A Linear Subspace Approach to Burst Communication Signal Processing

This dissertation focuses on the topic of burst signal communications in a high interference environment. It derives new signal processing algorithms from a mathematical linear subspace approach instead of the common stationary or cyclostationary approach. The research developed new algorithms that have well-known optimality criteria associated with them. The investigation demonstrated a unique class of multisensor filters having a lower mean square error than all other known filters, a maximum likelihood time difference of arrival estimator that outperformed previously optimal estimators, and a signal presence detector having a selectivity unparalleled in burst interference environments. It was further shown that these improvements resulted in a greater ability to communicate, to locate electronic transmitters, and to mitigate the effects of a growing interference environment

Scalable System Design for Covert MIMO Communications

In modern communication systems, bandwidth is a limited commodity. Bandwidth efficient systems are needed to meet the demands of the ever-increasing amount of data that users share. Of particular interest is the U.S. Military, where high-resolution pictures and video are used and shared. In these environments, covert communications are necessary while still providing high data rates. The promise of multi-antenna systems providing higher data rates has been shown on a small scale, but limitations in hardware prevent large systems from being implemented

Kinematic and cyclostationary parameter estimation for co-channel emitter location applications

The problem of locating a signal source, or an emitter, has many civilian and military applications, such as communication regulations enforcement, military reconnaissance, and search-and-rescue operations. Many of the most widely used emitter location methods rely on the accurate and robust estimation of the differential time delay, or time-difference-of-arrival (TDOA), and the differential Doppler shift, or frequency- difference-of-arrival (FDOA), between signal replicas arriving at two spatially separated receivers. There are many conventional methods for estimating TDOA and/or FDOA. However, these methods are unable to produce unbiased TDOA and FDOA estimates when multiple emitters are located spatially close to each other. In many cases, the spatial proximity at which the conventional methods fail is still unacceptably large for precision emitter location applications. This problem is made even more diffcult when separating signals from multiple emitters that share the same regions of the spectrum at the same time. When spatially close emitters overlap spectrally and temporally, robust TDOA and FDOA estimation is diffcult, and accurate emitter location not only requires both estimation of TDOA, or FDOA, or both jointly, but also the estimation of a signal parameter that can be used to separate the signal-of-interest (SOI) from a signal(s)-not-of-interest (SNOI) that are both within the receiver's field of view. The signal separation pa- rameter selected depends on the type of signal modulation. In this thesis, the signals of interest are bauded signals. The separation methodology for such signals is cyclo- stationarity with parameterization by cyclic frequency. Based on this assumption, a new three-dimensional joint estimation method for TDOA, FDOA, and cyclic frequency parameters, called alpha cross ambiguity function (alpha-CAF), has been developed to ex- ploit signal modulations with cyclostationary properties. By exploiting cyclostationarity, alppha-CAF can produce separate unbiased TDOA and FDOA estimates that will in turn yield reliable geolocation estimates for precision emitter location applications even when severe interference causes conventional methods to fail. In this thesis the alpha-CAF param- eter estimation (TDOA, FDOA, Cyclic Frequency) algorithm is introduced along with a complete analysis of its performance compared to conventional estimators. A connection is also made between the alpha-CAF algorithm and the additional steps needed to perform an emitter location technique

A Survey of Positioning Systems Using Visible LED Lights

© 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.As Global Positioning System (GPS) cannot provide satisfying performance in indoor environments, indoor positioning technology, which utilizes indoor wireless signals instead of GPS signals, has grown rapidly in recent years. Meanwhile, visible light communication (VLC) using light devices such as light emitting diodes (LEDs) has been deemed to be a promising candidate in the heterogeneous wireless networks that may collaborate with radio frequencies (RF) wireless networks. In particular, light-fidelity has a great potential for deployment in future indoor environments because of its high throughput and security advantages. This paper provides a comprehensive study of a novel positioning technology based on visible white LED lights, which has attracted much attention from both academia and industry. The essential characteristics and principles of this system are deeply discussed, and relevant positioning algorithms and designs are classified and elaborated. This paper undertakes a thorough investigation into current LED-based indoor positioning systems and compares their performance through many aspects, such as test environment, accuracy, and cost. It presents indoor hybrid positioning systems among VLC and other systems (e.g., inertial sensors and RF systems). We also review and classify outdoor VLC positioning applications for the first time. Finally, this paper surveys major advances as well as open issues, challenges, and future research directions in VLC positioning systems.Peer reviewe

