Preprint: Using RF-DNA Fingerprints To Classify OFDM Transmitters Under Rayleigh Fading Conditions

The Internet of Things (IoT) is a collection of Internet connected devices capable of interacting with the physical world and computer systems. It is estimated that the IoT will consist of approximately fifty billion devices by the year 2020. In addition to the sheer numbers, the need for IoT security is exacerbated by the fact that many of the edge devices employ weak to no encryption of the communication link. It has been estimated that almost 70% of IoT devices use no form of encryption. Previous research has suggested the use of Specific Emitter Identification (SEI), a physical layer technique, as a means of augmenting bit-level security mechanism such as encryption. The work presented here integrates a Nelder-Mead based approach for estimating the Rayleigh fading channel coefficients prior to the SEI approach known as RF-DNA fingerprinting. The performance of this estimator is assessed for degrading signal-to-noise ratio and compared with least square and minimum mean squared error channel estimators. Additionally, this work presents classification results using RF-DNA fingerprints that were extracted from received signals that have undergone Rayleigh fading channel correction using Minimum Mean Squared Error (MMSE) equalization. This work also performs radio discrimination using RF-DNA fingerprints generated from the normalized magnitude-squared and phase response of Gabor coefficients as well as two classifiers. Discrimination of four 802.11a Wi-Fi radios achieves an average percent correct classification of 90% or better for signal-to-noise ratios of 18 and 21 dB or greater using a Rayleigh fading channel comprised of two and five paths, respectively.Comment: 13 pages, 14 total figures/images, Currently under review by the IEEE Transactions on Information Forensics and Securit

Analysis and Compensation of Power Amplifier Distortions in Wireless Communication Systems

Wireless communication devices transmit message signals which should possess desirable power levels for quality transmission. Power amplifiers are devices in the wireless transmitters which increase the power of signals to the desired levels, but produce nonlinear distortions due to their saturation property, resulting in degradation of the quality of the transmitted signal. This thesis talks about the analysis and performance of communication systems in presence of power amplifier nonlinear distortions. First, the thesis studies the effects of power amplifier nonlinear distortions on communication signals and proposes a simplified design for identification and compensation of the distortions at the receiver end of a wireless communication system using a two-step pilot signal approach. Step one involves the estimation of the channel state information of the wireless channel and step two estimates the power amplifier parameters. Then, the estimated power amplifier parameters are used for transmitter identification with the help of a testing procedure proposed in this thesis. With the evolution of millimeter wave wireless communication systems today, study and analysis of these systems is the need of the hour. Thus, the second part of this thesis is extended to study the performance of millimeter wave wireless communication systems in presence of power amplifier nonlinear distortions and derives an analytical expression for evaluation of the symbol error probability for this system. The proposed analysis evaluates the performance of millimeter wave systems theoretically without the need of simulations, and is helpful in studying systems in the absence of actual hardware

Secure OFDM System Design for Wireless Communications

Wireless communications is widely employed in modern society and plays an increasingly important role in people\u27s daily life. The broadcast nature of radio propagation, however, causes wireless communications particularly vulnerable to malicious attacks, and leads to critical challenges in securing the wireless transmission. Motivated by the insufficiency of traditional approaches to secure wireless communications, physical layer security that is emerging as a complement to the traditional upper-layer security mechanisms is investigated in this dissertation. Five novel techniques toward the physical layer security of wireless communications are proposed. The first two techniques focus on the security risk assessment in wireless networks to enable a situation-awareness based transmission protection. The third and fourth techniques utilize wireless medium characteristics to enhance the built-in security of wireless communication systems, so as to prevent passive eavesdropping. The last technique provides an embedded confidential signaling link for secure transmitter-receiver interaction in OFDM systems

