Mitigation of multipath fading in indoor radiometric fingerprinting systems

Wireless sensor network technology offers endless possibilities for innovative solutions for different security and intrusion detection and recognition applications. By distribut- ing multiple clusters of preconfigured wireless sensor network detection nodes, a widely monitored area can be consistently checked for intruders. These systems are simple, easy to install and reliable in detecting intruders automatically. This paper presents the utiliza- tion of a wireless sensor network as a non-invasive human identification system for smart homes and security applications. The proposed scheme analyzes the effect of individuals moving into a monitored area, where the 2.4 GHz wireless sensor network has been in- stalled. It is imperative to comprehend the critical impact caused by different human bod- ies on multiple readings of Received Signal Strength Indicator collected at different levels for individuals at the same recording position. Multiple experiments were performed by utilizing the wireless sensor network nodes on different individuals at different positions. The paper particularly studies the effect of filtration and change of filtering parameters used to mitigate the multipath effect on the accuracy and detection capacity of the pre- sented IEEE802.15.4-based radiometric human identification scheme

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

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

Infrared ranging in multipath environments for indoor localization of mobile targets

Esta tesis aborda el problema de la medida de diferencias de distancia mediante señales ópticas afectadas por multicamino, aplicada a la localización de agentes móviles en espacios interiores. Los avances en robótica, entornos inteligentes y vehículos autónomos han creado un campo de aplicación específico para la localización en interiores, cuyos requerimientos de precisión (en el rango de los cm) son muy superiores a los demandados por las aplicaciones de localización orientadas a personas, en cuyo contexto se han desarrollado la mayor parte de las alternativas tecnológicas. La investigación con métodos de geometría proyectiva basados en cámaras y de multilateración basados en medida de distancia con señales de radiofrecuencia de banda ancha, de ultrasonido y ópticas han demostrado un rendimiento potencial adecuado para cubrir estos requerimientos. Sin embargo, todas estas alternativas, aún en fase de investigación, presentan dificultades que limitan su aplicación práctica. En el caso de los sistemas ópticos, escasamente estudiados en este contexto, los trabajos previos se han basado en medidas de diferencia de fase de llegada de señales infrarrojas moduladas sinusoidalmente en intensidad. Una infraestructura centralizada computa medidas diferenciales, entre receptores fijos, de la señal emitida desde el móvil a posicionar, y calcula la posición del móvil mediante trilateración hiperbólica a partir de éstas. Estas investigaciones demostraron que se pueden alcanzar precisiones de pocos centímetros; sin embargo, las interferencias por multicamino debidas a la reflexión de la señal óptica en superficies del entorno pueden degradar esta precisión hasta las decenas de centímetros dependiendo de las características del espacio. Así pues, el efecto del multicamino es actualmente la principal fuente de error en esta tecnología, y por tanto, la principal barrera a superar para su implementación en situaciones reales. En esta tesis se propone y analiza un sistema de medida con señales ópticas que permite obtener estimaciones de diferencias de distancia precisas reduciendo el efecto crítico del multicamino. El sistema propuesto introduce una modulación con secuencias de ruido pseudoaleatorio sobre la modulación sinusoidal típicamente usada para medida de fase por onda continua, y aprovecha las propiedades de ensanchamiento en frecuencia de estas secuencias para reducir el efecto del multicamino. El sistema, que realiza una doble estimación de tiempo y fase de llegada, está compuesto por una etapa de sincronización que posibilita la demodulación parcialmente coherente de la señal recibida, seguida de un medidor diferencial de fase sobre las componentes desensanchadas tras la demodulación. Las condiciones de multicamino óptico típicas en espacios interiores, con una componente de camino directo claramente dominante, permiten que el proceso de demodulación recupere más potencia del camino directo que del resto de contribuciones, reduciendo el efecto del multicamino en la estimación final. Los resultados obtenidos demuestran que la aplicación del método propuesto permitiría realizar posicionamiento a partir de señales ópticas con el rendimiento adecuando para aplicaciones de robótica y guiado de vehículos en espacios interiores; además, el progresivo aumento de la potencia y el ancho de banda de los dispositivos optoelectrónicos disponibles permite esperar un incremento considerable de las prestaciones de la propuesta en los próximos años

Wireless communication, sensing, and REM: A security perspective

The diverse requirements of next-generation communication systems necessitate awareness, flexibility, and intelligence as essential building blocks of future wireless networks. The awareness can be obtained from the radio signals in the environment using wireless sensing and radio environment mapping (REM) methods. This is, however, accompanied by threats such as eavesdropping, manipulation, and disruption posed by malicious attackers. To this end, this work analyzes the wireless sensing and radio environment awareness mechanisms, highlighting their vulnerabilities and provides solutions for mitigating them. As an example, the different threats to REM and its consequences in a vehicular communication scenario are described. Furthermore, the use of REM for securing communications is discussed and future directions regarding sensing/REM security are highlighted

Indoor Positioning and Navigation

In recent years, rapid development in robotics, mobile, and communication technologies has encouraged many studies in the field of localization and navigation in indoor environments. An accurate localization system that can operate in an indoor environment has considerable practical value, because it can be built into autonomous mobile systems or a personal navigation system on a smartphone for guiding people through airports, shopping malls, museums and other public institutions, etc. Such a system would be particularly useful for blind people. Modern smartphones are equipped with numerous sensors (such as inertial sensors, cameras, and barometers) and communication modules (such as WiFi, Bluetooth, NFC, LTE/5G, and UWB capabilities), which enable the implementation of various localization algorithms, namely, visual localization, inertial navigation system, and radio localization. For the mapping of indoor environments and localization of autonomous mobile sysems, LIDAR sensors are also frequently used in addition to smartphone sensors. Visual localization and inertial navigation systems are sensitive to external disturbances; therefore, sensor fusion approaches can be used for the implementation of robust localization algorithms. These have to be optimized in order to be computationally efficient, which is essential for real-time processing and low energy consumption on a smartphone or robot