Effects of Multipath and Oversampling on Navigation Using Orthogonal Frequency Division Multiplexed Signals of Opportunity

The Global Positioning System (GPS) has become the primary system for navigation and precise positioning. GPS has limitations, though, and is not suitable in environments where a line-of-site (LOS) path to multiple satellites is not available. Reliable alternatives need to be developed to provide GPS-like positioning when GPS is unavailable. One such alternative is to use signals of opportunity (SoOP). This concept refers to navigation using signals which inherently exist in the environment and were developed for non-navigation applications. This research focuses on exploiting the Orthogonal Frequency Division Multiplexed (OFDM) signal for the purpose of navigation. An algorithm was developed to simulate a transmitter, receiver, channel noise, and multipath propagation. A transmitter and reference receiver, both at known locations, and a mobile receiver at an unknown location were used to conduct simulations with a transmitted OFDM signal in a Rayleigh-distributed multipath environment. The OFDM signal structure was exploited by using its cyclic prefix in a correlation process to find the first symbol boundary in each received signal. Each receiver calculates statistical features about each symbol in the received signal. These two sets of data are then correlated in order find the difference in symbol arrival times. The simulations were run for varying levels of oversampling in an effort to gain more accurate results by decreasing the sample period. Results show that oversampling the signal only slightly reduces errors in the symbol boundary correlation process, while multipath has a significant impact on correlation performance. It was also found that increasing the window size significantly improved feature correlator performance and yielded promising results even in the presence of high multipath environments

Efficient cooperative OFMD localization

The author of this project has been working on the topic of cooperative OFDM localization for one year in the TU Delft as an exchange student. Nowadays there are many potential uses for cooperative localization in places in which the common systems like GPS could not provide an accurate estimation. It is an advantage to join into a wireless network with a mobile device and be able to navigate and know your position. Two critical points in this topic are the accuracy of the localization, that is required to be high, and the power consumption of the mobile devices, which is a critical resource. Existing indoor cooperative localization methods require big battery consumption for the mobile relays, and the accuracy in low SNR situations is not good enough. The scope of this thesis is to estimate the localization of an unknown mobile device in an efficient way, being accurate even in low SNR situations, with low power consumption. One first approximation and the reference [11] suggested the idea of the “feature method” which is a bandwidth efficient cooperative ZP-OFDM localization method. After testing different features and conclude that the peak to average power ratio has the best performance another new idea came up. A new simple relay is proposed, called trigger relay, which consists of forwarding a known signal when the incoming signal is received. With this new idea it is solved the bandwidth and computational problem, being the most efficient method to estimate the TDOA. This brilliant idea was published in the PIMRC conference in September, 2011.Ingeniería de TelecomunicaciónTelekomunikazio Ingeniaritz

Time of Arrival and Angle of Arrival Estimation of LTE Signals for Positioning Applications

With the increase of services that need accurate location of the user, new techniques that cooperate with the Global Navigation Satellite System (GNSS) are necessary. Toward this objective, this thesis presents our research work about the estimation of the time of arrival (TOA) and of the angle of arrival (AOA) exploiting modern cellular signals. In particular, we focus on the Third Generation Partnership Project (3GPP) Long Term Evolution (LTE) standard, and in particular uplink and downlink reference signals are exploited to this purposes. The current release of the 3GPP LTE specification supports a UTDOA localization technique based on the Sounding Reference Signal (SRS). In real environments, however, user equipments (UE) are rarely set up to transmit this particular signal. The main original contribution of this thesis consists in a new TOA estimation method based on uplink transmission. In particular, we explore the possibility of performing radio localization exploiting the uplink Demodulation Reference Signal (DM-RS), which is always sent by UEs during data transmission. Real uplink transmissions are modeled in simulations and the performance of known algorithms like SAGE and IAA-APES are evaluated for TOA estimation. A new method to estimate the initial conditions of the SAGE algorithm is proposed and the estimation performance in uplink scenarios is evaluated. The analysis revealed that the proposed method outperforms the non-coherent initial conditions estimation proposed in the literature, when uplink transmission are used. Then, the benefits of our proposal are evaluated and the feasibility of TOA estimation exploiting the DM-RS is demonstrated by means of experiments using real DM-RS signals generated by an LTE module. A second original contribution is given by AOA estimation. In particular, the independence of AOA estimation with respect to uplink and downlink transmission is verified. According to this result, the performance of IAA-APES and SAGE in real-world AOA experiments is evaluated in the downlink scenarios. Based on the overall results, we conclude that the proposed radio localization method, exploiting the uplink Demodulation Reference Signal (DM-RS), can be extended also to joint TOA, AOA using SAGE, for hybrid localization techniques. We can also conclude that the proposed method can be easily extended to downlink transmission exploiting the cell specific reference signal (CRS)

