Waveform-Defined Security: A Low-Cost Framework for Secure Communications

Communication security could be enhanced at physical layer but at the cost of complex algorithms and redundant hardware, which would render traditional physical layer security (PLS) techniques unsuitable for use with resource-constrained communication systems. This work investigates a waveform-defined security (WDS) framework, which differs fundamentally from traditional PLS techniques used in today’s systems. The framework is not dependent on channel conditions such as signal power advantage and channel state information (CSI). Therefore, the framework is more reliable than channel dependent beamforming and artificial noise (AN) techniques. In addition, the framework is more than just increasing the cost of eavesdropping. By intentionally tuning waveform patterns to weaken signal feature diversity and enhance feature similarity, eavesdroppers will not be able to identify correctly signal formats. The wrong classification of signal formats would result in subsequent detection errors even when an eavesdropper uses brute-force detection techniques. To get a robust WDS framework, three impact factors, namely training data feature, oversampling factor and bandwidth compression factor (BCF) offset, are investigated. An optimal WDS waveform pattern is obtained at the end after a joint study of the three factors. To ensure a valid eavesdropping model, artificial intelligence (AI) dependent signal classifiers are designed followed by optimal performance achievable signal detectors. To show the compatibility in available communication systems, the WDS framework is successfully integrated in IEEE 802.11a with nearly no adding computational complexity. Finally, a low-cost software-defined radio (SDR) experiment is designed to verify the feasibility of the WDS framework in resource-constrained communications

Diversity performance of off-body MB-OFDM UWB-MIMO

This paper introduces a novel formalism to improve the performance of an off-body system by deploying multiple ultra wideband (UWB) antennas, positioned strategically on the body. A methodology is presented for determining the optimal positions of UWB antennas on the body, necessary to provide a reliable multiband orthogonal frequency division multiplexing (MB-OFDM) UWB diversity antenna system operating in the Federal Communications Commission frequency band between 3.1 and 10.6 GHz. By evaluating the diversity metric, using simulation and measurement data, it is shown that the performance of such a system is stable throughout the entire investigated frequency band for both indoor and outdoor environments. There is a good agreement between the simulated and measured diversity values with a deviation of less than 9%. Therefore, the proposed technique optimizes the antennas' positions for maximum diversity performance within a very broad frequency band, independent of the used wireless communication standard. Thus, the obtained diversity system might be used in any kind of wireless communication link within that frequency band, e.g., UWB-OFDM, UWBMB-OFDM, UWB, or even narrowband transmission

Algorithm-Architecture Co-Design for Digital Front-Ends in Mobile Receivers

The methodology behind this work has been to use the concept of algorithm-hardware co-design to achieve efficient solutions related to the digital front-end in mobile receivers. It has been shown that, by looking at algorithms and hardware architectures together, more efficient solutions can be found; i.e., efficient with respect to some design measure. In this thesis the main focus have been placed on two such parameters; first reduced complexity algorithms to lower energy consumptions at limited performance degradation, secondly to handle the increasing number of wireless standards that preferably should run on the same hardware platform. To be able to perform this task it is crucial to understand both sides of the table, i.e., both algorithms and concepts for wireless communication as well as the implications arising on the hardware architecture. It is easier to handle the high complexity by separating those disciplines in a way of layered abstraction. However, this representation is imperfect, since many interconnected "details" belonging to different layers are lost in the attempt of handling the complexity. This results in poor implementations and the design of mobile terminals is no exception. Wireless communication standards are often designed based on mathematical algorithms with theoretical boundaries, with few considerations to actual implementation constraints such as, energy consumption, silicon area, etc. This thesis does not try to remove the layer abstraction model, given its undeniable advantages, but rather uses those cross-layer "details" that went missing during the abstraction. This is done in three manners: In the first part, the cross-layer optimization is carried out from the algorithm perspective. Important circuit design parameters, such as quantization are taken into consideration when designing the algorithm for OFDM symbol timing, CFO, and SNR estimation with a single bit, namely, the Sign-Bit. Proof-of-concept circuits were fabricated and showed high potential for low-end receivers. In the second part, the cross-layer optimization is accomplished from the opposite side, i.e., the hardware-architectural side. A SDR architecture is known for its flexibility and scalability over many applications. In this work a filtering application is mapped into software instructions in the SDR architecture in order to make filtering-specific modules redundant, and thus, save silicon area. In the third and last part, the optimization is done from an intermediate point within the algorithm-architecture spectrum. Here, a heterogeneous architecture with a combination of highly efficient and highly flexible modules is used to accomplish initial synchronization in at least two concurrent OFDM standards. A demonstrator was build capable of performing synchronization in any two standards, including LTE, WiFi, and DVB-H

