Design Strategies and Modelling of Low-Power Sigma-Delta Analog-to-Digital Converters

Oggi, i dispositivi portatili sono diventati la forza trainante del mercato consumer e nuove sfide stanno emergendo per aumentarne le prestazioni, pur mantenendo un ragionevole tempo di vita della batteria. Il dominio digitale è la miglior soluzione per realizzare funzioni di elaborazione del segnale, grazie alla scalabilità della tecnologia CMOS, che spinge verso l'integrazione a livello sub-micrometrico. Infatti, la riduzione della tensione di alimentazione introduce limitazioni severe per raggiungere un range dinamico accettabile nel dominio analogico. Minori costi, minore consumo di potenza, maggiore resa e una maggiore riconfigurabilità sono i principali vantaggi dell'elaborazione dei segnali nel dominio digitale. Da più di un decennio, diverse funzioni puramente analogiche sono state spostate nel dominio digitale. Ciò significa che i convertitori analogico-digitali (ADC) stanno diventando i componenti chiave in molti sistemi elettronici. Essi sono, infatti, il ponte tra il mondo digitale e analogico e, di conseguenza, la loro efficienza e la precisione spesso determinano le prestazioni globali del sistema. I convertitori Sigma-Delta sono il blocco chiave come interfaccia in circuiti a segnale-misto ad elevata risoluzione e basso consumo di potenza. I tools di modellazione e simulazione sono strumenti efficaci ed essenziali nel flusso di progettazione. Sebbene le simulazioni a livello transistor danno risultati più precisi ed accurati, questo metodo è estremamente lungo a causa della natura a sovracampionamento di questo tipo di convertitore. Per questo motivo i modelli comportamentali di alto livello del modulatore sono essenziali per il progettista per realizzare simulazioni veloci che consentono di identificare le specifiche necessarie al convertitore per ottenere le prestazioni richieste. Obiettivo di questa tesi è la modellazione del comportamento del modulatore Sigma-Delta, tenendo conto di diverse non idealità come le dinamiche dell'integratore e il suo rumore termico. Risultati di simulazioni a livello transistor e dati sperimentali dimostrano che il modello proposto è preciso ed accurato rispetto alle simulazioni comportamentali.

Signal processing in a loudspeaking telephone

One of the major problems associated with communication via a loudspeaking telephone (LST) is that, using analogue processing, duplex transmission is limited to low-loss lines and produces a low acoustic output. An architectural for an instrument has been developed and tested, which uses digital signal processing to provide duplex transmission between a LST and a telopnone handset over most of the B.T. network. Digital adaptive-filters are used in the duplex LST to cancel coupling between the loudspeaker and microphone, and across the transmit to receive paths of the 2-to-4-wire converter. Normal movement of a person in the acoustic path causes a loss of stability by increasing the level of coupling from the loudspeaker to the microphone, since there is a lag associated the adaptive filters learning about a non-stationary path, Control of the loop stability and the level of sidetone heard by the hadset user is by a microprocessoe, which continually monitors the system and regulates the gain. The result is a system which offers the best compromise available based on a set of measured parameters.A theory has been developed which gives the loop stability requirements based on the error between the parameters of the filter and those of the unknown path. The programme to develope a low-cost adaptive filter in LST produced a low-cost adaptive filter in LST produced a unique architecture which has a number of features not available in any similar system. These include automatic compensation for the rate of adaptation over a 36 dB range of output level, , 4 rates of adaptation (with a maximum of 465 dB/s), plus the ability to cascade up to 4 filters without loss o performance. A complex story has been developed to determine the adptation which can be achieved using finite-precision arithmatic. This enabled the development of an architecture which distributed the normalisation required to achieve optimum rate of adaptation over the useful input range. Comparison of theory and measurement for the adaptive filter show very close agreement. A single experimental LST was built and tested on connections to hanset telephones over the BT network. The LST demonstrated that duplex transmission was feasible using signal processing and produced a more comfortable means of communication beween people than methods emplying deep voice-switching to regulate the local-loop gain. Although, with the current level of processing power, it is not a panacea and attention must be directed toward the physical acoustic isolation between loudspeaker and microphone.

All-optical nonlinear signal processing at a RZ receiver

We propose a novel all-optical signal processor for use at a return-to-zero receiver utilising loop mirror intensity filtering and nonlinear pulse broadening in normal dispersion fibre. The device offers reamplification and cleaning up of the optical signals, and phase margin improvement. The efficiency of the technique is demonstrated by application to 40 Gbit/s data transmission.