Wireless Device Authentication Techniques Using Physical-Layer Device Fingerprint

Due to the open nature of the radio signal propagation medium, wireless communication is inherently more vulnerable to various attacks than wired communication. Consequently, communication security is always one of the critical concerns in wireless networks. Given that the sophisticated adversaries may cover up their malicious behaviors through impersonation of legitimate devices, reliable wireless authentication is becoming indispensable to prevent such impersonation-based attacks through verification of the claimed identities of wireless devices. Conventional wireless authentication is achieved above the physical layer using upper-layer identities and key-based cryptography. As a result, user authenticity can even be validated for the malicious attackers using compromised security key. Recently, many studies have proven that wireless devices can be authenticated by exploiting unique physical-layer characteristics. Compared to the key-based approach, the possession of such physical-layer characteristics is directly associated with the transceiver\u27s unique radio-frequency hardware and corresponding communication environment, which are extremely difficult to forge in practice. However, the reliability of physical-layer authentication is not always high enough. Due to the popularity of cooperative communications, effective implementation of physical-layer authentication in wireless relay systems is urgently needed. On the other hand, the integration with existing upper-layer authentication protocols still has many challenges, e.g., end-to-end authentication. This dissertation is motivated to develop novel physical-layer authentication techniques in addressing the aforementioned challenges. In achieving enhanced wireless authentication, we first specifically identify the technique challenges in authenticating cooperative amplify-and-forward (AF) relay. Since AF relay only works at the physical layer, all of the existing upper-layer authentication protocols are ineffective in identifying AF relay nodes. To solve this problem, a novel device fingerprint of AF relay consisting of wireless channel gains and in-phase and quadrature imbalances (IQI) is proposed. Using this device fingerprint, satisfactory authentication accuracy is achieved when the signal-to-noise ratio is high enough. Besides, the optimal AF relay identification system is studied to maximize the performance of identifying multiple AF relays in the low signal-to-noise regime and small IQI. The optimal signals for quadrature amplitude modulation and phase shift keying modulations are derived to defend against the repeated access attempts made by some attackers with specific IQIs. Exploring effective authentication enhancement technique is another key objective of this dissertation. Due to the fast variation of channel-based fingerprints as well as the limited range of device-specific fingerprints, the performance of physical-layer authentication is not always reliable. In light of this, the physical-layer authentication is enhanced in two aspects. On the one hand, the device fingerprinting can be strengthened by considering multiple characteristics. The proper characteristics selection strategy, measurement method and optimal weighted combination of the selected characteristics are investigated. On the other hand, the accuracy of fingerprint estimation and differentiation can be improved by exploiting diversity techniques. To be specific, cooperative diversity in the form of involving multiple collaborative receivers is used in differentiating both frequency-dependent and frequency-independent device fingerprints. As a typical combining method of the space diversity techniques, the maximal-ratio combining is also applied in the receiver side to combat the channel degeneration effect and increase the fingerprint-to-noise ratio. Given the inherent weaknesses of the widely utilized upper-layer authentication protocols, it is straightforward to consider physical-layer authentication as an effective complement to reinforce existing authentication schemes. To this end, a cross-layer authentication is designed to seamlessly integrate the physical-layer authentication with existing infrastructures and protocols. The specific problems such as physical-layer key generation as well as the end-to-end authentication in networks are investigated. In addition, the authentication complexity reduction is also studied. Through prediction, pre-sharing and reusing the physical-layer information, the authentication processing time can be significantly shortened

Spectrum sensing for cognitive radio and radar systems

The use of the radio frequency spectrum is increasing at a rapid rate. Reliable and efficient operation in a crowded radio spectrum requires innovative solutions and techniques. Future wireless communication and radar systems should be aware of their surrounding radio environment in order to have the ability to adapt their operation to the effective situation. Spectrum sensing techniques such as detection, waveform recognition, and specific emitter identification are key sources of information for characterizing the surrounding radio environment and extracting valuable information, and consequently adjusting transceiver parameters for facilitating flexible, efficient, and reliable operation. In this thesis, spectrum sensing algorithms for cognitive radios and radar intercept receivers are proposed. Single-user and collaborative cyclostationarity-based detection algorithms are proposed: Multicycle detectors and robust nonparametric spatial sign cyclic correlation based fixed sample size and sequential detectors are proposed. Asymptotic distributions of the test statistics under the null hypothesis are established. A censoring scheme in which only informative test statistics are transmitted to the fusion center is proposed for collaborative detection. The proposed detectors and methods have the following benefits: employing cyclostationarity enables distinction among different systems, collaboration mitigates the effects of shadowing and multipath fading, using multiple strong cyclic frequencies improves the performance, robust detection provides reliable performance in heavy-tailed non-Gaussian noise, sequential detection reduces the average detection time, and censoring improves energy efficiency. In addition, a radar waveform recognition system for classifying common pulse compression waveforms is developed. The proposed supervised classification system classifies an intercepted radar pulse to one of eight different classes based on the pulse compression waveform: linear frequency modulation, Costas frequency codes, binary codes, as well as Frank, P1, P2, P3, and P4 polyphase codes. A robust M-estimation based method for radar emitter identification is proposed as well. A common modulation profile from a group of intercepted pulses is estimated and used for identifying the radar emitter. The M-estimation based approach provides robustness against preprocessing errors and deviations from the assumed noise model