing posterior probabilities in online positioning. Acceleration, gyroscope, and magnetometer data are used to calculate attitude angle, step frequency, and step length, respectively. Received Wi-Fi signal strength is susceptible in complex indoor environments, and PDR errors accumulate over time. A factor-graph model with adaptive robust adjustment is proposed to fuse the positioning results of Wi-Fi and PDR, and it overcomes such shortcomings as slow update frequency and gross errors of Wi-Fi and PDR errors accumulated over time, respectively. When the absence of PDR occurs, hidden Markov model is introduced to smooth multiple DNN-based Wi-Fi positioning estimates at the unknown point to obtain the optimal solution. Experimental results show that the proposed system is more robust and has better accuracy under different motion gestures (held-in-hand, dangling, and calling).
The increase in the demand for eXtended Reality (XR)/Virtual Reality (VR) services in the recent years, poses a great challenge for Wi-Fi networks to maintain the strict latency requirements. In VR ...over Wi-Fi, latency is a significant issue. In fact, VR users expect instantaneous responses to their interactions, and any noticeable delay can disrupt user experience. Such disruptions can cause motion sickness, and users might end up quitting the service. Differentiating interactive VR traffic from Non-VR traffic within a Wi-Fi network can aim to decrease latency for VR users and improve Wi-Fi Quality of Service (QoS) with giving priority to VR users in the access point (AP) and efficiently handle VR traffic. In this paper, we propose a machine learning-based approach for identifying interactive VR traffic in a Cloud-Edge VR scenario. The correlation between downlink and uplink is crucial in our study. First, we extract features from single-user traffic characteristics and then, we compare six common classification techniques (i.e., Logistic Regression, Support Vector Machines, k-Nearest Neighbors, Decision Trees, Random Forest, and Naive Bayes). For each classifier, a process of hyperparameter tuning and feature selection, namely permutation importance is applied. The model created is evaluated using datasets generated by different VR applications, including both single and multi-user cases. Then, a Wi-Fi network simulator is used to analyze the VR traffic identification and prioritization QoS improvements. Our simulation results show that we successfully reduce VR traffic delays by a factor of 4.2x compared to scenarios without prioritization, while incurring only a 2.3x increase in delay for background (BG) traffic related to Non-VR services.
Although Wi-Fi is an ideal technology for many ranging applications, the performance of current methods is limited by the system bandwidth, leading to low accuracy of ~ 1 m. For many applications, ...measuring differential range, viz., the change in the range between adjacent measurements, is sufficient. Correspondingly, this work proposes WiDRa - a Wi-Fi based Differential Ranging solution that provides differential range estimates by using the sum-carrier-phase information. The proposed method is not limited by system bandwidth and can track range changes even smaller than the carrier wavelength. The proposed method is first theoretically justified, while taking into consideration the various hardware impairments affecting Wi-Fi chips. In the process, methods to isolate the sum-carrier phase from the hardware impairments are proposed. Extensive simulation results show that WiDRa can achieve a differential range estimation root-mean-square-error (RMSE) of ≈ 1 mm in channels with a Rician-factor ≥ 7 (a 100× improvement to existing methods). The proposed methods are also validated on off-the-shelf Wi-Fi hardware to demonstrate feasibility, where they achieve an RMSE of < 1 mm in the differential range. Finally, limitations of current investigation and future directions of exploration are suggested, to further tap into the potential of WiDRa.
This study presents a Wi-Fi-based passive indoor positioning system (IPS) that does not require active collaboration from the user or additional interfaces on the device-under-test (DUT). To maximise ...the accuracy of the IPS, the optimal deployment of Wi-Fi Sniffers in the area of interest is crucial. A modified Genetic Algorithm (GA) with an entropy-enhanced objective function is proposed to optimize the deployment. These Wi-Fi Sniffers are used to scan and collect the DUT's Wi-Fi received signal strength indicators (RSSIs) as Wi-Fi fingerprints, which are then mapped to reference points (RPs) in the physical world. The positioning algorithm utilises a weighted k-nearest neighbourhood (WKNN) method. Automated data collection of RSSI on each RP is achieved using a surveying robot for the Wi-Fi 2.4 GHz and 5 GHz bands. The preliminary results show that using only 20 Wi-Fi Sniffers as features for model training, the offline positioning accuracy is 2.2 m in terms of root mean squared error (RMSE). A proof-of-concept real-time online passive IPS is implemented to show that it is possible to detect the online presence of DUTs and obtain their RSSIs as online fingerprints to estimate their position.
Standard wireless systems are rapidly evolving to support the strict requirements of industrial applications. In this research line, wireless time-sensitive networking (TSN) is gaining momentum, ...thanks to the interest of wired TSN among the industries. A critical aspect of the wireless TSN research is the integration of wired and wireless TSN to create large-scale hybrid TSN networks. This integration is currently being discussed for 5G, whereas the integration between wired TSN and IEEE 802.11 is a step behind. To address this gap in the state of the art, this article discusses the integration challenges of wired TSN and wireless local area network technologies and proposes a hybrid TSN device architecture. Based on the architecture, we have developed a hybrid TSN network proof-of-concept. The proof-of-concept demonstrates that the hybrid TSN architecture can maintain the essential TSN services, including providing guaranteed latency in the 100-microsecond level.
Resource Slicing in Virtual Wireless Networks: A Survey Richart, Matias; Baliosian, Javier; Serrat, Joan ...
IEEE eTransactions on network and service management,
09/2016, Volume:
13, Issue:
3
Journal Article, Publication
Peer reviewed
Open access
New architectural and design approaches for radio access networks have appeared with the introduction of network virtualization in the wireless domain. One of these approaches splits the wireless ...network infrastructure into isolated virtual slices under their own management, requirements, and characteristics. Despite the advances in wireless virtualization, there are still many open issues regarding the resource allocation and isolation of wireless slices. Because of the dynamics and shared nature of the wireless medium, guaranteeing that the traffic on one slice will not affect the traffic on the others has proven to be difficult. In this paper, we focus on the detailed definition of the problem, discussing its challenges. We also provide a review of existing works that deal with the problem, analyzing how new trends such as software defined networking and network function virtualization can assist in the slicing. We will finally describe some research challenges on this topic.
Estimating the number of people present in a given venue in real-time is extremely useful from a security, management, and resource optimization perspective. This article presents the architecture of ...a system based on the use of Wi-Fi sensor devices that allows estimating, almost in real-time, the number of people attending an event that is taking place in a venue. The estimate is based on the analysis of the “probe request” messages periodically transmitted by smartphones to determine the existence of Wi-Fi access points in the vicinity. The method considers the MAC address randomization mechanisms introduced in recent years in smartphones, which prevents the estimation of the number of devices by simply counting different MAC addresses. To solve this difficulty, our Wi-Fi sensors analyze other fields present in the header of the IEEE 802.11 frames, the information elements, to extract a unique fingerprint from each smartphone. The designed system was tested in a set of real scenarios, obtaining an estimate of attendance at different public events with an accuracy close to 95%.
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