Modelling and inverting complex-valued Wiener systems

We develop a complex-valued (CV) B-spline neural network approach for efficient identification and inversion of CV Wiener systems. The CV nonlinear static function in the Wiener system is represented using the tensor product of two univariate B-spline neural networks. With the aid of a least squares parameter initialisation, the Gauss-Newton algorithm effectively estimates the model parameters that include the CV linear dynamic model coefficients and B-spline neural network weights. The identification algorithm naturally incorporates the efficient De Boor algorithm with both the B-spline curve and first order derivative recursions. An accurate inverse of the CV Wiener system is then obtained, in which the inverse of the CV nonlinear static function of the Wiener system is calculated efficiently using the Gaussian-Newton algorithm based on the estimated B-spline neural network model, with the aid of the De Boor recursions. The effectiveness of our approach for identification and inversion of CV Wiener systems is demonstrated using the application of digital predistorter design for high power amplifiers with memor

Experimental demonstration of digital predistortion for orthogonal frequency-division multiplexing-radio over fibre links near laser resonance

Radio over fibre (RoF), an enabling technology for distribution of wireless broadband service signals through analogue optical links, suffers from non-linear distortion. Digital predistortion has been demonstrated as an effective approach to overcome the RoF non-linearity. However, questions remain as to how the approach performs close to laser resonance, a region of significant dynamic non-linearity, and how resilient the approach is to changes in input signal and link operating conditions. In this work, the performance of a digital predistortion approach is studied for directly modulated orthogonal frequency-division multiplexing RoF links operating from 2.47 to 3.7 GHz. It extends previous works to higher frequencies, and to higher quadrature amplitude modulation (QAM) levels. In addition, the resilience of the predistortion approach to changes in modulation level of QAM schemes, and average power levels are investigated, and a novel predistortion training approach is proposed and demonstrated. Both memoryless and memory polynomial predistorter models, and a simple off-line least-squares-based identification method, are used, with excellent performance improvements demonstrated up to 3.0 GHz

Transmitter Linearization for mm-Wave Communications Systems

There is an ever increasing need for enabling higher data rates in modern communication systems which brings new challenges in terms of the power consumption and nonlinearity of hardware components. These problems become prominent in power amplifiers (PAs) and can significantly degrade the performance of transmitters, and hence the overall communication system. Hence, it is of central importance to design efficient PAs with a linear operation region. This thesis proposes a methodology and a comprehensive framework to address this challenge. This is accomplished by application of predistortion to a mm-wave PA and an E-band IQ transmitter while investigating the trade-offs between linearity, efficiency and predistorter complexity using the proposed framework.In the first line of work, we have focused on a mm-wave PA. A PA has high efficiency at high input power at the expense of linearity, whereas it operates linearly for lower input power levels while sacrificing efficiency. To attain both linearity and efficiency, predistortion is often used to compensate for the PA nonlinearity. Yet, the trade-offs related to predistortion complexities are not fully understood. To address this challenge, we have used our proposed framework for evaluation of predistorters using modulated test signals and implemented it using digital predistortion and a mm-wave PA. This set-up enabled us to investigate the trade-offs between linearity, efficiency and predistorter complexity in a systematic manner. We have shown that to achieve similar linearity levels for different PA classes, predistorters with different complexities are needed and provided guidelines on the achievable limits in term linearity for a given predistorter complexity for different PA classes.In the second line of work, we have focused on linearization of an E-band transmitter using a baseband analog predistorter (APD) and under constraints given by a spectrum emission standard. In order to use the above proposed framework with these components, characterizations of the E-band transmitter and the APD are performed. In contrast to typical approaches in the literature, here joint mitigation of the PA and I/Q modulator impairments is used to model the transmitter. Using the developed models, optimal model parameters in terms of output power at the mask limit are determined. Using these as a starting point, we have iteratively optimized operating point of the APD and linearized the E-band transmitter. The experiments demonstrated that the analog predistorter can successfully increase the output power by 35% (1.3 dB) improvement while satisfying the spectrum emission mask

