Nonlinear models and algorithms for RF systems digital calibration

Focusing on the receiving side of a communication system, the current trend in pushing the digital domain ever more closer to the antenna sets heavy constraints on the accuracy and linearity of the analog front-end and the conversion devices. Moreover, mixed-signal implementations of Systems-on-Chip using nanoscale CMOS processes result in an overall poorer analog performance and a reduced yield. To cope with the impairments of the low performance analog section in this "dirty RF" scenario, two solutions exist: designing more complex analog processing architectures or to identify the errors and correct them in the digital domain using DSP algorithms. In the latter, constraints in the analog circuits' precision can be offloaded to a digital signal processor. This thesis aims at the development of a methodology for the analysis, the modeling and the compensation of the analog impairments arising in different stages of a receiving chain using digital calibration techniques. Both single and multiple channel architectures are addressed exploiting the capability of the calibration algorithm to homogenize all the channels' responses of a multi-channel system in addition to the compensation of nonlinearities in each response. The systems targeted for the application of digital post compensation are a pipeline ADC, a digital-IF sub-sampling receiver and a 4-channel TI-ADC. The research focuses on post distortion methods using nonlinear dynamic models to approximate the post-inverse of the nonlinear system and to correct the distortions arising from static and dynamic errors. Volterra model is used due to its general approximation capabilities for the compensation of nonlinear systems with memory. Digital calibration is applied to a Sample and Hold and to a pipeline ADC simulated in the 45nm process, demonstrating high linearity improvement even with incomplete settling errors enabling the use of faster clock speeds. An extended model based on the baseband Volterra series is proposed and applied to the compensation of a digital-IF sub-sampling receiver. This architecture envisages frequency selectivity carried out at IF by an active band-pass CMOS filter causing in-band and out-of-band nonlinear distortions. The improved performance of the proposed model is demonstrated with circuital simulations of a 10th-order band pass filter, realized using a five-stage Gm-C Biquad cascade, and validated using out-of-sample sinusoidal and QAM signals. The same technique is extended to an array receiver with mismatched channels' responses showing that digital calibration can compensate the loss of directivity and enhance the overall system SFDR. An iterative backward pruning is applied to the Volterra models showing that complexity can be reduced without impacting linearity, obtaining state-of-the-art accuracy/complexity performance. Calibration of Time-Interleaved ADCs, widely used in RF-to-digital wideband receivers, is carried out developing ad hoc models because the steep discontinuities generated by the imperfect canceling of aliasing would require a huge number of terms in a polynomial approximation. A closed-form solution is derived for a 4-channel TI-ADC affected by gain errors and timing skews solving the perfect reconstruction equations. A background calibration technique is presented based on cyclo-stationary filter banks architecture. Convergence speed and accuracy of the recursive algorithm are discussed and complexity reduction techniques are applied

Post Conversion Correction of Non-Linear Mismatches for Time Interleaved Analog-to-Digital Converters

Time Interleaved Analog-to-Digital Converters (TI-ADCs) utilize an architecture which enables conversion rates well beyond the capabilities of a single converter while preserving most or all of the other performance characteristics of the converters on which said architecture is based. Most of the approaches discussed here are independent of architecture; some solutions take advantage of specific architectures. Chapter 1 provides the problem formulation and reviews the errors found in ADCs as well as a brief literature review of available TI-ADC error correction solutions. Chapter 2 presents the methods and materials used in implementation as well as extend the state of the art for post conversion correction. Chapter 3 presents the simulation results of this work and Chapter 4 concludes the work. The contribution of this research is three fold: A new behavioral model was developed in SimulinkTM and MATLABTM to model and test linear and nonlinear mismatch errors emulating the performance data of actual converters. The details of this model are presented as well as the results of cumulant statistical calculations of the mismatch errors which is followed by the detailed explanation and performance evaluation of the extension developed in this research effort. Leading post conversion correction methods are presented and an extension with derivations is presented. It is shown that the data converter subsystem architecture developed is capable of realizing better performance of those currently reported in the literature while having a more efficient implementation

