Dirty RF Signal Processing for Mitigation of Receiver Front-end Non-linearity

Moderne drahtlose Kommunikationssysteme stellen hohe und teilweise gegensätzliche Anforderungen an die Hardware der Funkmodule, wie z.B. niedriger Energieverbrauch, große Bandbreite und hohe Linearität. Die Gewährleistung einer ausreichenden Linearität ist, neben anderen analogen Parametern, eine Herausforderung im praktischen Design der Funkmodule. Der Fokus der Dissertation liegt auf breitbandigen HF-Frontends für Software-konfigurierbare Funkmodule, die seit einigen Jahren kommerziell verfügbar sind. Die praktischen Herausforderungen und Grenzen solcher flexiblen Funkmodule offenbaren sich vor allem im realen Experiment. Eines der Hauptprobleme ist die Sicherstellung einer ausreichenden analogen Performanz über einen weiten Frequenzbereich. Aus einer Vielzahl an analogen Störeffekten behandelt die Arbeit die Analyse und Minderung von Nichtlinearitäten in Empfängern mit direkt-umsetzender Architektur. Im Vordergrund stehen dabei Signalverarbeitungsstrategien zur Minderung nichtlinear verursachter Interferenz - ein Algorithmus, der besser unter "Dirty RF"-Techniken bekannt ist. Ein digitales Verfahren nach der Vorwärtskopplung wird durch intensive Simulationen, Messungen und Implementierung in realer Hardware verifiziert. Um die Lücken zwischen Theorie und praktischer Anwendbarkeit zu schließen und das Verfahren in reale Funkmodule zu integrieren, werden verschiedene Untersuchungen durchgeführt. Hierzu wird ein erweitertes Verhaltensmodell entwickelt, das die Struktur direkt-umsetzender Empfänger am besten nachbildet und damit alle Verzerrungen im HF- und Basisband erfasst. Darüber hinaus wird die Leistungsfähigkeit des Algorithmus unter realen Funkkanal-Bedingungen untersucht. Zusätzlich folgt die Vorstellung einer ressourceneffizienten Echtzeit-Implementierung des Verfahrens auf einem FPGA. Abschließend diskutiert die Arbeit verschiedene Anwendungsfelder, darunter spektrales Sensing, robuster GSM-Empfang und GSM-basiertes Passivradar. Es wird gezeigt, dass nichtlineare Verzerrungen erfolgreich in der digitalen Domäne gemindert werden können, wodurch die Bitfehlerrate gestörter modulierter Signale sinkt und der Anteil nichtlinear verursachter Interferenz minimiert wird. Schließlich kann durch das Verfahren die effektive Linearität des HF-Frontends stark erhöht werden. Damit wird der zuverlässige Betrieb eines einfachen Funkmoduls unter dem Einfluss der Empfängernichtlinearität möglich. Aufgrund des flexiblen Designs ist der Algorithmus für breitbandige Empfänger universal einsetzbar und ist nicht auf Software-konfigurierbare Funkmodule beschränkt.Today's wireless communication systems place high requirements on the radio's hardware that are largely mutually exclusive, such as low power consumption, wide bandwidth, and high linearity. Achieving a sufficient linearity, among other analogue characteristics, is a challenging issue in practical transceiver design. The focus of this thesis is on wideband receiver RF front-ends for software defined radio technology, which became commercially available in the recent years. Practical challenges and limitations are being revealed in real-world experiments with these radios. One of the main problems is to ensure a sufficient RF performance of the front-end over a wide bandwidth. The thesis covers the analysis and mitigation of receiver non-linearity of typical direct-conversion receiver architectures, among other RF impairments. The main focus is on DSP-based algorithms for mitigating non-linearly induced interference, an approach also known as "Dirty RF" signal processing techniques. The conceived digital feedforward mitigation algorithm is verified through extensive simulations, RF measurements, and implementation in real hardware. Various studies are carried out that bridge the gap between theory and practical applicability of this approach, especially with the aim of integrating that technique into real devices. To this end, an advanced baseband behavioural model is developed that matches to direct-conversion receiver architectures as close as possible, and thus considers all generated distortions at RF and baseband. In addition, the algorithm's performance is verified under challenging fading conditions. Moreover, the thesis presents a resource-efficient real-time implementation of the proposed solution on an FPGA. Finally, different use cases are covered in the thesis that includes spectrum monitoring or sensing, GSM downlink reception, and GSM-based passive radar. It is shown that non-linear distortions can be successfully mitigated at system level in the digital domain, thereby decreasing the bit error rate of distorted modulated signals and reducing the amount of non-linearly induced interference. Finally, the effective linearity of the front-end is increased substantially. Thus, the proper operation of a low-cost radio under presence of receiver non-linearity is possible. Due to the flexible design, the algorithm is generally applicable for wideband receivers and is not restricted to software defined radios

