Stochastic Geometry Analysis of Individual Carrier Sense Threshold Adaptation in IEEE 802.11ax WLANs

This paper discusses the impact of spatial reuse and carrier sense threshold (CST) optimization on the performance of wireless local area networks using stochastic geometry analysis. The adjustment of the CST is a promising approach to improve spatial reuse, and has been proposed for the IEEE 802.11ax standard. Considering the situation where each access point (AP) individually adjusts its CST based on the individual received power, this paper derives the probability of transmission success and the density of successful transmissions (DST). The evaluation results of these metrics reveal that the optimal setting is to increase the CST linearly (in terms of dB) with respect to the average received signal power. Because the maximization of the DST causes unfairness from the viewpoint of success of transmission, the maximization of the product of the transmission success probabilities is proposed to improve the performance of the entire system and restrain unfairness. Using the trend of the optimal CST function, the impact of the density of APs on the optimal CST function is determined. Moreover, individual CST adjustment is found to improve spatial reuse compared with identical adjustment, i.e., setting the CST of all APs to an identical value

An RF-Isolated Real-Time Multipath Testbed for Performance Analysis of WLANs

Real-time performance evaluation of wireless local area networks (WLANs) is an extremely challenging topic. The major drawback of real-time performance analysis in actual network installations is a lack of repeatability due to uncontrollable interference and propagation complexities. These are caused by unpredictable variations in the interference scenarios and statistical behavior of the wireless propagation channel. This underscores the need for a Radio Frequency (RF) test platform that provides isolation from interfering sources while simulating a real-time wireless channel, thereby creating a realistic and controllable radio propagation test environment. Such an RF-isolated testbed is necessary to enable an empirical yet repeatable evaluation of the effects of the wireless channel on WLAN performance. In this thesis, a testbed is developed that enables real-time laboratory performance evaluation of WLANs. This testbed utilizes an RF-isolated test system, Azimuthâ„¢ Systems 801W, for isolation from external interfering sources such as cordless phones and microwave ovens and a real-time multipath channel simulator, Elektrobit PROPSimâ„¢ C8, for wireless channel emulation. A software protocol analyzer, WildPackets Airopeek NX, is used to capture data packets in the testbed from which statistical data characterizing performance such as data rate and Received Signal Strength (RSS) are collected. The relationship between the wireless channel and WLAN performance, under controlled propagation and interference conditions, is analyzed using this RF-isolated multipath testbed. Average throughput and instantaneous throughput variation of IEEE 802.11b and 802.11g WLANs operating in four different channels - a constant channel and IEEE 802.11 Task Group n (TGn) Channel Models A, B, and C - are examined. Practical models describing the average throughput as a function of the average received power and throughput variation as a function of the average throughput under different propagation conditions are presented. Comprehensive throughput models that incorporate throughput variation are proposed for the four channels using Weibull and Gaussian probability distributions. These models provide a means for realistic simulation of throughput for a specific channel at an average received power. Also proposed is a metric to describe the normalized throughput capacity of WLANs for comparative performance evaluation

Wi-Fi Denial of Service Attack on Wired Analog RF Channel Emulator

This report presents the design and implementation of an analog wireless channel emulator to examine various denial of service attacks in multiple mobile scenarios. The scenarios emulated in this project involve three node topologies of wireless interferers (Wi-Fi radios), including a software defined radio that transmits one of three denial of service (DoS) waveforms. The testbed was functional and met the original specifications. Results from mobile experiments show a clear distinction in performance among the three DoS waveforms depending on the node topology; a digital waveform using binary phase shift keying (BPSK) is most effective at reducing total network throughput at close range while sweep waveforms exhibit minor throughput reduction from a greater distance

Channel ranking scheme in wireless sensor networks based on packet delivery ratio estimation

The widespread deployment of competitive wireless technologies in the 2.4 GHz unlicensed Industrial, Scientific, Medical (ISM) band has introduced co-existence issues between different wireless devices. Co-channel interference severely affects the performance of Wireless Sensor Networks (WSNs) that are limited to low transmission power and low data rate. This problem can be mitigated by searching the candidate channels and choosing ones for operation which provide more reliable connection. In this thesis, a Packet Delivery Ratio (PDR) estimation algorithm is proposed that can be used by WSNs operating in license free bands in order to rank the channels. Since the PDR is a function of Signal to Interference plus Noise Ratio at receiver node and the traffic pattern of the interferer, receiver node predicts the achievable PDR on each channel according to received signal strength from transmitter node, noise and interference characteristics obtained through spectrum measurements. Finally, channels are ranked based on achieved estimates. The PDR estimation algorithm is implemented on the IEEE 802.15.4-based wireless sensor platform in order to assess its performance. Wireless channels are emulated to model different environments and the accuracy of PDR estimates are observed under different channel conditions. It is beneficial to minimize the energy consumption of channel scanning by reducing the number of collected samples from the channel, while the desired accuracy is fulfilled for channel ranking purpose. Hence effect of number of collected samples on performance of estimates is investigated. The channel ranking method is also evaluated in a real environment to rank IEEE 802.15.4 candidate channels in existence of interference from multiple wireless devices in 2.4 GHz frequency band

