Directional Antenna System-Based DoA/RSS Estimation, Localization and Tracking in Future Wireless Networks: Algorithms and Performance Analysis

Location information plays an important role in many emerging technologies such as robotics, autonomous vehicles, and augmented reality. Already now the majority of smartphone owners use their devices' localization capabilities for a broad range of location-based services. Currently, location information in smartphones is mostly obtained in a device-centric approach, where the device to be localized, here referred to as the target node (TN), estimates its own location using, for example, the global positioning system (GPS). However, TNs with wireless communication capabilities can be localized based on their transmitted signals by a third party. In particular, localization can be implemented as a functionality of a wireless network. Depending on the application area and implementation, this network-centric approach has several advantages compared to device-centric localization, such as reducing the energy consumption within the TNs, enabling localization of non-cooperative TNs, and making location information available in the network itself. Current generation wireless networks are already capable of coarse localization. However, these existing localization capabilities do not suffice for the challenging demands of future applications. The majority of approaches moreover does not exploit the fact that an increasing number of base stations (BSs) and user devices are equipped with directional antennas. However, directional antennas enable direction of arrival (DoA) estimation that can, in turn, serve as the basis for advanced localization and location tracking. In this thesis, we thus study the application of directional antennas for localization and location tracking in future generation wireless networks. The contributions of this thesis can be grouped into two topics.First, this thesis provides a detailed study of DoA/received signal strength (RSS) estimation and localization with a group of directional antennas herein denoted as sectorized antennas. This group of antennas is of particular interest as it encompasses a broad range of directional antennas that can be implemented with a single RF front-end. Thus, the hardware complexity of sectorized antennas is low in comparison to the conventionally used antenna arrays that require multiple transceiver branches. However, at the same time this means that DoA estimation with sectorized antennas has to be implemented in a fundamentally different way. In order to address these differences, the study of sectorized antennas in this thesis includes the derivation of Cramer-Rao bounds (CRBs) for DoA/RSS estimation and localization, the proposal of three different DoA/RSS estimators, as well as numerical and analytical performance evaluations of DoA/RSS estimation and localization using sectorized antennas.Second, this thesis deals with localization based on the fusion of DoA and RSS estimates as well as DoA and time of arrival (ToA) estimates. It is shown that the combination of these estimates can result in a much increased localization performance compared to a localization based on one of these estimates alone. For the localization based on DoA/RSS estimates, a mechanism explaining this improvement is revealed by means of a CRB analysis. Thereafter, DoA/RSS-based fusion is further studied using an extended Kalman filter (EKF) as an example location tracking algorithm. Finally, an EKF is proposed that tracks the location of a TN by fusing DoA and ToA estimates. Apart from a significantly improved tracking performance, this joint DoA/ToA-EKF moreover provides estimates for the TN device clock offset and is able to localize the TN in situations where a classical DoA-only EKF fails to provide a location estimate altogether.Overall, this thesis thus provides insights into benefits of localization and location tracking using directional antennas, accompanied by specific DoA/RSS estimation, localization and location tracking solutions, as well as design guidelines for implementing localization systems in future generation wireless networks

Cognitive relay nodes for airborne LTE emergency networks

This paper is proposing a novel concept of Cognitive Relay Node for intelligently improving the radio coverage of an airborne LTE emergency network, considering the scenarios outlined in the ABSOLUTE research project. The proposed network model was simulated comparing the different cases of deploying relay nodes to complement the coverage of an aerial LTE network. Simulation results of the proposed Cognitive Relay Nodes show significant performance improvement in terms of radio coverage quantified by the regional outage probability enhancement. Also, this paper is presenting the methodology and results of choosing the optimum aerial eNodeB altitude

An adaptive learning algorithm for spectrum sensing based on direction of arrival estimation in cognitive radio systems

In cognitive radio systems, estimating primary user direction of arrival (DOA) measurement is one of the key issues. In order to increase the probability detection multiple sensor antennas are used and they are analysed by using subspace-based technique. In this work, we considered wideband spectrum with sub channels and here each sub channel facilitated with a sensor for the estimation of DOA. In practical spectrum sensing process interference component also encounters in the sensing process. To avoid this interference level at output of receiver, we used an adaptive learning algorithm known as Normalised Least Absolute Mean Deviation (NLAMD) algorithm. Further to achieve better performance a bias compensator function is applied in weight coefficient updating process. Using this hybrid realization, the vacant spectrum can be sensed based on DOA estimation and number of vacant locations in each channel can be identified using maximum likelihood approach. In order to test at the diversified conditions different threshold parameters 0.1, 0.5, 1 are analysed.</p