DSP-based mitigation of RF front-end non-linearity in cognitive wideband receivers

Software defined radios are increasingly used in modern communication systems, especially in cognitive radio. Since this technology has been commercially available, more and more practical deployments are emerging and its challenges and realistic limitations are being revealed. One of the main problems is the RF performance of the front-end over a wide bandwidth. This paper presents an analysis and mitigation of RF impairments in wideband front-ends for software defined radios, focussing on non-linear distortions in the receiver. We discuss the effects of non-linear distortions upon spectrum sensing in cognitive radio and analyse the performance of a typical wideband software-defined receiver. Digital signal processing techniques are used to alleviate non-linear distortions in the baseband signal. A feed-forward mitigation algorithm with an adaptive filter is implemented and applied to real measurement data. The results obtained show that distortions can be suppressed significantly and thus increasing the reliability of spectrum sensing

Implementation of DSP-based algorithms on USRP for mitigating non-linear distortions in the receiver

In recent years, software-defined radio (SDR) has attracted increasingly more attention in regards to modern communication systems. The concept of SDR defines a radio device that is capable of flexibly reconfiguring its radio interface by software. This opens multiple fields of application and makes SDR an enormously adjustable and versatile radio technology. However, RF impairments induced by cheap and simple RF front-ends turn out to be a significant limitation in practice. Non-linear distortions emerge from non-linear components of the direct down-conversion chain that are driven into their saturation level. This is a result of a finite linearity and limited dynamic range of the RF frontend. The focus of this thesis are non-linear distortions in wideband receivers and a mitigation of them by means of digital signal processing. The idea is to artificially regenerate the non-linear distortions in the digital domain by applying a memoryless, polynomial model. An adaptive filter adjusts these reference distortions in their magnitude and phase and subtracts them from the distorted signal. A hardware implementation of a mitigation algorithm on a typical SDR-platform is presented. No prior implementation of this pure-digital approach is known. An implementation design flow is described following a top-down approach, starting from a fixed-point high-level implementation and ending up with a low-level hardware description language implementation. Both high-level and low-level simulations help to validate and evaluate the implementation. In conclusion, the implementation of the mitigation algorithm is a sophisticated mitigation technique for cleaning a down-converted baseband spectrum of non-linear distortions in real-time. Therefore, the effective linearity of the RF front-end is increased. This may lead to a significant improvement in the bit error rate performance of cleansed modulated signals, as well as to an enhanced sensing reliability in the context of cognitive radio.Zusammenfassung: In den letzten Jahren sorgte Software-Defined Radio (SDR) in Bezug auf moderne Kommunikationssysteme für immer größere Aufmerksamkeit. Das Konzept von SDR bezeichnet ein Funkgerät, das in der Lage ist, seine Funkschnittstelle durch Software flexibel zu rekonfigurieren. Dies ermöglicht eine Vielzahl von Anwendungsmöglichkeiten und macht SDR zu einer enorm anpassungsfähigen und vielseitigen Funktechnologie. Allerdings stellen im HF-Frontend ausgelöste Störungen in der Praxis eine erhebliche Einschränkung dar. In direkt umsetzenden Empfängerstrukturen entstehen durch nichtlineare Komponenten, die in ihren Sättigungsbereich getrieben werden, nichtlineare Verzerrungen. Das ist ein Ergebnis der begrenzten Linearität und des Dynamikbereich des HF-Frontends eingeschränkt sind. Der Fokus der Arbeit liegt auf nichtlinearen Verzerrungen in breitbandigen Empfängern und deren Minderung mit Hilfe von digitaler Signalverarbeitung. Die Idee ist, die nichtlinearen Verzerrungen im digitalen Bereich auf Basis eines gedächtnislosen, Polynom-Modells zu regenerieren. Ein adaptives Filter passt dabei den Betrag der nichtlinearen Referenzverzerrungen an und subtrahiert diese vom verzerrten Signal. In der Arbeit wird eine Hardwareimplementierung eines Störungsminderungsalgorithmus auf einer typischen SDR Plattform vorgestellt. Bisher ist keine Implementierung des rein-digitalen Ansatzes bekannt. Der Implementierungsablauf beschreibt anhand eines Top-Bottom-Ansatzes, wie der Algorithmus zuerst in einer Festpunkt High-Level Realisierung und schließlich in einer Low-Level Implementierung mit einer Hardwarebeschreibungssprache umgesetzt wird. Sowohl High-Level als auch Low-Level Simulationen unterstützen dabei die Validierung und Bewertung der Implementierung. Die Implementierung des Abschwächungsalgorithmus stellt schließlich eine ausgefeilte Methode dar, um ein heruntergeschmischtes Basisbandspektrum in Echtzeit von nichtlinearen Verzerrungen zu befreien. Demzufolge wird die effektive Linearität des HF-Frontends erhöht. Dies kann zu einer erheblichen Verbesserung der Bitfehlerrate von modulierten Signalen führen sowie die Zuverlässigkeit des Sensings in Bezug auf kognitiven Funk steigern.Ilmenau, Techn. Univ., Masterarbeit, 201