Characterization and modelling of software defined radio front-ends

Doutoramento em Engenharia ElectrotécnicaO presente trabalho tem por objectivo estudar a caracterização e modelação de arquitecturas de rádio frequência para aplicações em rádios definidos por software e rádios cognitivos. O constante aparecimento no mercado de novos padrões e tecnologias para comunicações sem fios têm levantado algumas limitações à implementação de transceptores rádio de banda larga. Para além disso, o uso de sistemas reconfiguráveis e adaptáveis baseados no conceito de rádio definido por software e rádio cognitivo assegurará a evolução para a próxima geração de comunicações sem fios. A ideia base desta tese passa por resolver alguns problemas em aberto e propor avanços relevantes, tirando para isso partido das capacidades providenciadas pelos processadores digitais de sinal de forma a melhorar o desempenho global dos sistemas propostos. Inicialmente, serão abordadas várias estratégias para a implementação e projecto de transceptores rádio, concentrando-se sempre na aplicabilidade específica a sistemas de rádio definido por software e rádio cognitivo. Serão também discutidas soluções actuais de instrumentação capaz de caracterizar um dispositivo que opere simultaneamente nos domínios analógico e digital, bem como, os próximos passos nesta área de caracterização e modelação. Além disso, iremos apresentar novos formatos de modelos comportamentais construídos especificamente para a descrição e caracterização não-linear de receptores de amostragem passa-banda, bem como, para sistemas nãolineares que utilizem sinais multi-portadora. Será apresentada uma nova arquitectura suportada na avaliação estatística dos sinais rádio que permite aumentar a gama dinâmica do receptor em situações de multi-portadora. Da mesma forma, será apresentada uma técnica de maximização da largura de banda de recepção baseada na utilização do receptor de amostragem passa-banda no formato complexo. Finalmente, importa referir que todas as arquitecturas propostas serão acompanhadas por uma introdução teórica e simulações, sempre que possível, sendo após isto validadas experimentalmente por protótipos laboratoriais.This work investigates the characterization and modeling of radio frequency front-ends for software defined radio and cognitive radio applications. The emergence of new standards and technologies in the wireless communications market are raising several issues to the implementation of wideband transceiver systems. Also, reconfigurable and adaptable systems based on software defined and cognitive radio models are paving the way for the next generation of wireless systems. In this doctoral thesis the fundamental idea is to address the particular open issues and propose appropriate advancements by exploring and taking profit from new capabilities of digital signal processors in a way to improve the overall performance of the novel schemes. Receiver and transmitter strategies for radio communications are summarized by concentrating on the usability for software defined radio and cognitive radio systems. Available instrumentation and next steps for analog and digital radio frequency hardware characterization is also discussed. Wideband behavioral model formats are proposed for nonlinear description and characterization of bandpass sampling receivers, as well as, for multi-carrier nonlinear systems operation. The proposed models share a great flexibility and have the freedom to be simply expanded to other fields. A new design for receiver dynamic range improvement in multi-carrier scenarios is proposed, which is supported on the useful wireless signals statistical evaluation. Additionally, receiver-side bandwidth maximization based on higher-order bandpass sampling approaches is evaluated. All the proposed designs and modeling strategies are accompanied by theoretical backgrounds and simulations whenever possible, being then experimentally validated by laboratory prototypes