Novel Models and Algorithms Paving the Road towards RF Convergence

After decades of rapid evolution in electronics and signal processing, the technologies in communications, positioning, and sensing have achieved considerable progress. Our daily lives are fundamentally changed and substantially defined by the advancement in these technologies. However, the trend is challenged by a well-established fact that the spectrum resources, like other natural resources, are gradually becoming scarce. This thesis carries out research in the field of RF convergence, which is regarded as a mean to intelligently exploit spectrum resources, e.g., by finding novel methods of optimising and sharing tasks between communication, positioning, and sensing. The work has been done to closely explore opportunities for supporting the RF convergence. As a supplement for the electromagnetic waves propagation near the ground, ground-to-air channel models are first proposed and analysed, by incorporating the atmospheric effects when the altitude of aerial users is higher than 300 m. The status quos of techniques in communications, positioning, and sensing are separately reviewed, and our newly developments in each field are briefly introduced. For instance, we study the MIMO techniques for interference mitigation on aerial users; we construct the reflected echoes, i.e., the radar receiving, for the joint sensing and communications system. The availability of GNSS signals is of vital importance to the GNSS-enabled services, particularly the life-critical applications. To enhance the resilience of GNSS receivers, the RF fingerprinting based anti-spoofing techniques are also proposed and discussed. Such a guarantee on GNSS and ubiquitous GNSS services drive the utilisation of location information, also needed for communications, hence the proposal of a location-based beamforming algorithm. The superposition coding scheme, as an attempt of the waveform design, is also brought up for the joint sensing and communications. The RF convergence will come with many facets: the joint sensing and communications promotes an efficient use of frequency spectrum; the positioning-aided communications encourage the cooperation between systems; the availability of robust global positioning systems benefits the applications relying on the GNSS service

Orbital Navigation Using Resident Space Object Observations

With the population of Resident Space Objects (RSOs) in low earth orbit growing steadily year by year, there is an increasing challenge to track and map this population. While dedicated space and ground-based RSO detectors have done well, there has been an increasing amount of space-based detectors that assist in maintaining the RSO catalog. With continual RSO knowledge improvements, it may be possible to one day use RSO observations as a means of space-based navigation. This paper explores how this RSO information could one day be used in the attitude and orbit determination of the satellite. By leveraging the measurement parallax of nearby RSOs on the star tracker detector, the star tracker can be used to provide both orbit and attitude information to the navigation filter on-board the spacecraft, providing a useful backup to a standard GPS receiver. This paper presents preliminary work on a combined orbit / attitude Kalman filter that includes RSO observations from standard star trackers

Comunicações ópticas por câmera para sistemas de assistência à condução

Communications, whatever its type, is a pillar of our modern society. More specifically, communications by visible light, that show numerous advantages, from electromagnetic spectral efficiency and regulation freedom to energy saving (since it combine illumination and communication). As such, the automotive world is interested in this technology, in particularly, its application into the Intelligent Transport System (ITS). The objective of this work relies on the study and development of a demonstrator able to support VLC communication means in V2V (Vehicle to Vehicle) scenario, making use of the LED luminaries already implemented in nowadays cars. Since the outdoor implementation is one of the requirements, reception based in OCC (Optical Camera Communication) is a viable solution in this conditions. Also the signal processing/decoding is performed by a CNN (Convolutional Neural Network), this type of algorithm shows a huge decoding flexibility and resilience, which benefits the transmission system performance. All the project was done in collaboration with the integrated circuits systems group of Instituto de Telecomunicações de Aveiro and Exatronic Lda company, based in Aveiro and specialized in innovation and investigation (I+I), engineering and manufacturing of electronics.As comunicações, qualquer que seja o seu tipo, mostram-se como um pilar fundamental para a sociedade. Especificamente as comunicações por luz visível, que apresentam inúmeras vantagens, desde a eficiência espectral e mais liberdade de regulamentação, até à energética pois alia duas caracteristicas distintas (iluminação e comunicação) numa só. Como tal, o mundo automóvel apresenta-se como um dos posíveis interessados na aplicação desta tecnologia, mais propriamente a aplicação como parte integrante do sistema inteligente de transportes (ITS). Este trabalho tem como objectivo o estudo e desenvolvimento de um demonstrador capaz de estabelecer um link de comunicação V2V (Vehicle to vehicle) por meio da modulação da luz visivel emitida pelas iluminárias LED já equipadas actualmente nos veículos. Sendo a implementação exterior um dos requerimentos deste sistema, a rececção através de OCC (Optical Camera Communication) mostra-se assim uma solução viável. Assim como o processamento do sinal recebido, que é efectuado por meio de CNNs (Convolutional Neural Networks), que mostram flexibilidade e resiliência, o que benefecia a capacidade do sistema de transmissão. Todo o projecto foi realizado em colaboração com o grupo de circuitos integrados do Instituto de Telecomunicações de Aveiro e a empresa Exatronic Lda, sediada em Aveiro, e especializada em inovação, investigação (I+I), engenharia e produção de eletrónica.Mestrado em Engenharia Eletrónica e Telecomunicaçõe

Deep Learning-based Transmitter identification on the physical layer

An essential part of most wireless communications systems is the identification of a transmitter by a receiver. Being able to identify a transmitter at the physical layer gives context to the communication itself, but is also an important building block for more advanced techniques such as physical layer security. It can also be used to reduce overhea