Implementation and Analysis of Spectral Subtraction and Signal Separation in Deterministic Wide-Band Anti-Jamming Scenarios

With the increasing volume of wireless traffic that military operations require, the likelihood of transmissions interfering with each other is steadily growing to the point that new techniques need to be employed. Furthermore, to combat remotely operated improvised explosive devices, many ground convoys transmit high-power broadband jamming signals, which block both hostile as well as friendly communications. These wide-band jamming fields pose a serious technical challenge to existing anti-jamming solutions that are currently employed by the Navy and Marine Corps. This thesis examines the feasibility of removing such deterministic jammers from the spectral environment, enabling friendly communications. Anti-jamming solutions in self-jamming environments are rarely considered in the literature, principally due to the non-traditional nature of such jamming techniques. As a result, a combination of approaches are examined which include: Antenna Subset Selection, Spectral Subtraction, and Source Separation. These are combined to reduce environmental interference for reliable transmissions. Specific operational conditions are considered and evaluated, primarily to define the limitations and utility of such a system. A final prototype was constructed using a collection of USRP software defined radios, providing solid conclusions of the overall system performance

Space-time-frequency methods for interference-limited communication systems

textTraditionally, noise in communication systems has been modeled as an additive, white Gaussian noise process with independent, identically distributed samples. Although this model accurately reflects thermal noise present in communication system electronics, it fails to capture the statistics of interference and other sources of noise, e.g. in unlicensed communication bands. Modern communication system designers must take into account interference and non-Gaussian noise to maximize efficiencies and capacities of current and future communication networks. In this work, I develop new multi-dimensional signal processing methods to improve performance of communication systems in three applications areas: (i) underwater acoustic, (ii) powerline, and (iii) multi-antenna cellular. In underwater acoustic communications, I address impairments caused by strong, time-varying and Doppler-spread reverberations (self-interference) using adaptive space-time signal processing methods. I apply these methods to array receivers with a large number of elements. In powerline communications, I address impairments caused by non-Gaussian noise arising from devices sharing the powerline. I develop and apply a cyclic adaptive modulation and coding scheme and a factor-graph-based impulsive noise mitigation method to improve signal quality and boost link throughput and robustness. In cellular communications, I develop a low-latency, high-throughput space-time-frequency processing framework used for large scale (up to 128 antenna) MIMO. This framework is used in the world's first 100-antenna MIMO system and processes up to 492 Gbps raw baseband samples in the uplink and downlink directions. My methods prove that multi-dimensional processing methods can be applied to increase communication system performance without sacrificing real-time requirements.Electrical and Computer Engineerin