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

Machine Learning in Digital Signal Processing for Optical Transmission Systems

The future demand for digital information will exceed the capabilities of current optical communication systems, which are approaching their limits due to component and fiber intrinsic non-linear effects. Machine learning methods are promising to find new ways of leverage the available resources and to explore new solutions. Although, some of the machine learning methods such as adaptive non-linear filtering and probabilistic modeling are not novel in the field of telecommunication, enhanced powerful architecture designs together with increasing computing power make it possible to tackle more complex problems today. The methods presented in this work apply machine learning on optical communication systems with two main contributions. First, an unsupervised learning algorithm with embedded additive white Gaussian noise (AWGN) channel and appropriate power constraint is trained end-to-end, learning a geometric constellation shape for lowest bit-error rates over amplified and unamplified links. Second, supervised machine learning methods, especially deep neural networks with and without internal cyclical connections, are investigated to combat linear and non-linear inter-symbol interference (ISI) as well as colored noise effects introduced by the components and the fiber. On high-bandwidth coherent optical transmission setups their performances and complexities are experimentally evaluated and benchmarked against conventional digital signal processing (DSP) approaches. This thesis shows how machine learning can be applied to optical communication systems. In particular, it is demonstrated that machine learning is a viable designing and DSP tool to increase the capabilities of optical communication systems

Compensation for Impairments of Frequency Converters in Millimeter Wave Vector Signal Generators

The upcoming fifth generation (5G) of wireless communications aims to utilize millimeter wave (mm-wave) frequencies in its infrastructure to alleviate the crowded spectrum problem below 6 GHz. At higher frequencies, modulation bandwidths of several hundreds of MHz can be utilized to increase system capacities. However, the radio frequency (RF) frontends can exhibit significant amounts of impairments over these wide bandwidths, thereby limiting the achievable output signal quality and capacity. In this work, two signal generation architectures and the accompanying compensation schemes to mitigate the impairments are proposed for the generation of wideband modulated signals at mm-wave frequencies. The frequency dependent IQ imbalance effects in conventional direct conversion signal generation architectures over ultra wide bandwidths are first investigated. For that, a new interleaved multi-tone test signal based identification and compensation scheme is proposed. This scheme was experimentally validated by using an off-the-shelf IQ mixer operating at 30 GHz driven with an interleaved multi-tone signal with 4 GHz of modulation bandwidth and achieving a reduction in the normalized mean squared error (NMSE) from -14 dB to -38 dB. Subsequently, a low-complexity pruned Volterra series based digital predistortion (DPD) scheme was devised to mitigate the nonlinear distortions exhibited by the power amplifier stage and maximize the signal quality of orthogonal frequency division multiplexing (OFDM) signals with modulation bandwidths up to 800 MHz. After compensation of the system with 66 DPD coefficients, the OFDM signal with 800 MHz of modulation bandwidth exhibited an NMSE of -32.4 dB and an adjacent channel power ratio (ACPR) of 45 dBc. However, the challenges associated with the implementation of traditional direct conversion architectures exacerbate as the operating frequency increases. For instance, the performance of high frequency active building blocks, e.g. mixer and amplifiers, deteriorates as the operating frequency approaches the maximum oscillation frequency of the semiconductor technology. To address this challenge, a signal generation system utilizing frequency multipliers to replace the mixer and facilitate frequency upconversion is proposed. A novel Volterra series based behavioural model is also devised to predict the nonlinear behaviour of frequency multipliers and to form the basis for synthesizing a DPD scheme capable of obtaining acceptable signal quality when driven with wideband modulated signals. Various frequency multiplier based signal generation systems were implemented using off-the-shelf frequency doublers, triplers, and quadruplers to serve as proof of concept prototypes. Experiments confirmed the ability to generate modulated signals with competitive error vector magnitudes (EVM) and ACPR levels with low complexity DPD schemes