Wireless indoor localisation within the 5G internet of radio light

This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University LondonNumerous applications can be enhanced by accurate and efficient indoor localisation using wireless sensor networks, however trade-offs often exist between these two parameters. In this thesis, realworld and simulation data is used to examine the hybrid millimeter wave and Visible Light Communications (VLC) architecture of the 5G Internet of Radio Light (IoRL) Horizon 2020 project. Consequently, relevant localisation challenges within Visible Light Positioning (VLP) and asynchronous sampling networks are identified, and more accurate and efficient solutions are developed. Currently, VLP relies strongly on the assumed Lambertian properties of light sources. However, in practice, not all lights are Lambertian. To support the widespread deployment of VLC technology in numerous environments, measurements from non-Lambertian sources are analysed to provide new insights into the limitations of existing VLP techniques. Subsequently, a novel VLP calibration technique is proposed, and results indicate a 59% accuracy improvement against existing methods. This solution enables high accuracy centimetre level VLP to be achieved with non- Lambertian sources. Asynchronous sampling of range-based measurements is known to impact localisation performance negatively. Various Asynchronous Sampling Localisation Techniques (ASLT) exist to mitigate these effects. While effective at improving positioning performance, the exact suitability of such solutions is not evident due to their additional processes, subsequent complexity, and increased costs. As such, extensive simulations are conducted to study the effectiveness of ASLT under variable sampling latencies, sensor measurement noise, and target trajectories. Findings highlight the computational demand of existing ASLT and motivate the development of a novel solution. The proposed Kalman Extrapolated Least Squares (KELS) method achieves optimal localisation performance with a significant energy reduction of over 50% when compared to current leading ASLT. The work in this thesis demonstrates both the capability for high performance VLP from non- Lambertian sources as well as the potential for energy efficient localisation for sequentially sampled range measurements.Horizon 202

Contributions to the security of cognitive radio networks

The increasing emergence of wireless applications along with the static spectrum allocation followed by regulatory bodies has led to a high inefficiency in spectrum usage, and the lack of spectrum for new services. In this context, Cognitive Radio (CR) technology has been proposed as a possible solution to reuse the spectrum being underutilized by licensed services. CRs are intelligent devices capable of sensing the medium and identifying those portions of the spectrum being unused. Based on their current perception of the environment and on that learned from past experiences, they can optimally tune themselves with regard to parameters such as frequency, coding and modulation, among others. Due to such properties, Cognitive Radio Networks (CRNs) can act as secondary users of the spectrum left unused by their legal owners or primary users, under the requirement of not interfering primary communications. The successful deployment of these networks relies on the proper design of mechanisms in order to efficiently detect spectrum holes, adapt to changing environment conditions and manage the available spectrum. Furthermore, the need for addressing security issues is evidenced by two facts. First, as for any other type of wireless network, the air is used as communications medium and can easily be accessed by attackers. On the other hand, the particular attributes of CRNs offer new opportunities to malicious users, ranging from providing wrong information on the radio environment to disrupting the cognitive mechanisms, which could severely undermine the operation of these networks. In this Ph.D thesis we have approached the challenge of securing Cognitive Radio Networks. Because CR technology is still evolving, to achieve this goal involves not only providing countermeasures for existing attacks but also to identify new potential threats and evaluate their impact on CRNs performance. The main contributions of this thesis can be summarized as follows. First, a critical study on the State of the Art in this area is presented. A qualitative analysis of those threats to CRNs already identified in the literature is provided, and the efficacy of existing countermeasures is discussed. Based on this work, a set of guidelines are designed in order to design a detection system for the main threats to CRNs. Besides, a high level description of the components of this system is provided, being it the second contribution of this thesis. The third contribution is the proposal of a new cross-layer attack to the Transmission Control Protocol (TCP) in CRNs. An analytical model of the impact of this attack on the throughput of TCP connections is derived, and a set of countermeasures in order to detect and mitigate the effect of such attack are proposed. One of the main threats to CRNs is the Primary User Emulation (PUE) attack. This attack prevents CRNs from using available portions of the spectrum and can even lead to a Denial of Service (DoS). In the fourth contribution of this the method is proposed in order to deal with such attack. The method relies on a set of time measures provided by the members of the network and allows estimating the position of an emitter. This estimation is then used to determine the legitimacy of a given transmission and detect PUE attacks. Cooperative methods are prone to be disrupted by malicious nodes reporting false data. This problem is addressed, in the context of cooperative location, in the fifth and last contribution of this thesis. A method based on Least Median Squares (LMS) fitting is proposed in order to detect forged measures and make the location process robust to them. The efficiency and accuracy of the proposed methodologies are demonstrated by means of simulation