Nonlinear Distortion in Wideband Radio Receivers and Analog-to-Digital Converters: Modeling and Digital Suppression

Emerging wireless communications systems aim to flexible and efficient usage of radio spectrum in order to increase data rates. The ultimate goal in this field is a cognitive radio. It employs spectrum sensing in order to locate spatially and temporally vacant spectrum chunks that can be used for communications. In order to achieve that, flexible and reconfigurable transceivers are needed. A software-defined radio can provide these features by having a highly-integrated wideband transceiver with minimum analog components and mostly relying on digital signal processing. This is also desired from size, cost, and power consumption point of view. However, several challenges arise, from which dynamic range is one of the most important. This is especially true on receiver side where several signals can be received simultaneously through a single receiver chain. In extreme cases the weakest signal can be almost 100 dB weaker than the strongest one. Due to the limited dynamic range of the receiver, the strongest signals may cause nonlinear distortion which deteriorates spectrum sensing capabilities and also reception of the weakest signals. The nonlinearities are stemming from the analog receiver components and also from analog-to-digital converters (ADCs). This is a performance bottleneck in many wideband communications and also radar receivers. The dynamic range challenges are already encountered in current devices, such as in wideband multi-operator receiver scenarios in mobile networks, and the challenges will have even more essential role in the future.This thesis focuses on aforementioned receiver scenarios and contributes to modeling and digital suppression of nonlinear distortion. A behavioral model for direct-conversion receiver nonlinearities is derived and it jointly takes into account RF, mixer, and baseband nonlinearities together with I/Q imbalance. The model is then exploited in suppression of receiver nonlinearities. The considered method is based on adaptive digital post-processing and does not require any analog hardware modification. It is able to extract all the necessary information directly from the received waveform in order to suppress the nonlinear distortion caused by the strongest blocker signals inside the reception band.In addition, the nonlinearities of ADCs are considered. Even if the dynamic range of the analog receiver components is not limiting the performance, ADCs may cause considerable amount of nonlinear distortion. It can originate, e.g., from undeliberate variations of quantization levels. Furthermore, the received waveform may exceed the nominal voltage range of the ADC due to signal power variations. This causes unintentional signal clipping which creates severe nonlinear distortion. In this thesis, a Fourier series based model is derived for the signal clipping caused by ADCs. Furthermore, four different methods are considered for suppressing ADC nonlinearities, especially unintentional signal clipping. The methods exploit polynomial modeling, interpolation, or symbol decisions for suppressing the distortion. The common factor is that all the methods are based on digital post-processing and are able to continuously adapt to variations in the received waveform and in the receiver itself. This is a very important aspect in wideband receivers, especially in cognitive radios, when the flexibility and state-of-the-art performance is required

Bandwidth Compressed Waveform and System Design for Wireless and Optical Communications: Theory and Practice