Design and theoretical analysis of advanced power based positioning in RF system

Accurate locating and tracking of people and resources has become a fundamental requirement for many applications. The global navigation satellite systems (GNSS) is widely used. But its accuracy suffers from signal obstruction by buildings, multipath fading, and disruption due to jamming and spoof. Hence, it is required to supplement GPS with inertial sensors and indoor localization schemes that make use of WiFi APs or beacon nodes. In the GPS-challenging or fault scenario, radio-frequency (RF) infrastructure based localization schemes can be a fallback solution for robust navigation. For the indoor/outdoor transition scenario, we propose hypothesis test based fusion method to integrate multi-modal localization sensors. In the first paper, a ubiquitous tracking using motion and location sensor (UTMLS) is proposed. As a fallback approach, power-based schemes are cost-effective when compared with the existing ToA or AoA schemes. However, traditional power-based positioning methods suffer from low accuracy and are vulnerable to environmental fading. Also, the expected accuracy of power-based localization is not well understood but is needed to derive the hypothesis test for the fusion scheme. Hence, in paper 2-5, we focus on developing more accurate power-based localization schemes. The second paper improves the power-based range estimation accuracy by estimating the LoS component. The ranging error model in fading channel is derived. The third paper introduces the LoS-based positioning method with corresponding theoretical limits and error models. In the fourth and fifth paper, a novel antenna radiation-pattern-aware power-based positioning (ARPAP) system and power contour circle fitting (PCCF) algorithm are proposed to address antenna directivity effect on power-based localization. Overall, a complete LoS signal power based positioning system has been developed that can be included in the fusion scheme --Abstract, page iv

Practical Secrecy at the Physical Layer: Key Extraction Methods with Applications in Cognitive Radio

The broadcast nature of wireless communication imposes the risk of information leakage to adversarial or unauthorized receivers. Therefore, information security between intended users remains a challenging issue. Currently, wireless security relies on cryptographic techniques and protocols that lie at the upper layers of the wireless network. One main drawback of these existing techniques is the necessity of a complex key management scheme in the case of symmetric ciphers and high computational complexity in the case of asymmetric ciphers. On the other hand, physical layer security has attracted significant interest from the research community due to its potential to generate information-theoretic secure keys. In addition, since the vast majority of physical layer security techniques exploit the inherent randomness of the communication channel, key exchange is no longer mandatory. However, additive white Gaussian noise, interference, channel estimation errors and the fact that communicating transceivers employ different radio frequency (RF) chains are among the reasons that limit utilization of secret key generation (SKG) algorithms to high signal to noise ratio levels. The scope of this dissertation is to design novel secret key generation algorithms to overcome this main drawback. In particular, we design a channel based SKG algorithm that increases the dynamic range of the key generation system. In addition, we design an algorithm that exploits angle of arrival (AoA) as a common source of randomness to generate the secret key. Existing AoA estimation systems either have high hardware and computation complexities or low performance, which hinder their incorporation within the context of SKG. To overcome this challenge, we design a novel high performance yet simple and efficient AoA estimation system that fits the objective of collecting sequences of AoAs for SKG. Cognitive radio networks (CRNs) are designed to increase spectrum usage efficiency by allowing secondary users (SUs) to exploit spectrum slots that are unused by the spectrum owners, i.e., primary users (PUs). Hence, spectrum sensing (SS) is essential in any CRN. CRNs can work both in opportunistic (interweaved) as well as overlay and/or underlay (limited interference) fashions. CRNs typically operate at low SNR levels, particularly, to support overlay/underlay operations. Similar to other wireless networks, CRNs are susceptible to various physical layer security attacks including spectrum sensing data falsification and eavesdropping. In addition to the generalized SKG methods provided in this thesis and due to the peculiarity of CRNs, we further provide a specific method of SKG for CRNs. After studying, developing and implementing several SS techniques, we design an SKG algorithm that exploits SS data. Our algorithm does not interrupt the SS operation and does not require additional time to generate the secret key. Therefore, it is suitable for CRNs

Beam Selection and Discrete Power Allocation in Opportunistic Cognitive Radio Systems with Limited Feedback Using ESPAR Antennas

We consider an opportunistic cognitive radio (CR) system consisting of a primary user (PU), secondary transmitter (SUtx), and secondary receiver (SUrx), where SUtx is equipped with an electrically steerable parasitic array radiator (ESPAR) antenna with the capability of choosing one beam among M beams for sensing and communication, and there is a limited feedback channel from SUrx to SUtx. Taking a holistic approach, we develop a framework for integrated sector-based spectrum sensing and sector-based data communication. Upon sensing the channel busy, SUtx determines the beam corresponding to PU's orientation. Upon sensing the channel idle, SUtx transmits data to SUrx, using the selected beam corresponding to the strongest channel between SUtx and SUrx. We formulate a constrained optimization problem, where SUtx-SUrx link ergodic capacity is maximized, subject to average transmit and interference power constraints, and the optimization variables are sensing duration, thresholds of channel quantizer at SUrx, and transmit power levels at SUtx. Since this problem is non-convex we develop a suboptimal computationally efficient iterative algorithm to find the solution. Our results demonstrate that our CR system yields a significantly higher capacity, and lower outage and symbol error probabilities, compared with a CR system that its SUtx has an omni-directional antenna.Comment: This paper has been submitted to IEEE Transactions on Cognitive Communications and Networkin