Analysis and design of low-power data converters

In a large number of applications the signal processing is done exploiting both analog and digital signal processing techniques. In the past digital and analog circuits were made on separate chip in order to limit the interference and other side effects, but the actual trend is to realize the whole elaboration chain on a single System on Chip (SoC). This choice is driven by different reasons such as the reduction of power consumption, less silicon area occupation on the chip and also reliability and repeatability. Commonly a large area in a SoC is occupied by digital circuits, then, usually a CMOS short-channel technological processes optimized to realize digital circuits is chosen to maximize the performance of the Digital Signal Proccessor (DSP). Opposite, the short-channel technology nodes do not represent the best choice for analog circuits. But in a large number of applications, the signals which are treated have analog nature (microphone, speaker, antenna, accelerometers, biopotential, etc.), then the input and output interfaces of the processing chip are analog/mixed-signal conversion circuits. Therefore in a single integrated circuit (IC) both digital and analog circuits can be found. This gives advantages in term of total size, cost and power consumption of the SoC. The specific characteristics of CMOS short-channel processes such as: • Low breakdown voltage (BV) gives a power supply limit (about 1.2 V). • High threshold voltage VTH (compared with the available voltage supply) fixed in order to limit the leakage power consumption in digital applications (of the order of 0.35 / 0.4V), puts a limit on the voltage dynamic, and creates many problems with the stacked topologies. • Threshold voltage dependent on the channel length VTH = f(L) (short channel effects). • Low value of the output resistance of the MOS (r0) and gm limited by speed saturation, both causes contribute to achieving a low intrinsic gain gmr0 = 20 to 26dB. • Mismatch which brings offset effects on analog circuits. make the design of high performance analog circuits very difficult. Realizing lowpower circuits is fundamental in different contexts, and for different reasons: lowering the power dissipation gives the capability to reduce the batteries size in mobile devices (laptops, smartphones, cameras, measuring instruments, etc.), increase the life of remote sensing devices, satellites, space probes, also allows the reduction of the size and weight of the heat sink. The reduction of power dissipation allows the realization of implantable biomedical devices that do not damage biological tissue. For this reason, the analysis and design of low power and high precision analog circuits is important in order to obtain high performance in technological processes that are not optimized for such applications. Different ways can be taken to reduce the effect of the problems related to the technology: • Circuital level: a circuit-level intervention is possible to solve a specific problem of the circuit (i.e. Techniques for bandwidth expansion, increase the gain, power reduction, etc.). • Digital calibration: it is the highest level to intervene, and generally going to correct the non-ideal structure through a digital processing, these aims are based on models of specific errors of the structure. • Definition of new paradigms. This work has focused the attention on a very useful mixed-signal circuit: the pipeline ADC. The pipeline ADCs are widely used for their energy efficiency in high-precision applications where a resolution of about 10-16 bits and sampling rates above hundreds of Mega-samples per second (telecommunication, radar, etc.) are needed. An introduction on the theory of pipeline ADC, its state of the art and the principal non-idealities that affect the energy efficiency and the accuracy of this kind of data converters are reported in Chapter 1. Special consideration is put on low-voltage low-power ADCs. In particular, for ADCs implemented in deep submicron technology nodes side effects called short channel effects exist opposed to older technology nodes where undesired effects are not present. An overview of the short channel effects and their consequences on design, and also power consuption reduction techniques, with particular emphasis on the specific techniques adopted in pipelined ADC are reported in Chapter 2. Moreover, another way may be undertaken to increase the accuracy and the efficiency of an ADC, this way is the digital calibration. In Chapter 3 an overview on digital calibration techniques, and furthermore a new calibration technique based on Volterra kernels are reported. In some specific applications, such as software defined radios or micropower sensor, some circuits should be reconfigurable to be suitable for different radio standard or process signals with different charateristics. One of this building blocks is the ADC that should be able to reconfigure the resolution and conversion frequency. A reconfigurable voltage-scalable ADC pipeline capable to adapt its voltage supply starting from the required conversion frequency was developed, and the results are reported in Chapter 4. In Chapter 5, a pipeline ADC based on a novel paradigm for the feedback loop and its theory is described

