Quality of service adaptive modulation and coding scheme for IEEE 802.11ac

Nowadays, the rising demand for digital communication technologies has contributed to the increase in the volume of traffic. This continuous trend of internet traffic has led to the deterioration of the quality of service (QoS) with reduced throughput and increased latency. This also is due to the proliferation of new broadband applications which require low latency and high throughput such as virtual reality and real-time gaming. Therefore, considering the aforementioned challenge in QoS of wireless networks, a link adaptation method is suggested in this study, in order to enhance the performance of the QoS in IEEE 802.11ac amendment wireless local-area network (WLAN). The proposed technique adaptively changes the transmission data rate by increasing or decreasing the modulation and coding scheme (MCS) level according to the traffic conditions. With the use of an OMNeT++ computer-aided design (CAD)-based simulation model, the effectiveness of the suggested approach is examined. Simulated findings were compared with the link adaptation approach of the default condition. The results of the simulation demonstrate that the proposed technique significantly increases throughput (36.48%) and decreases latency in comparison to the default situation. These findings demonstrate the technique's potential to improve WLAN QoS efficiency, notably in regard to throughput and latency

Feedback Mechanisms for Centralized and Distributed Mobile Systems

The wireless communication market is expected to witness considerable growth in the immediate future due to increasing smart device usage to access real-time data. Mobile devices become the predominant method of Internet access via cellular networks (4G/5G) and the onset of virtual reality (VR), ushering in the wide deployment of multiple bands, ranging from TVWhite Spaces to cellular/WiFi bands and on to mmWave. Multi-antenna techniques have been considered to be promising approaches in telecommunication to optimize the utilization of radio spectrum and minimize the cost of system construction. The performance of multiple antenna technology depends on the utilization of radio propagation properties and feedback of such information in a timely manner. However, when a signal is transmitted, it is usually dispersed over time coming over different paths of different lengths due to reflections from obstacles or affected by Doppler shift in mobile environments. This motivates the design of novel feedback mechanisms that improve the performance of multi-antenna systems. Accurate channel state information (CSI) is essential to increasing throughput in multiinput, multi-output (MIMO) systems with digital beamforming. Channel-state information for the operation of MIMO schemes (such as transmit diversity or spatial multiplexing) can be acquired by feedback of CSI reports in the downlink direction, or inferred from uplink measurements assuming perfect channel reciprocity (CR). However, most works make the assumption that channels are perfectly reciprocal. This assumption is often incorrect in practice due to poor channel estimation and imperfect channel feedback. Instead, experiments have demonstrated that channel reciprocity can be easily broken by multiple factors. Specifically, channel reciprocity error (CRE) introduced by transmitter-receiver imbalance have been widely studied by both simulations and experiments, and the impact of mobility and estimation error have been fully investigated in this thesis. In particular, unmanned aerial vehicles (UAVs) have asymmetric behavior when communicating with one another and to the ground, due to differences in altitude that frequently occur. Feedback mechanisms are also affected by channel differences caused by the user’s body. While there has been work to specifically quantify the losses in signal reception, there has been little work on how these channel differences affect feedback mechanisms. In this dissertation, we perform system-level simulations, implement design with a software defined radio platform, conduct in-field experiments for various wireless communication systems to analyze different channel feedback mechanisms. To explore the feedback mechanism, we then explore two specific real world scenarios, including UAV-based beamforming communications, and user-induced feedback systems

Pushing the Limits of Indoor Localization in Today’s Wi-Fi Networks

Wireless networks are ubiquitous nowadays and play an increasingly important role in our everyday lives. Many emerging applications including augmented reality, indoor navigation and human tracking, rely heavily on Wi-Fi, thus requiring an even more sophisticated network. One key component for the success of these applications is accurate localization. While we have GPS in the outdoor environment, indoor localization at a sub-meter granularity remains challenging due to a number of factors, including the presence of strong wireless multipath reflections indoors and the burden of deploying and maintaining any additional location service infrastructure. On the other hand, Wi-Fi technology has developed significantly in the last 15 years evolving from 802.11b/a/g to the latest 802.11n and 802.11ac standards. Single user multiple-input, multiple-output (SU-MIMO) technology has been adopted in 802.11n while multi-user MIMO is introduced in 802.11ac to increase throughput. In Wi-Fi’s development, one interesting trend is the increasing number of antennas attached to a single access point (AP). Another trend is the presence of frequency-agile radios and larger bandwidths in the latest 802.11n/ac standards. These opportunities can be leveraged to increase the accuracy of indoor wireless localization significantly in the two systems proposed in this thesis: ArrayTrack employs multi-antenna APs for angle-of-arrival (AoA) information to localize clients accurately indoors. It is the first indoor Wi-Fi localization system able to achieve below half meter median accuracy. Innovative multipath identification scheme is proposed to handle the challenging multipath issue in indoor environment. ArrayTrack is robust in term of signal to noise ratio, collision and device orientation. ArrayTrack does not require any offline training and the computational load is small, making it a great candidate for real-time location services. With six 8-antenna APs, ArrayTrack is able to achieve a median error of 23 cm indoors in the presence of strong multipath reflections in a typical office environment. ToneTrack is a fine-grained indoor localization system employing time difference of arrival scheme (TDoA). ToneTrack uses a novel channel combination algorithm to increase effective bandwidth without increasing the radio’s sampling rate, for higher resolution time of arrival (ToA) information. A new spectrum identification scheme is proposed to retrieve useful information from a ToA profile even when the overall profile is mostly inaccurate. The triangle inequality property is then applied to detect and discard the APs whose direct path is 100% blocked. With a combination of only three 20 MHz channels in the 2.4 GHz band, ToneTrack is able to achieve below one meter median error, outperforming the traditional super-resolution ToA schemes significantly