Design and analysis of multi-element antenna systems and agile radiofrequency frontends for automotive applications

Vehicular connectivity serves as one of the major enabling technologies for current applications like driver assistance, safety and infotainment as well as upcoming features like highly automated vehicles - all of which having certain quality of service requirements, e. g. datarate or reliability. This work focuses on vehicular integration of multiple-input-multiple-output (MIMO) capable multielement antenna systems and frequency-agile radio frequency (RF) front ends to cover current and upcoming connectivity needs. It is divided in four major parts. For each part, mostly physical layer effects are analyzed (any performance lost on physical layer, cannot be compensated in higher layers), sensitivities are identified and novel concepts are introduced based on the status-quo findings.Fahrzeugvernetzung dient als eine der wesentlichsten Befähigungstechnologien für moderne Fahrerassistenzsysteme und zukünftig auch hochautomatisiertes Fahren. Sowohl die heutigen als auch zukünftige Anwendungen haben besondere Dienstgüteanforderungen, z.B. in Bezug auf die Datenrate oder Verlässlichkeit. Im Rahmen dieser Arbeit wird die Integration von Mehrantennensystemen für MIMO-Funkanwendungen (MIMO: engl. Multiple Input Multiple Output) sowie von frequenzagilen Hochfrequenzfrontends im Fahrzeugumfeld untersucht, um so eine technische Grundlage für zukünftige Anforderungen an die automobile Vernetzung anbieten zu können. Die dabei gewonnenen Erkenntnisse lassen sich in vier Teile gliedern. Grundsätzlich konzentrieren sich die Untersuchungen vorrangig auf die physikalische Ebene. Auf Basis des aktuellen Status Quo werden Sensitivitäten herausgearbeitet, neue Konzepte hergeleitet und entwickelt