Channel parameter tuning in a hybrid Wi-Fi-Dynamic Spectrum Access Wireless Mesh Network

This work addresses Channel Assignment in a multi-radio multi-channel (MRMC) Wireless Mesh Network (WMN) using both Wi-Fi and Dynamic Spectrum Access (DSA) spectrum bands and standards. This scenario poses new challenges because nodes are spread out geographically so may have differing allowed channels and experience different levels of external interference in different channels. A solution must meet two conflicting requirements simultaneously: 1) avoid or minimise interference within the network and from external interference sources, and 2) maintain connectivity within the network. These two requirements must be met while staying within the link constraints and the radio interface constraints, such as only assigning as many channels to a node as it has radios. This work's original contribution to the field is a unified framework for channel optimisation and assignment in a WMN that uses both DSA and traditional Wi-Fi channels for interconnectivity. This contribution is realised by providing and analysing the performance of near-optimal Channel Assignment (CA) solutions using metaheuristic algorithms for the MRMC WMNs using DSA bands. We have created a simulation framework for evaluating the algorithms. The performance of Simulated Annealing, Genetic Algorithm, Differential Evolution, and Particle Swarm Optimisation algorithms have been analysed and compared for the CA optimisation problem. We introduce a novel algorithm, used alongside the metaheuristic optimisation algorithms, to generate feasible candidate CA solutions. Unlike previous studies, this sensing and CA work takes into account the requirement to use a Geolocation Spectrum Database (GLSD) to get the allowed channels, in addition to using spectrum sensing to identify and estimate the cumulative severity of both internal and external interference sources. External interference may be caused by other secondary users (SUs) in the vicinity or by primary transmitters of the DSA band whose emissions leak into adjacent channels, next-toadjacent, or even into further channels. We use signal-to-interference-plus-noise ratio (SINR) as the optimisation objective. This incorporates any possible source or type of interference and makes our method agnostic to the protocol or technology of the interfering devices while ensuring that the received signal level is high enough for connectivity to be maintained on as many links as possible. To support our assertion that SINR is a reasonable criterion on which to base the optimisation, we have carried out extensive outdoor measurements in both line-of-sight and wooded conditions in the television white space (TVWS) DSA band and the 5 GHz Wi-Fi band. These measurements show that SINR is useful as a performance measure, especially when the interference experienced on a link is high. Our statistical analysis shows that SINR effectively differentiates the performance of different channels and that SINR is well correlated with throughput and is thus a good predictor of end-user experience, despite varying conditions. We also identify and analyse the idle times created by Carrier Sense Multiple Access with Collision Avoidance (CSMA/CA) contention-based Medium Access Control (MAC) operations and propose the use of these idle times for spectrum sensing to measure the SINR on possible channels. This means we can perform spectrum sensing with zero spectrum sensing delay experienced by the end user. Unlike previous work, this spectrum sensing is transparent and can be performed without causing any disruption to the normal data transmission of the network. We conduct Markov chain analysis to find the expected length of time of a sensing window. We also derive an efficient minimum variance unbiased estimator of the interference plus noise and show how the SINR can be found using this estimate. Our estimation is more granular, accurate, and appropriate to the problem of Secondary User (SU)-SU coexistence than the binary hypothesis testing methods that are most common in the literature. Furthermore, we construct confidence intervals based on the probability density function derived for the observations. This leads to finding and showing the relationships between the number of sampling windows and sampling time, the interference power, and the achievable confidence interval width. While our results coincide with (and thus are confirmed by) some key previous recommendations, ours are more precise, granular, and accurate and allow for application to a wider range of operating conditions. Finally, we present alterations to the IEEE 802.11k protocol to enable the reporting of spectrum sensing results to the fusion or gateway node and algorithms for distributing the Channel Assignment once computed. We analyse the convergence rate of the proposed procedures and find that high network availability can be maintained despite the temporary loss of connectivity caused by the channel switching procedure. This dissertation consolidates the different activities required to improve the channel parameter settings of a multi-radio multi-channel DSA-WMN. The work facilitates the extension of Internet connectivity to the unconnected or unreliably connected in rural or peri-urban areas in a more cost-effective way, enabling more meaningful and affordable access technologies. It also empowers smaller players to construct better community networks for sharing local content. This technology can have knock-on effects of improved socio-economic conditions for the communities that use it

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

Array Architectures and Physical Layer Design for Millimeter-Wave Communications Beyond 5G

