The radio frequency power amplifier (RF-PA) within a digital wireless transmitter is a critical component regarding both the energy consumption and the signal quality. Especially due to today's broadband multicarrier modulation methods that generate signals with high peak-to-average power ratio, it is very hard to construct RF-PAs that achieve good energy efficiency and fulfill the strict linearity requirements imposed by the standard. Because of this, the digital predistortion (DPD) of RF-PAs has become a key technique for implementing energy efficient, high data rate wireless transmitters. This thesis investigates theoretical foundations and practical methods for the behavioral modeling and DPD of RF-PAs. The main contributions are a semi-physical model of the joint linearity-efficiency characteristics of RF-PAs, a detailed analysis of polynomial baseband models of RF-PAs focusing on the often neglected even-order terms in baseband, and a collection of practical methods for ...

Modern modulation methods as used in 3rd generation mobile communications (UMTS) generate strongly fluctuating transmission signal envelopes with high peak-to-average power ratios. These properties result in significant distortion due to the nonlinear behavior of the radio-frequency power amplifier (RF PA). We propose different nonlinear model structures for such amplifiers, based on memory polynomials and frequency-domain Volterra kernel expansion, where we can reduce the number of free parameters by 80% compared to traditional Volterra series approaches. Because these nonlinear models incorporate memory, we are able to model the nonlinear distortion of RF PAs with sufficient accuracy (e.g., −30 dB relative modeling error ), including the wideband case (bandwidth B = 20 MHz as needed for four-carrier WCDMA). Furthermore, we propose a method to construct RF PA models from frequency-dependent AM/AM and AM/PM conversions. For the compensation of the nonlinearities, we analyze ...

To satisfy the continuously growing demands for higher data rates, modern radio communication systems employ larger bandwidths and more complex waveforms. Furthermore, radio devices are expected to support a rich mixture of standards such as cellular networks, wireless local-area networks, wireless personal area networks, positioning and navigation systems, etc. In general, a "smart'' device should be flexible to support all these requirements while being portable, cheap, and energy efficient. These seemingly conflicting expectations impose stringent radio frequency (RF) design challenges which, in turn, call for their proper understanding as well as developing cost-effective solutions to address them. The direct-conversion transceiver architecture is an appealing analog front-end for flexible and multi-standard radio systems. However, it is sensitive to various circuit impairments, and modern communication systems based on multi-carrier waveforms such as Orthogonal Frequency Division Multiplexing (OFDM) and Orthogonal Frequency Division Multiple ...

Modern wireless communication systems utilize complex modulated signals such as OFDM signals to achieve increased data rates and spectral efficiency. These signals are characterized by a high peak-to-average-power ratio (PAPR). Thus, highly linear transmitters are required to provide sufficient transmission signal linearity. Conventional linear PAs, such as Class A or Class AB, produce high efficiency only near or at the peak output power region. As a result, the average efficiency is quite low for high PAPR signals. For non-portable devices such as base stations or mobile devices like mobile phones, low PA efficiency means higher heat dissipation which is often a design criterion. In addition, in mobile devices, a direct consequence of the low PA efficiency is the reduced battery lifetime, especially when the mobile device is required to operate at quite different output power levels. This thesis addresses the ...

Massive MIMO (multiple-input–multiple-output) is a multi-antenna technology for cellular wireless communication, where the base station uses a large number of individually controllable antennas to multiplex users spatially. This technology can provide a high spectral efficiency. One of its main challenges is the immense hardware complexity and cost of all the radio chains in the base station. To make massive MIMO commercially viable, inexpensive, low-complexity hardware with low linearity has to be used, which inherently leads to more signal distortion. This thesis investigates how the degenerated linearity of some of the main components—power amplifiers, analog-to-digital converters (ADCs) and low-noise amplifiers—affects the performance of the system, with respect to data rate, power consumption and out-of-band radiation. The main results are: Spatial processing can reduce PAR (peak-to-average ratio) of the transmit signals in the downlink to as low as 0B; this, however, does ...