Interference analysis of high frequency power line communications

Abstract. In power line communications, the existing in-house or in-office power distribution network can be used as a communications channel. Current broadband power line communication systems in the market deploy frequency range up to 86 MHz with transmission speeds up to 1 Gb/s. To increase the capacity even further, an extension of the frequency range above 100 MHz has been proposed in the published literature. This thesis presents an empirical study of radiated interference of high frequency broadband power line communications. Utilization of high frequencies for power line communications will cause unwanted radio interference which needs to be treated with caution. The preliminary results obtained in this work show how the components and structures of a power grid segment will contribute to the overall interference radiation when frequencies above 100 MHz are used for power line communication. The results indicate that the peak levels of radiated interference from a typical cabling in in-house or in-office power line networks reach their maximum on frequencies near 300 MHz and remain on a relatively same level on above. The peak levels are approximately 13 dB above the EN 55022 limit in the 230–1000 MHz frequency range with an injected power spectral density of -80 dBm/Hz. The results will provide valuable information when designing and making more comprehensive measurement campaigns for deciding on the national transmission levels for power line communications in UHF and higher frequencies.Korkeataajuisen sähköverkkotiedonsiirron aiheuttama säteily. Tiivistelmä. Sähköverkkotiedonsiirrossa hyödynnetään olemassa olevaa sähköverkkoa tiedonsiirtokanavana. Tällä hetkellä käytössä olevat sähköverkkotiedonsiirron standardit käyttävät taajuuksia 86 MHz:iin asti. Saavutettavat tiedonsiirtonopeudet yltävät 1 Gb/s asti. Kapasiteetin kasvattamiseksi on julkaistussa kirjallisuudessa esitetty taajuusalueen laajentamista yli 100 MHz:n taajuuksille. Tässä diplomityössä esitetään empiirinen tutkimus korkeataajuisen sähköverkkotiedonsiirron aiheuttamasta säteilystä. Korkeiden taajuuksien käyttö sähköverkkotiedonsiirrossa aiheuttaa haitallista säteilyä, joka täytyy ottaa huomioon ennen kuin taajuusaluetta voidaan laajentaa. Työssä saavutetut tulokset osoittavat kuinka sähköverkon eri komponentit vaikuttavat kokonaissäteilyyn kun yli 100 MHz:n taajuuksia käytetään sähköverkkotiedonsiirrossa. Tulokset osoittavat että tyypillisen talon tai toimistorakennuksen sähköverkossa siirretyn korkeataajuisien signaalin vuotama säteily saavuttaa maksimitasonsa 300 MHz:n taajuuteen mennessä ja ei kasva sitä korkeammilla taajuuksilla. Säteilyn maksimitasot ovat noin 13 dB EN55022 standardin rajojen yläpuolella taajuuksilla 230–1000 MHz kun sähköverkkoon syötetyn signaalin tehollinen tehotiheys on -80 dBm/Hz. Tuloksia voidaan käyttää hyödyksi laajempia mittauskampanjoita suoritettaessa kansallisten tehorajoitusten päättämiseksi kun UHF ja sitä korkeampia taajuuksia käytetään sähköverkkotiedonsiirrossa

Thirty Years of Machine Learning: The Road to Pareto-Optimal Wireless Networks

Future wireless networks have a substantial potential in terms of supporting a broad range of complex compelling applications both in military and civilian fields, where the users are able to enjoy high-rate, low-latency, low-cost and reliable information services. Achieving this ambitious goal requires new radio techniques for adaptive learning and intelligent decision making because of the complex heterogeneous nature of the network structures and wireless services. Machine learning (ML) algorithms have great success in supporting big data analytics, efficient parameter estimation and interactive decision making. Hence, in this article, we review the thirty-year history of ML by elaborating on supervised learning, unsupervised learning, reinforcement learning and deep learning. Furthermore, we investigate their employment in the compelling applications of wireless networks, including heterogeneous networks (HetNets), cognitive radios (CR), Internet of things (IoT), machine to machine networks (M2M), and so on. This article aims for assisting the readers in clarifying the motivation and methodology of the various ML algorithms, so as to invoke them for hitherto unexplored services as well as scenarios of future wireless networks.Comment: 46 pages, 22 fig

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

How Well Sensing Integrates with Communications in MmWave Wi-Fi?

The development of integrated sensing and communication (ISAC) systems has recently gained interest for its ability to offer a variety of services including resources sharing and new applications, for example, localization, tracking, and health care related. While the sensing capabilities are offered through many technologies, rending to their wide deployments and the high frequency spectrum they provide and high range resolution, its accessibility through the Wi-Fi networks IEEE 802.11ad and 802.11ay has been getting the interest of research and industry. Even though there is a dedicated standardization body, namely the 802.11bf task group, working on enhancing the Wi-Fi sensing performance, investigations are needed to evaluate the effectiveness of various sensing techniques. In this project, we, in addition to surveying related literature, we evaluate the sensing performance of the millimeter wave (mmWave) Wi-Fi systems by simulating a scenario of a human target using Matlab simulation tools. In this analysis, we processed channel estimation data using the short time Fourier transform (STFT). Furthermore, using a channel variation threshold method, we evaluated the performance while reducing feedback. Our findings indicate that using STFT window overlap can provide good tracking results, and that the reduction in feedback measurements using 0.05 and 0.1 threshold levels reduces feedback measurements by 48% and 77%, respectively, without significantly degrading performance.Comment: arXiv admin note: substantial text overlap with arXiv:2207.04859 by other author