Fiber link design considerations for cloud-Radio Access Networks

Analog radio over fiber (RoF) links may offer advantages for cloud-Radio Access Networks in terms of component cost, but the behavior of the distortion with large numbers of subcarriers needs to be understood. In this paper, this is presented in terms of the variation between subcarriers. Memory polynomial predistortion is also shown to compensate for RoF and wireless path distortion. Whether for digitized or analog links, it is shown that appropriate framing structure parameters must be used to assure performance, especially of time-division duplex systems

Behavioral modeling and FPGA implementation of digital predistortion for RF and microwave power amplifiers

With the high interest in digital modulation techniques which are very sensitive to the PA nonlinearity, modern wireless communication systems require the usage of linearization techniques to improve the linear behavior of the RF power amplifier. The powerful and cheap digital processing technology makes the digital predistortion (DPD) a competitive candidate for the linearization of the PA. This thesis introduces the basic principle of DPD, its implementation on FPGA and the adaptive DPD system. The linearization of 4 PAs with DPD technique has been introduced: for the hybrid class AB PA operating at 2.6 GHz with a WiMAX testing signal, 33.7 dBm average power, 29.6 % drain efficiency, 13 dB ACPR and 9 dB NMSE improvement have been obtained; for the hybrid Doherty PA operating at 3.4 GHz with an I/Q testing signal, 35.0 dBm average power, 36.8 % drain efficiency, 12 dB ACPR and 13 dB NMSE improvement have been obtained; for the MMIC class AB PA operating at 7 GHz with an I/Q testing signal, 29.4 dBm average power, 25.7 % drain efficiency, 12 dB ACPR and 12 dB NMSE improvement have been obtained; for the two-stage PA operating at 24 GHz with an I/Q testing signal, 23.5 dBm average power, more than 14.0 % drain efficiency, 11 dB ACPR and 11 dB NMSE improvement have been obtained. The DPD algorithm has been implemented on FPGA with two methods based on LUT and a direct structure with only adders and multipliers. The block RAM on the FPGA board is chosen as the table in the LUT methods. The linearization performance for these three methods is similar. The test PA is the hybrid Doherty PA mentioned above and the test signal is the I/Q signal with 7.4 dB PAPR. 35.1 dBm average power, 36.8 % efficiency, 11 dB ACPR and 11 dB NMSE improvement have been obtained. The cost of logic resources for the direct structure method is the largest with 1,172 flip-flops, while the number of flip-flops for the two LUT methods are 263 and 583, respectively. A new adaptive algorithm has been proposed in this thesis for the adaptive DPD system. This new algorithm improves the performance in extracting the model parameters in complex number domain. With the experimental data from a combined class AB PA, the final accuracy of the model extracted by the new algorithm has been improved from -20 dB to about -40 dB and the converge speed is faster

Digital Pre-distortion for Interference Reduction in Dynamic Spectrum Access Networks