Novel Predistortion System for 4G/5G Small-Cell and Wideband Transmitters

To meet the growing demand for mobile data, various technologies are being introduced to wireless networks to increase system capacity. On one hand, large number of small-cell base stations are adopted to serve the reduced cell size; on the other hand, millimeter wave (mm-wave) systems with large antenna arrays that transmit ultra-wideband signals are expected in fifth generation (5G) networks. Power amplifiers (PAs), responsible for boosting the radio frequency (RF) signal power, are the most critical components in base station transmitters, and dominate the overall efficiency and linearity of the system. The design challenges to balance the contradictory requirements of efficiency and linearity of the PAs are usually addressed by linearization techniques, particularly the digital predistortion (DPD) system. However, existing DPD solutions face increasing difficulties keeping up with new developments in base station technologies. When considering sub-6 GHz small-cell base station transmitters, analog and RF predistortion techniques have recently received renewed attention due to their inherent low power nature. Their achievable linearization capacity is significantly limited, however, largely by their implementation complexity in realizing the needed predistortion models in analog circuitry. On the other hand, despite significant developments in DPD models for wideband signals, the implementations of such DPD models in practical hardware have received relatively little attention. Yet the conventional implementation of a DPD engine is limited by the maximum clock frequency of the digital circuitry employed and cannot be scaled to satisfy the growing bandwidth of transmitted signals for 5G networks. Furthermore, both analog and digital solutions require a transmitter-observation-receiver (TOR) to capture the PA outputs, necessitates the use of analog-to-digital converters (ADCs) whose complexity and power consumption increase with signal bandwidth. Such trend is not scalable for future base stations, and new innovations in feedback and training methods are required. This thesis presents a number of contributions to address the above identified challenges. To reduce the power overhead of the linearization system, a digitally-assisted analog-RF predistortion (DA-ARFPD) system that uses a novel predistortion model is introduced. The proposed finite-impulse-response assisted envelope memory polynomial (FIR-EMP) model allows for a reduction of hardware implementation complexity while maintaining good linearization capacity and low power overhead. A two-step small-signal-assisted parameter identification (SSAPI) algorithm is devised to estimate the parameters of the two main blocks of the FIR-EMP model, such that the training can be completed efficiently. A DA-ARFPD test bench has been built, which incorporates major RF components, to assess the validity of the proposed FIR-EMP scheme and the SSAPI algorithm. Measurement results show that the proposed FIR-EMP model with SSAPI algorithm can successfully linearize multiple PAs driven with various wideband and carrier-aggregated signals of up to 80~MHz modulation bandwidths for sub-6 GHz systems. Next, a hardware-efficient real-time DPD system with scalable linearization bandwidth for ultra-wideband 5G mm-wave transmitters is proposed. It uses a novel parallel-processing DPD engine architecture to process multiple samples per clock cycle, overcomes the linearization bandwidth limit imposed by the maximum clock rate of digital circuits used in conventional DPD implementation. Potentially unlimited linearization bandwidth could be achieved by using the proposed system with current digital circuit technologies. The linearization performance and bandwidth scalability of the proposed system is demonstrated experimentally using a silicon-based Doherty (DPA) with 400 MHz wideband signal operating at 28 GHz, and over-the-air measurements using a 64-element beamforming array with 800 MHz wideband signal, also at 28 GHz. The proposed DPD system achieves over 2.4 GHz linearization bandwidth using only a 300 MHz core clock for the digital circuits. Finally, to reduce the power consumption and cost of the TOR, a new approach to train the predistorter using under-sampled feedback signal is presented. Using aliased samples of the PA's output captured at either baseband or intermedia frequency (IF), the proposed algorithm is able to compute the coefficients of the predistortion engine to linearize the PA using a direct learning architecture. Experimentally, both the baseband and IF schemes achieve linearization performance comparable to a full-rate system. Implemented together with a parallel-processing based DPD engine on a field-programmable gate array (FPGA) based system-on-chip (SOC), the proposed feedback and training solution achieves over 2.4~GHz linearization bandwidth using an ADC operating at a clock rate of 200 MHz. Its performance is demonstrated experimentally by linearizing a silicon DPA with 200 MHz and 400 MHz signals in conductive measurements, and a 64-element beamforming array with 400 MHz and 800 MHz signals in over-the-air testing