This thesis addresses theoretical and practical challenges of spectrally efficient frequency division multiplexing (SEFDM) systems in both wireless and optical domains. SEFDM improves spectral efficiency relative to the well-known orthogonal frequency division multiplexing (OFDM) by non-orthogonally multiplexing overlapped sub-carriers. However, the deliberate violation of orthogonality results in inter carrier interference (ICI) and associated detection complexity, thus posing many challenges to practical implementations. This thesis will present solutions for these issues. The thesis commences with the fundamentals by presenting the existing challenges of SEFDM, which are subsequently solved by proposed transceivers. An iterative detection (ID) detector iteratively removes self-created ICI. Following that, a hybrid ID together with fixed sphere decoding (FSD) shows an optimised performance/complexity trade-off. A complexity reduced Block-SEFDM can subdivide the signal detection into several blocks. Finally, a coded Turbo-SEFDM is proved to be an efficient technique that is compatible with the existing mobile standards. The thesis also reports the design and development of wireless and optical practical systems. In the optical domain, given the same spectral efficiency, a low-order modulation scheme is proved to have a better bit error rate (BER) performance when replacing a higher order one. In the wireless domain, an experimental testbed utilizing the LTE-Advanced carrier aggregation (CA) with SEFDM is operated in a realistic radio frequency (RF) environment. Experimental results show that 40% higher data rate can be achieved without extra spectrum occupation. Additionally, a new waveform, termed Nyquist-SEFDM, which compresses bandwidth and suppresses out-of-band power leakage is investigated. A 4th generation (4G) and 5th generation (5G) coexistence experiment is followed to verify its feasibility. Furthermore, a 60 GHz SEFDM testbed is designed and built in a point-to-point indoor fiber wireless experiment showing 67% data rate improvement compared to OFDM. Finally, to meet the requirements of future networks, two simplified SEFDM transceivers are designed together with application scenarios and experimental verifications

Estimation Techniques and Mitigation Tools for Ionospheric effects on GNSS Receivers

Navigation is defined as the science of getting a craft or person from one place to another. The development of radio in the past century brought fort new navigation aids that enabled users, or rather their receivers, to compute their position with the help of signals from one or more radio-navigation system . The U.S. Global Positioning System (GPS) was envisioned as a satellite system for three-dimensional position and velocity determination fulfilling the following key attributes: global coverage, continuous/all weather operation, ability to serve high-dynamic platforms, and high accuracy. It represents the fruition of several technologies, which matured and came together in the second half of the 20th century. In particular, stable space-born platforms, ultra-stable atomic frequency standards, spread spectrum signaling, and microelectronics are the key developments in the realization and success of GPS. While GPS was under development, the Soviet Union undertook to develop a similar system called GLObalnaya NAvigatsionnaya Sputnikovaya Sistema (GLONASS). Both GLONASS and GPS were designed primarily for the military, but have transitioned in the past decades towards providing civilian and Safety-of-Life services as well. Other Global Navigation Satellite Systems (GNSS) are now being developed and deployed by governments, international consortia, and commercial interests. Among these are the European system Galileo and the Chinese system Beidou. Other regional systems are the Japanese Quasi-Zenith Satellite System and the Indian Gagan. GNSS have become a crucial component in countless modern systems, e.g. in telecommunication, navigation, remote sensing, precise agriculture, aviation and timing. One of the main threats to the reliable and safe operation of GNSS are the variable propagation conditions encountered by GNSS signals as they pass through the upper atmosphere of the Earth. In particular, irregular concentration of electrons in the ionosphere induce fast fluctuations in the amplitude and phase of GNSS signals called scintillations. The latter can greatly degrade the performance of GNSS receivers, with consequent economical impacts on service providers and users of high performance applications. New GNSS navigation signals and codes are expected to help mitigate such effects, although to what degree is still unknown. Furthermore, these new technologies will only come on line incrementally over the next decade as new GNSS satellites become operational. In the meantime, GPS users who need high performance navigation solution, e.g., offshore drilling companies, might be forced to postpone operations for which precision position knowledge is required until the ionospheric disturbances are over. For this reason continuous monitoring of scintillations has become a priority in order to try to predict its occurrence. Indeed, it is a growing scientific and industrial activity. However, Radio Frequency (RF) Interference from other telecommunication systems might threaten the monitoring of scintillation activity. Currently, the majority of the GNSS based application are highly exposed to unintentional or intentional interference issues. The extremely weak power of the GNSS signals, which is actually completely buried in the noise floor at the user receiver antenna level, puts interference among the external error contributions that most degrade GNSS performance. It is then of interest to study the effects these external systems may have on the estimation of ionosphere activity with GNSS. In this dissertation, we investigate the effect of propagation issues in GNSS, focusing on scintillations, interference and the joint effect of the two phenomena