Given the ever increasing reliance of today’s society on ubiquitous wireless access, the paradigm of dynamic spectrum access (DSA) as been proposed and implemented for utilizing the limited wireless spectrum more efficiently. Orthogonal frequency division multiplexing (OFDM) is growing in popularity for adoption into wireless services employing DSA frame- work, due to its high bandwidth efficiency and resiliency to multipath fading. While these advantages have been proven for many wireless applications, including LTE-Advanced and numerous IEEE wireless standards, one potential drawback of OFDM or its non-contiguous variant, NC-OFDM, is that it exhibits high peak-to-average power ratios (PAPR), which can induce in-band and out-of-band (OOB) distortions when the peaks of the waveform enter the compression region of the transmitter power amplifier (PA). Such OOB emissions can interfere with existing neighboring transmissions, and thereby severely deteriorate the reliability of the DSA network. A performance-enhancing digital pre-distortion (DPD) technique compensating for PA and in-phase/quadrature (I/Q) modulator distortions is proposed in this dissertation. Al- though substantial research efforts into designing DPD schemes have already been presented in the open literature, there still exists numerous opportunities to further improve upon the performance of OOB suppression for NC-OFDM transmission in the presence of RF front-end impairments. A set of orthogonal polynomial basis functions is proposed in this dissertation together with a simplified joint DPD structure. A performance analysis is presented to show that the OOB emissions is reduced to approximately 50 dBc with proposed algorithms employed during NC-OFDM transmission. Furthermore, a novel and intuitive DPD solution that can minimize the power regrowth at any pre-specified frequency in the spurious domain is proposed in this dissertation. Conventional DPD methods have been proven to be able to effectively reduce the OOB emissions that fall on top of adjacent channels. However more spectral emissions in more distant frequency ranges are generated by employing such DPD solutions, which are potentially in violation of the spurious emission limit. At the same time, the emissions in adjacent channel must be kept under the OOB limit. To the best of the author’s knowledge, there has not been extensive research conducted on this topic. Mathematical derivation procedures of the proposed algorithm are provided for both memoryless nonlinear model and memory-based nonlinear model. Simulation results show that the proposed method is able to provide a good balance of OOB emissions and emissions in the far out spurious domain, by reducing the spurious emissions by 4-5 dB while maintaining the adjacent channel leakage ratio (ACLR) improvement by at least 10 dB, comparing to the PA output spectrum without any DPD

Energy-Efficient Distributed Estimation by Utilizing a Nonlinear Amplifier

abstract: Distributed estimation uses many inexpensive sensors to compose an accurate estimate of a given parameter. It is frequently implemented using wireless sensor networks. There have been several studies on optimizing power allocation in wireless sensor networks used for distributed estimation, the vast majority of which assume linear radio-frequency amplifiers. Linear amplifiers are inherently inefficient, so in this dissertation nonlinear amplifiers are examined to gain efficiency while operating distributed sensor networks. This research presents a method to boost efficiency by operating the amplifiers in the nonlinear region of operation. Operating amplifiers nonlinearly presents new challenges. First, nonlinear amplifier characteristics change across manufacturing process variation, temperature, operating voltage, and aging. Secondly, the equations conventionally used for estimators and performance expectations in linear amplify-and-forward systems fail. To compensate for the first challenge, predistortion is utilized not to linearize amplifiers but rather to force them to fit a common nonlinear limiting amplifier model close to the inherent amplifier performance. This minimizes the power impact and the training requirements for predistortion. Second, new estimators are required that account for transmitter nonlinearity. This research derives analytically and confirms via simulation new estimators and performance expectation equations for use in nonlinear distributed estimation. An additional complication when operating nonlinear amplifiers in a wireless environment is the influence of varied and potentially unknown channel gains. The impact of these varied gains and both measurement and channel noise sources on estimation performance are analyzed in this paper. Techniques for minimizing the estimate variance are developed. It is shown that optimizing transmitter power allocation to minimize estimate variance for the most-compressed parameter measurement is equivalent to the problem for linear sensors. Finally, a method for operating distributed estimation in a multipath environment is presented that is capable of developing robust estimates for a wide range of Rician K-factors. This dissertation demonstrates that implementing distributed estimation using nonlinear sensors can boost system efficiency and is compatible with existing techniques from the literature for boosting efficiency at the system level via sensor power allocation. Nonlinear transmitters work best when channel gains are known and channel noise and receiver noise levels are low.Dissertation/ThesisPh.D. Electrical Engineering 201