Joint Communication and Positioning based on Channel Estimation

Mobile wireless communication systems have rapidly and globally become an integral part of everyday life and have brought forth the internet of things. With the evolution of mobile wireless communication systems, joint communication and positioning becomes increasingly important and enables a growing range of new applications. Humanity has already grown used to having access to multimedia data everywhere at every time and thereby employing all sorts of location-based services. Global navigation satellite systems can provide highly accurate positioning results whenever a line-of-sight path is available. Unfortunately, harsh physical environments are known to degrade the performance of existing systems. Therefore, ground-based systems can assist the existing position estimation gained by satellite systems. Determining positioning-relevant information from a unified signal structure designed for a ground-based joint communication and positioning system can either complement existing systems or substitute them. Such a system framework promises to enhance the existing systems by enabling a highly accurate and reliable positioning performance and increased coverage. Furthermore, the unified signal structure yields synergetic effects. In this thesis, I propose a channel estimation-based joint communication and positioning system that employs a virtual training matrix. This matrix consists of a relatively small training percentage, plus the detected communication data itself. Via a core semi- blind estimation approach, this iteratively includes the already detected data to accurately determine the positioning-relevant parameter, by mutually exchanging information between the communication part and the positioning part of the receiver. Synergy is created. I propose a generalized system framework, suitable to be used in conjunction with various communication system techniques. The most critical positioning-relevant parameter, the time-of-arrival, is part of a physical multipath parameter vector. Estimating the time-of-arrival, therefore, means solving a global, non-linear, multi-dimensional optimization problem. More precisely, it means solving the so-called inverse problem. I thoroughly assess various problem formulations and variations thereof, including several different measurements and estimation algorithms. A significant challenge, when it comes to solving the inverse problem to determine the positioning-relevant path parameters, is imposed by realistic multipath channels. Most parameter estimation algorithms have proven to perform well in moderate multipath environments. It is mathematically straightforward to optimize this performance in the sense that the number of observations has to exceed the number of parameters to be estimated. The typical parameter estimation problem, on the other hand, is based on channel estimates, and it assumes that so-called snapshot measurements are available. In the case of realistic channel models, however, the number of observations does not necessarily exceed the number of unknowns. In this thesis, I overcome this problem, proposing a method to reduce the problem dimensionality via joint model order selection and parameter estimation. Employing the approximated and estimated parameter covariance matrix inherently constrains the estimation problem’s model order selection to result in optimal parameter estimation performance and hence optimal positioning performance. To compare these results with the optimally achievable solution, I introduce a focused order-related lower bound in this thesis. Additionally, I use soft information as a weighting matrix to enhance the positioning algorithm positioning performance. For demonstrating the feasibility and the interplay of the proposed system components, I utilize a prototype system, based on multi-layer interleave division multiple access. This proposed system framework and the investigated techniques can be employed for multiple existing systems or build the basis for future joint communication and positioning systems. The assessed estimation algorithms are transferrable to all kinds of joint communication and positioning system designs. This thesis demonstrates their capability to, in principle, successfully cope with challenging estimation problems stemming from harsh physical environments