Localisation via Wi‑Fi networks is one of the possible techniques which can be used for positioning inside buildings or in other places without the GPS signal. The accurate indoor positioning system ...can help users with localisation or navigation within unfamiliar places. Almost all buildings are covered with the Wi‑Fi signal. Using the currently existing infrastructure will minimise cost for construction other types of indoor positioning systems. Among other reasons, usage of Wi‑Fi for positioning is also convenient because almost every mobile device has a Wi‑Fi capability and therefore the system can be easily used by everyone. However, an important factor is the precision of such a solution. The article is focused on the evaluation of Wi‑Fi localisation precision within the university grounds.
A Tutorial on IEEE 802.11ax High Efficiency WLANs Khorov, Evgeny; Kiryanov, Anton; Lyakhov, Andrey ...
IEEE Communications surveys and tutorials,
2019-Firstquarter, Volume:
21, Issue:
1
Journal Article
Peer reviewed
Open access
While celebrating the 21st year since the very first IEEE 802.11 "legacy" 2 Mbit/s wireless local area network standard, the latest Wi-Fi newborn is today reaching the finish line, topping the ...remarkable speed of 10 Gbit/s. IEEE 802.11ax was launched in May 2014 with the goal of enhancing throughput-per-area in high-density scenarios. The first 802.11ax draft versions, namely, D1.0 and D2.0, were released at the end of 2016 and 2017. Focusing on a more mature version D3.0, in this tutorial paper, we help the reader to smoothly enter into the several major 802.11ax breakthroughs, including a brand new orthogonal frequency-division multiple access-based random access approach as well as novel spatial frequency reuse techniques. In addition, this tutorial will highlight selected significant improvements (including physical layer enhancements, multi-user multiple input multiple output extensions, power saving advances, and so on) which make this standard a very significant step forward with respect to its predecessor 802.11ac.
Wireless device-to-device (D2D) communication has empowered efficient and convenient video sharing among neighboring devices. However, the mobility and diversity of user devices, combined with ...dynamically shifting channel conditions, make these processes susceptible to environmental interference. In this paper, we introduce an adaptive network coding scheme tailored for D2D raw source video streaming in the scalable video coding (SVC) format. Video frames are partitioned into equal-sized fragments and encoded into streaming packets with the addition of certain redundancy. To address the observed deficiency where decoding throughput of coded video frames is generally lower than that of the encoding operation on mobile device platforms, we introduce a parallel decoding algorithm based on LU decomposition. Furthermore, we propose a flexible adjustment mechanism, named Nefis, which dynamically adapts the network coding redundancy and stream resolution based on the statistical model established to predict current network conditions and video streaming quality. Implementation on Android platform demonstrates that Nefis reduce redundancy in bandwidth usage during streaming process and enhance resilience to network dynamics. Experimental results also conclusively demonstrate the feasibility and advantages of network coding technology in D2D streaming applications. Nevertheless, achieving these advantages requires carefully designed encoding and decoding mechanisms.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
To provide limited delays for remote sensing and control, gaming, and virtual reality applications, the Wi-Fi 7 standard introduces the Restricted Target Wake Time (R-TWT) mechanism, which reserves ...time intervals for particular stations with such real-time traffic. As legacy stations do not support R-TWT, the access point forbids channel access during these intervals for legacy stations. Quiet Intervals have been announced for this purpose. Since the support for the Quieting Framework can be configured as mandatory in some networks, Quiet Intervals are assumed to be valid protection for R-TWT. The paper describes experimental results with mass-market devices that disprove this assumption. The paper reveals significant inconsistencies between the standard and widely used devices, e.g., the inability to schedule multiple Quiet Intervals. It will be a significant problem for Wi-Fi 7 devices using R-TWT in heterogeneous networks with legacy devices and will require much effort from academia and industry to solve.
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High-precision indoor localisation is becoming a necessity with novel location-based services that are emerging around 5G. The deployment of high-precision indoor location technologies is usually ...costly due to the high density of reference points. In this work, we propose the opportunistic fusion of several different technologies, such as ultra-wide band (UWB) and WiFi fine-time measurement (FTM), in order to improve the performance of location. We also propose the use of fusion with cellular networks, such as LTE, to complement these technologies where the number of reference points is under-determined, increasing the availability of the location service. Maximum likelihood estimation (MLE) is presented to weight the different reference points to eliminate outliers, and several searching methods are presented and evaluated for the localisation algorithm. An experimental setup is used to validate the presented system, using UWB and WiFi FTM due to their incorporation in the latest flagship smartphones. It is shown that the use of multi-technology fusion in trilateration algorithm remarkably optimises the precise coverage area. In addition, it reduces the positioning error by over-determining the positioning problem. This technique reduces the costs of any network deployment oriented to location services, since a reduced number of reference points from each technology is required.