Energy-Efficient Receiver Design for High-Speed Interconnects

High-speed interconnects are of vital importance to the operation of high-performance computing and communication systems, determining the ultimate bandwidth or data rates at which the information can be exchanged. Optical interconnects and the employment of high-order modulation formats are considered as the solutions to fulfilling the envisioned speed and power efficiency of future interconnects. One common key factor in bringing the success is the availability of energy-efficient receivers with superior sensitivity. To enhance the receiver sensitivity, improvement in the signal-to-noise ratio (SNR) of the front-end circuits, or equalization that mitigates the detrimental inter-symbol interference (ISI) is required. In this dissertation, architectural and circuit-level energy-efficient techniques serving these goals are presented. First, an avalanche photodetector (APD)-based optical receiver is described, which utilizes non-return-to-zero (NRZ) modulation and is applicable to burst-mode operation. For the purposes of improving the overall optical link energy efficiency as well as the link bandwidth, this optical receiver is designed to achieve high sensitivity and high reconfiguration speed. The high sensitivity is enabled by optimizing the SNR at the front-end through adjusting the APD responsivity via its reverse bias voltage, along with the incorporation of 2-tap feedforward equalization (FFE) and 2-tap decision feedback equalization (DFE) implemented in current-integrating fashion. The high reconfiguration speed is empowered by the proposed integrating dc and amplitude comparators, which eliminate the RC settling time constraints. The receiver circuits, excluding the APD die, are fabricated in 28-nm CMOS technology. The optical receiver achieves bit-error-rate (BER) better than 1E−12 at −16-dBm optical modulation amplitude (OMA), 2.24-ns reconfiguration time with 5-dB dynamic range, and 1.37-pJ/b energy efficiency at 25 Gb/s. Second, a 4-level pulse amplitude modulation (PAM4) wireline receiver is described, which incorporates continuous time linear equalizers (CTLEs) and a 2-tap direct DFE dedicated to the compensation for the first and second post-cursor ISI. The direct DFE in a PAM4 receiver (PAM4-DFE) is made possible by the proposed CMOS track-and-regenerate slicer. This proposed slicer offers rail-to-rail digital feedback signals with significantly improved clock-to-Q delay performance. The reduced slicer delay relaxes the settling time constraint of the summer circuits and allows the stringent DFE timing constraint to be satisfied. With the availability of a direct DFE employing the proposed slicer, inductor-based bandwidth enhancement and loop-unrolling techniques, which can be power/area intensive, are not required. Fabricated in 28-nm CMOS technology, the PAM4 receiver achieves BER better than 1E−12 and 1.1-pJ/b energy efficiency at 60 Gb/s, measured over a channel with 8.2-dB loss at Nyquist frequency. Third, digital neural-network-enhanced FFEs (NN-FFEs) for PAM4 analog-to-digital converter (ADC)-based optical interconnects are described. The proposed NN-FFEs employ a custom learnable piecewise linear (PWL) activation function to tackle the nonlinearities with short memory lengths. In contrast to the conventional Volterra equalizers where multipliers are utilized to generate the nonlinear terms, the proposed NN-FFEs leverage the custom PWL activation function for nonlinear operations and reduce the required number of multipliers, thereby improving the area and power efficiencies. Applications in the optical interconnects based on micro-ring modulators (MRMs) are demonstrated with simulation results of 50-Gb/s and 100-Gb/s links adopting PAM4 signaling. The proposed NN-FFEs and the conventional Volterra equalizers are synthesized with the standard-cell libraries in a commercial 28-nm CMOS technology, and their power consumptions and performance are compared. Better than 37% lower power overhead can be achieved by employing the proposed NN-FFEs, in comparison with the Volterra equalizer that leads to similar improvement in the symbol-error-rate (SER) performance.</p