The error vector magnitude (EVM) is a standard metric to quantify the performance of digital communication systems and related building blocks. Regular EVM measurements require expensive equipment featuring inphase and quadrature (IQ) demodulation, wideband analog-to-digital converters (ADCs), and dedicated receiver algorithms to demodulate the data symbols. With modern high data rate communication standards that require high bandwidths and low amounts of error, it is difficult to avoid bias due to errors in the measurement chain. This thesis develops and discusses measurement methods that address the above-described issues with EVM measurements. The first method is an extension of the regular EVM, yielding two results from a single measurement. One result equals the regular EVM result, whereas the other excludes potential errors due to mismatches of the I- and Q- paths of direct conversion transmitters and receivers (IQ imbalance). This can be ...

Magnetic Resonance Imaging (MRI) is an important diagnostic tool for imaging soft tissue without the use of ionizing radiation. Moreover, through advanced signal processing, MRI can provide more than just anatomical information, such as estimates of tissue-specific physical properties. Signal processing lies at the very core of the MRI process, which involves input design, information encoding, image reconstruction, and advanced filtering. Based on signal modeling and estimation, it is possible to further improve the images, reduce artifacts, mitigate noise, and obtain quantitative tissue information. In quantitative MRI, different physical quantities are estimated from a set of collected images. The optimization problems solved are typically nonlinear, and require intelligent and application-specific algorithms to avoid suboptimal local minima. This thesis presents several methods for efficiently solving different parameter estimation problems in MRI, such as multi-component T2 relaxometry, temporal phase correction of complex-valued ...

This Dissertation addresses the signal acquisition problem using antenna arrays in the general framework of Global Navigation Satellite Systems (GNSS) receivers. GNSSs provide the necessary infrastructures for a myriad of applications and services that demand a robust and accurate positioning service. GNSS ranging signals are received with very low signal-to-noise ratio. Despite that the GNSS CDMA modulation offers limited protection against Radio Frequency Interferences (RFI), an interference that exceeds the processing gain can easily degrade receivers' performance or even deny completely the GNSS service. A growing concern of this problem has appeared in recent times. A single-antenna receiver can make use of time and frequency diversity to mitigate interferences, even though the performance of these techniques is compromised in the presence of wideband interferences. Antenna arrays receivers can benefit from spatial-domain processing, and thus mitigate the effects of interfering signals. ...

In the recent years, a significant portion of the research within the field of wireless communications has been motivated by two aspects: the constant increase in the number of wireless devices and the higher and higher data rate requirements of the individual applications. The undisputed outcome of these phenomena is the heavy congestion of the suitable spectral resources. This has inspired many innovative solutions for improving the spectral efficiency of the wireless communications systems by facilitating more simultaneous connections and higher data rates without requiring additional spectrum. These include technologies such as in-phase/quadrature (I/Q) modulation, multiple-input and multiple-output (MIMO) systems, and the orthogonal frequency-division multiplexing (OFDM) waveform, among others. Even though these existing solutions have greatly improved the spectral efficiency of wireless communications, even more advanced techniques are needed for fulfilling the future data transfer requirements in the ultra high ...

With the advent of spectrally efficient wireless communication systems employing modulation schemes with varying amplitude of the communication signal, linearisation techniques for nonlinear microwave power amplifiers have gained significant interest. The availability of fast and cheap digital processing technology makes digital pre-distortion an attractive candidate as a means for power amplifier linearisation since it promises high power efficiency and fleexibility. Digital pre-distortion is further in line with the current efforts towards software defined radio systems, where a principal aim is to substitute costly and inflexible analogue circuitry with cheap and reprogrammable digital circuitry. Microwave power amplifiers are most efficient in terms of delivered microwave output power vs. supplied power if driven near the saturation point. In this operational mode, the amplifier behaves as a nonlinear device, which introduces undesired distortions in the information bear- ing microwave signal. These nonlinear distortions ...