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Wireless networks are a key component of the telecommunications infrastructure in our society, and wireless services become increasingly important as the applications of wireless devices have ...penetrated every aspect of our lives. Although wireless technologies have significantly advanced in the past decades, most wireless networks are still vulnerable to radio jamming attacks due to the openness nature of wireless channels, and the progress in the design of jamming-resistant wireless networking systems remains limited. This stagnation can be attributed to the lack of practical physical-layer wireless technologies that can efficiently decode data packets in the presence of jamming attacks. This article surveys existing jamming attacks and anti-jamming strategies in wireless local area networks (WLANs), cellular networks, cognitive radio networks (CRNs), ZigBee networks, Bluetooth networks, vehicular networks, LoRa networks, RFID networks, GPS system, millimeter-wave (mmWave) and learning-assisted wireless systems, with the objective of offering a comprehensive knowledge landscape of existing jamming and anti-jamming strategies and therefore stimulating more research efforts to secure wireless networks against jamming attacks. Different from prior survey papers, this article conducts a comprehensive, in-depth review on jamming and anti-jamming strategies, casting insights on the design of jamming-resilient wireless networking systems. An outlook on promising anti-jamming techniques is offered at the end of this article to delineate important research directions.
WPA3-Personal renders the Simultaneous Authentication of Equals (SAE) password-authenticated key agreement method mandatory. The scheme achieves forward secrecy and is highly resistant to offline ...brute-force dictionary attacks. Given that SAE is based on the Dragonfly handshake, essentially a simple password exponential key exchange, it remains susceptible to clogging type of attacks at the Access Point side. To resist such attacks, SAE includes an anti-clogging scheme. To shed light on this contemporary and high-stakes issue, this work offers a full-fledged empirical study on Denial of Service (DoS) against SAE. By utilizing both real-life modern Wi-Fi 6 certified and non-certified equipment and the OpenBSD’s hostapd, we expose a significant number of novel DoS assaults affecting virtually any AP. No less important, more than a dozen of vendor-depended and severe zero-day DoS assaults are manifested, showing that the implementation of the protocol by vendors is not yet mature enough. The fallout of the introduced attacks to the associated stations ranges from a temporary loss of Internet connectivity to outright disconnection. To our knowledge, this work provides the first wholemeal appraisal of SAE’s mechanism endurance against DoS, and it is therefore anticipated to serve as a basis for further research in this timely and intriguing area.
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Positioning using Wi-Fi received signal strength indication (RSSI) signals is an effective method for identifying the user positions in an indoor scenario. Wi-Fi RSSI signals in an autonomous system ...can be easily used for vehicle tracking in underground parking. In Wi-Fi RSSI signal based positioning, the positioning system estimates the signal strength of the access points (APs) to the receiver and identifies the user’s indoor positions. The existing Wi-Fi RSSI based positioning systems use raw RSSI signals obtained from APs and estimate the user positions. These raw RSSI signals can easily fluctuate and be interfered with by the indoor channel conditions. This signal interference in the indoor channel condition reduces localization performance of these existing Wi-Fi RSSI signal based positioning systems. To enhance their performance and reduce the positioning error, we propose a hybrid deep learning model (HDLM) based indoor positioning system. The proposed HDLM based positioning system uses RSSI heat maps instead of raw RSSI signals from APs. This results in better localization performance for Wi-Fi RSSI signal based positioning systems. When compared to the existing Wi-Fi RSSI based positioning technologies such as fingerprint, trilateration, and Wi-Fi fusion approaches, the proposed approach achieves reasonably better positioning results for indoor localization. The experiment results show that a combination of convolutional neural network and long short-term memory network (CNN-LSTM) used in the proposed HDLM outperforms other deep learning models and gives a smaller localization error than conventional Wi-Fi RSSI signal based localization approaches. From the experiment result analysis, the proposed system can be easily implemented for autonomous applications.
The growing commercial interest in indoor location-based services (ILBS) has spurred recent development of many indoor positioning techniques. Due to the absence of Global Positioning System (GPS) ...signal, many other signals have been proposed for indoor usage. Among them, Wi-Fi (802.11) emerges as a promising one due to the pervasive deployment of wireless LANs (WLANs). In particular, Wi-Fi fingerprinting has been attracting much attention recently because it does not require line-of-sight measurement of access points (APs) and achieves high applicability in complex indoor environment. This survey overviews recent advances on two major areas of Wi-Fi fingerprint localization: advanced localization techniques and efficient system deployment. Regarding advanced techniques to localize users, we present how to make use of temporal or spatial signal patterns, user collaboration, and motion sensors. Regarding efficient system deployment, we discuss recent advances on reducing offline labor-intensive survey, adapting to fingerprint changes, calibrating heterogeneous devices for signal collection, and achieving energy efficiency for smartphones. We study and compare the approaches through our deployment experiences, and discuss some future directions.
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