Ever increasing demands in mobile data rates have resulted in exploration of millimeter-wave (mmW) frequencies for the next generation (5G) wireless networks. Communications at mmW frequencies is presented with two keys challenges. Firstly, high propagation loss requires base stations (BSs) and user equipment (UEs) to use a large number of antennas and narrow beams to close the link with sufficient received signal power. Consequently, communications using narrow beams create a new challenge in channel estimation and link establishment based on fine angular probing. Current mmW system use analog phased arrays that can probe only one angle at the time which results in high latency during link establishment and channel tracking. It is desirable to design low latency beam training by exploring both physical layer designs and array architectures that could replace current 5G approaches and pave the way to the communications for frequency bands in higher mmW band and sub-THz region where larger antenna arrays and communications bandwidth can be exploited. To this end, we propose a novel signal processing techniques exploiting unique properties of mmW channel, and show both theoretically, in simulation and experiments its advantages over conventional approaches. Secondly, we explore different array architecture design and analyze their trade-offs between spectral efficiency and power consumption and area. For comprehensive comparison, we have developed a methodology for optimal design of system parameters for different array architecture candidates based on the spectral efficiency target, and use these parameters to estimate the array area and power consumption based on the circuits reported in the literature. We show that the hybrid analog and digital architectures have severe scalability concerns in radio frequency signal distribution with increased array size and spatial multiplexing levels, while the fully-digital array architectures have the best performance and power/area trade-offs.The developed approaches are based on a cross-disciplinary research that combines innovation in model based signal processing, machine learning, and radio hardware. This work is the first to apply compressive sensing (CS), a signal processing tool that exploits sparsity of mmW channel model, to accelerate beam training of mmW cellular system. The algorithm is designed to address practical issues including the requirement of cell discovery and synchronization that involves estimation of angular channel together with carrier frequency offset and timing offsets. We have analyzed the algorithm performance in the 5G compliant simulation and showed that an order of magnitude saving is achieved in initial access latency for the desired channel estimation accuracy. Moreover, we are the first to develop and implement a neural network assisted compressive beam alignment to deal with hardware impairments in mmW radios. We have used 60GHz mmW testbed to perform experiments and show that neural networks approach enhances alignment rate compared to CS. To further accelerate beam training, we proposed a novel frequency selective probing beams using the true-time-delay (TTD) analog array architecture. Our approach utilizes different subcarriers to scan different directions, and achieves a single-shot beam alignment, the fastest approach reported to date. Our comprehensive analysis of different array architectures and exploration of emerging architectures enabled us to develop an order of magnitude faster and energy efficient approaches for initial access and channel estimation in mmW systems

Resilient Peer-to-Peer Ranging using Narrowband High-Performance Software-Defined Radios for Mission-Critical Applications

There has been a growing need for resilient positioning for numerous applications of the military and emergency services that routinely conduct operations that require an uninterrupted positioning service. However, the level of resilience required for these applications is difficult to achieve using the popular navigation and positioning systems available at the time of this writing. Most of these systems are dependent on existing infrastructure to function or have certain vulnerabilities that can be too easily exploited by hostile forces. Mobile ad-hoc networks can bypass some of these prevalent issues making them an auspicious topic for positioning and navigation research and development. Such networks consist of portable devices that collaborate to form wireless communication links with one another and collectively carry out vital network functions independent of any fixed centralized infrastructure. The purpose of the research presented in this thesis is to adapt the protocols of an existing narrowband mobile ad-hoc communications system provided by Terrafix to enable range measuring for positioning. This is done by extracting transmission and reception timestamps of signals exchanged between neighbouring radios in the network with the highest precision possible. However, many aspects of the radios forming this network are generally not conducive to precise ranging, so the ranging protocols implemented need to either maneuver around these shortcomings or compensate for loss of precision caused. In particular, the narrow bandwidth of the signals that drastically reduces the resolution of symbol timing. The objective is to determine what level of accuracy and precision is possible using this radio network and whether one can justify investment for further development. Early experiments have provided a simple ranging demonstration in a benign environment, using the existing synchronization protocols, by extracting time data. The experiments have then advanced to the radio’s signal processing to adjust the synchronization protocols for maximize symbol timing precision and correct for clock drift. By implementing innovative synchronization techniques to the radio network, ranging data collected under benign conditions can exhibit a standard deviation of less than 3m. The lowest standard deviation achieved using only the existing methods of synchronization was over two orders of magnitude greater. All this is achieved in spite of the very narrow 10−20kHz bandwidth of the radio signals, which makes producing range estimates with an error less than 10−100m much more challenging compared to wider bandwidth systems. However, this figure is beholden to the relative motion of neighbouring radios in the network and how frequently range estimates need to be made. This thesis demonstrates how such a precision may be obtained and how this figure is likely to hold up when applied in conditions that are not ideal