MUSE-Fi: Contactless MUti-person SEnsing Exploiting Near-field Wi-Fi Channel Variation

Having been studied for more than a decade, Wi-Fi human sensing still faces a major challenge in the presence of multiple persons, simply because the limited bandwidth of Wi-Fi fails to provide a sufficient range resolution to physically separate multiple subjects. Existing solutions mostly avoid this challenge by switching to radars with GHz bandwidth, at the cost of cumbersome deployments. Therefore, could Wi-Fi human sensing handle multiple subjects remains an open question. This paper presents MUSE-Fi, the first Wi-Fi multi-person sensing system with physical separability. The principle behind MUSE-Fi is that, given a Wi-Fi device (e.g., smartphone) very close to a subject, the near-field channel variation caused by the subject significantly overwhelms variations caused by other distant subjects. Consequently, focusing on the channel state information (CSI) carried by the traffic in and out of this device naturally allows for physically separating multiple subjects. Based on this principle, we propose three sensing strategies for MUSE-Fi: i) uplink CSI, ii) downlink CSI, and iii) downlink beamforming feedback, where we specifically tackle signal recovery from sparse (per-user) traffic under realistic multi-user communication scenarios. Our extensive evaluations clearly demonstrate that MUSE-Fi is able to successfully handle multi-person sensing with respect to three typical applications: respiration monitoring, gesture detection, and activity recognition.Comment: 15 pages. Accepted by ACM MobiCom 202

Developing a Systematic Process for Mobile Surveying and Analysis of WLAN security

Wireless Local Area Network (WLAN), familiarly known as Wi-Fi, is one of the most used wireless networking technologies. WLANs have rapidly grown in popularity since the release of the original IEEE 802.11 WLAN standard in 1997. We are using our beloved wireless internet connection for everything and are connecting more and more devices into our wireless networks in every form imaginable. As the number of wireless network devices keeps increasing, so does the importance of wireless network security. During its now over twenty-year life cycle, a multitude of various security measures and protocols have been introduced into WLAN connections to keep our wireless communication secure. The most notable security measures presented in the 802.11 standard have been the encryption protocols Wired Equivalent Privacy (WEP) and Wi-Fi Protected Access (WPA). Both encryption protocols have had their share of flaws and vulnerabilities, some of them so severe that the use of WEP and the first generation of the WPA protocol have been deemed irredeemably broken and unfit to be used for WLAN encryption. Even though the aforementioned encryption protocols have been long since deemed fatally broken and insecure, research shows that both can still be found in use today. The purpose of this Master’s Thesis is to develop a process for surveying wireless local area networks and to survey the current state of WLAN security in Finland. The goal has been to develop a WLAN surveying process that would at the same time be efficient, scalable, and easily replicable. The purpose of the survey is to determine to what extent are the deprecated encryption protocols used in Finland. Furthermore, we want to find out in what state is WLAN security currently in Finland by observing the use of other WLAN security practices. The survey process presented in this work is based on a WLAN scanning method called Wardriving. Despite its intimidating name, wardriving is simply a form of passive wireless network scanning. Passive wireless network scanning is used for collecting information about the surrounding wireless networks by listening to the messages broadcasted by wireless network devices. To collect our research data, we conducted wardriving surveys on three separate occasions between the spring of 2019 and early spring of 2020, in a typical medium-sized Finnish city. Our survey results show that 2.2% out of the located networks used insecure encryption protocols and 9.2% of the located networks did not use any encryption protocol. While the percentage of insecure networks is moderately low, we observed during our study that private consumers are reluctant to change the factory-set default settings of their wireless network devices, possibly exposing them to other security threats

Towards Integrated Sensing and Communications in IEEE 802.11bf Wi-Fi Networks

As Wi-Fi becomes ubiquitous in public and private spaces, it becomes natural to leverage its intrinsic ability to sense the surrounding environment to implement groundbreaking wireless sensing applications such as human presence detection, activity recognition, and object tracking. For this reason, the IEEE 802.11bf Task Group is defining the appropriate modifications to existing Wi-Fi standards to enhance sensing capabilities through 802.11-compliant devices. However, the new standard is expected to leave the specific sensing algorithms open to implementation. To fill this gap, this article explores the practical implications of integrating sensing and communications into Wi-Fi networks. We provide an overview of the support that will enable sensing applications, together with an in-depth analysis of the role of different devices in a Wi-Fi sensing system and a description of the open research challenges. Moreover, an experimental evaluation with off-the-shelf devices provides suggestions about the parameters to be considered when designing Wi-Fi sensing systems. To make such an evaluation replicable, we pledge to release all of our dataset and code to the community