Digital Signal Processing Techniques Applied to Radio over Fiber Systems

The dissertation aims to analyze different Radio over Fiber systems for the front-haul applications. Particularly, analog radio over fiber (A-RoF) are simplest and suffer from nonlinearities, therefore, mitigating such nonlinearities through digital predistortion are studied. In particular for the long haul A-RoF links, direct digital predistortion technique (DPDT) is proposed which can be applied to reduce the impairments of A-RoF systems due to the combined effects of frequency chirp of the laser source and chromatic dispersion of the optical channel. Then, indirect learning architecture (ILA) based structures namely memory polynomial (MP), generalized memory polynomial (GMP) and decomposed vector rotation (DVR) models are employed to perform adaptive digital predistortion with low complexities. Distributed feedback (DFB) laser and vertical capacity surface emitting lasers (VCSELs) in combination with single mode/multi-mode fibers have been linearized with different quadrature amplitude modulation (QAM) formats for single and multichannel cases. Finally, a feedback adaptive DPD compensation is proposed. Then, there is still a possibility to exploit the other realizations of RoF namely digital radio over fiber (D-RoF) system where signal is digitized and transmits the digitized bit streams via digital optical communication links. The proposed solution is robust and immune to nonlinearities up-to 70 km of link length. Lastly, in light of disadvantages coming from A-RoF and D-RoF, it is still possible to take only the advantages from both methods and implement a more recent form knows as Sigma Delta Radio over Fiber (S-DRoF) system. Second Order Sigma Delta Modulator and Multi-stAge-noise-SHaping (MASH) based Sigma Delta Modulator are proposed. The workbench has been evaluated for 20 MHz LTE signal with 256 QAM modulation. Finally, The 6x2 GSa/s sigma delta modulators are realized on FPGA to show a real time demonstration of S-DRoF system. The demonstration shows that S-DRoF is a competitive competitor for 5G sub-6GHz band applications

High Linearity Millimeter Wave Power Amplifiers with Novel Linearizer Techniques

Millimeter-wave communications have experienced phenomenal growth in recent years when limited frequency spectrum is occupied by the ever-developing communication services. The power amplifier, as the key component in the transmitter/receiver module of communication systems, affects performance of the whole system directly and receives much attention. For minimized distortion and optimum system performance, the non-constant en- velope modulation schemes used in communication systems have challenging requirements on linearity. As linearity is related to communication quality directly, several linearization techniques, such as predistortion and feedforward, are applied to power amplifier design. Predistortion method has the advantages over other techniques in relatively simple struc- ture and reasonable linearity improvement. But current predistortion circuits have quite limited performance improvement and relatively large insertion loss, which indicate the need for further research. In most of millimeter-wave amplifier design, great effort has been spent on output power or gain, while linearity is often ignored. As almost all the predistortion circuits operate at the RF frequencies, the linearized millimeter-wave com- munication circuit is still relatively immature and very challenging. This project is dedicated to solve the linearity problem faced by millimeter-wave power amplifier in communication systems, which lacks of e®ective techniques in this field. Linearity improvement with the predistortion method will be the key issue in this project and some original ideas for predistortion circuit design will be applied to millimeter-wave amplifiers. In this thesis, several predistortion circuits with novel structure were proposed, which provide a new approach for linearity improvement for millimeter-wave power am- plifier. A millimeter-wave power ampli¯er for LMDS applications built on GaAs pHEMT technology was developed to a high engineering standard, which works as the test bench for linearization. Actual operation and parasitic elements at tens of gigahertz have been taken into consideration during the design. Firstly, two novel predistorter structures based on the amplifier were proposed, one is based on an amplifier with a fixed bias circuit and the other is based on an amplifier with a nonlinear signal dependant bias circuit. These novel structures can improve the linearity while improving other metrics simultaneously, which can effectively solve the problem of insertion loss faced by the conventional structures. Besides this, an original predistortion circuit design methodology derived from frequency to signal amplitude transformation was proposed. Based on this methodology, several transfer functions were proposed and related predistortion circuits were built to linearize the power amplifier. As this methodology is quite different from the traditional approach, it can improve the linearity signifficantly while other metrics are affected slightly and has a broad prospect for application