Ultra-wideband (UWB) communication systems use radio signals with a bandwidth in the range of some hundred MHz to several GHz. Radio channels with dense multipath propagation achieve high multipath diversity, which can be used to improve the robustness and capacity of the communication channel. Furthermore the large bandwidth allows to transmit signals with a small power spectral density such that the interference to other radio signals will be negligible, even if they lie within the same frequency band. In this work the focus is on low-complexity receiver architectures for communication systems in presence of multiple-access interference (MAI). The main objective of this thesis is to develop and to study a framework for communications for transmitted reference (TR) UWB systems and energy detection UWB systems. First, we study the hybrid matched-filter (HMF) receiver for TR UWB systems, which employs matched filters ...

This thesis investigates noncoherent multi-channel ultra-wideband receivers. Noncoherent ultra-wideband receivers promise low power consumption and low processing complexity as they, in contrast to coherent receiver architectures, relinquish the need of complex carrier frequency and phase recovering. Unfortunately, their peak data rate is limited by the delay spread of the multipath radio channel. Noncoherent multi-channel receivers can break this rate limit due to their capability to demodulate multi-carrier signals. Such receivers use an analog front-end to separate the received signals into their sub-channels. In this work, the modeling and optimization of realistic front-end components is addressed and their impact on the system performance of noncoherent multi-channel ultra-wideband receivers is analyzed. With a proposed generalized mathematical framework, it is shown that there exists a variety of noncoherent multi-channel receiver types with similar system performance which differ only in their front-end filters. It ...

Nowadays, many disciplines in science and engineering deal with problems for which a solution relies on knowledge about the characteristics of one or more given systems that can only be ascertained based on restricted observations. This requires the fitting of an adequately chosen model, such that it “best” conforms to a set of measured data. Depending on the context, this fitting procedure may resort to a huge amount of recorded data and abundant numerical power, or contrarily, to only a few streams of samples, which have to be processed on the fly at low computational cost. This thesis, exclusively focuses on the latter scenario. It specifically studies unexpected behaviour and reliability of the widely spread and computationally highly efficient class of gradient type algorithms. Additionally, special attention is paid to systems that combine several of them. Chapter 3 is dedicated ...

Digital subscriber line (DSL) technology is one of the fastest growing broadband internet access media. Whereas asymmetric DSL (ADSL) already offers data rates of a few megabits per second, next-generation ADSL2+ and VDSL promise even higher bit rates to support so-called triple play (high-quality video, voice and high-speed data). The use of a large bandwidth over the phone line (up to 12 MHz for VDSL) induces impairments, such as severe channel distortion, echo, narrow-band radiofrequency interference (RFI) and crosstalk from other DSL systems. DSL communication makes use of so-called discrete multitone (DMT) modulation, supplemented with advanced digital signal processing algorithms, to tackle these impairments and serve a maximum number of customers. In this thesis, we focus on channel equalization and RFI mitigation algorithms that outperform existing algorithms in terms of bit rate. DMT equalization is typically done by means of ...

The widespread use of mobile internet and smart applications has led to an explosive growth in mobile data traffic. With the rise of smart homes, smart buildings, and smart cities, this demand is ever growing since future communication systems will require the integration of multiple networks serving diverse sectors, domains and applications, such as multimedia, virtual or augmented reality, machine-to-machine (M2M) communication / the Internet of things (IoT), automotive applications, and many more. Therefore, in the future, the communication systems will not only be required to provide Gbps wireless connectivity but also fulfill other requirements such as low latency and massive machine type connectivity while ensuring the quality of service. Without significant technological advances to increase the system capacity, the existing telecommunications infrastructure will be unable to support these multi-dimensional requirements. This poses an important demand for suitable waveforms with ...