Signal processing for molecular and cellular biological physics:an emerging field

Recent advances in our ability to watch the molecular and cellular processes of life in action-such as atomic force microscopy, optical tweezers and Forster fluorescence resonance energy transfer-raise challenges for digital signal processing (DSP) of the resulting experimental data. This article explores the unique properties of such biophysical time series that set them apart from other signals, such as the prevalence of abrupt jumps and steps, multi-modal distributions and autocorrelated noise. It exposes the problems with classical linear DSP algorithms applied to this kind of data, and describes new nonlinear and non-Gaussian algorithms that are able to extract information that is of direct relevance to biological physicists. It is argued that these new methods applied in this context typify the nascent field of biophysical DSP. Practical experimental examples are supplied.

Progress toward 100-G digital coherent pluggables using InP-based photonics

A new generation of high-capacity WDM systems with extremely robust performance has been enabled by coherent transmission and digital signal processing. To facilitate widespread deployment of this technology, particularly in the metro space, new photonic components and subsystems are being developed to support cost-effective, compact, and scalable transceivers. We briefly review the recent progress in InP-based photonic components, and report numerical simulation results of an InP-based transceiver comprising a dual-polarization I/Q modulator and a commercial DSP ASIC. Predicted performance penalties due to the nonlinear response, lower bandwidth, and finite extinction ratio of these transceivers are less than 1 and 2 dB for 100-G PM-QPSK and 200-G PM-16QAM, respectively. Using the well-established Gaussian-Noise model, estimated system reach of 100-G PM-QPSK is greater than 600 km for typical ROADM-based metro-regional systems with internode losses up to 20 dB. © 1983-2012 IEEE.

Digital nonlinear equalization for optical transmission systems

This thesis focuses on digital equalization of nonlinear fiber impairments for coherent optical transmission systems. Building from well-known physical models of signal propagation in single-mode optical fibers, novel nonlinear equalization techniques are proposed, numerically assessed and experimentally demonstrated. The structure of the proposed algorithms is strongly driven by the optimization of the performance versus complexity tradeoff, envisioning the near-future practical application in commercial real-time transceivers. The work is initially focused on the mitigation of intra-channel nonlinear impairments relying on the concept of digital backpropagation (DBP) associated with Volterra-based filtering. After a comprehensive analysis of the third-order Volterra kernel, a set of critical simplifications are identified, culminating in the development of reduced complexity nonlinear equalization algorithms formulated both in time and frequency domains. The implementation complexity of the proposed techniques is analytically described in terms of computational effort and processing latency, by determining the number of real multiplications per processed sample and the number of serial multiplications, respectively. The equalization performance is numerically and experimentally assessed through bit error rate (BER) measurements. Finally, the problem of inter-channel nonlinear compensation is addressed within the context of 400 Gb/s (400G) superchannels for long-haul and ultra-long-haul transmission. Different superchannel configurations and nonlinear equalization strategies are experimentally assessed, demonstrating that inter-subcarrier nonlinear equalization can provide an enhanced signal reach while requiring only marginal added complexity.

A Study of the Robustness Against SEUs of Digital Circuits Implemented with FPGA DSPs

In this paper we present an experimental validation of the reliability increase of digital circuits implemented in XilinxTMFPGAs when they are implemented using the DSPs (Digital Signal Processors) that are available in the reconfigurable device. For this purpose, we have used a fault-injection platform developed by our research group, NESSY [1]. The presented experiments demonstrate that the probability of occurrence of a SEU effect is similar both in the circuits implemented with and without using embedded DSPs. However, the former are more efficient in terms of area usage, which leads to a decrease in the probability of a SEU occurrence.

Defibrillator

Defibrillator is a 16’41” musical work for solo performer, laptop computer and electric guitar. The electric guitar is processed in real-time by digital signal processing network in software, with gestural control provided by a foot-operated pedal board. --------- The work is informed by a range of ideas from the genres of electroacoustic music, western art music, popular music and cinematic sound. It seeks to fluidly cross and hybridise musical practices from these diverse sonic traditions and to develop a compositional language that draws upon multiple genres, but at the same time resists the ability to be located within a singular genre. Musical structures and sonic markers which form genre are ruptured at strategic levels of the musical structure in order to allow for a cross flow of concepts between genres. The process of rupture is facilitated by the practical implementation of music and sound reception theories into the compositional process. -------- The piece exhibits the by-products of a composer born into a media saturated environment, drawing on a range of musical and sonic traditions, actively seeking to explore the liminal space in between these traditions. The project stems from the author's research interests in locating points of connection between traditions of experimentation in diverse musical and sonic traditions arising from the broad uptake of media technologies in the early 20th century.

Application of higher order statistics/spectra in biomedical signals : a review

For many decades correlation and power spectrum have been primary tools for digital signal processing applications in the biomedical area. The information contained in the power spectrum is essentially that of the autocorrelation sequence; which is sufficient for complete statistical descriptions of Gaussian signals of known means. However, there are practical situations where one needs to look beyond autocorrelation of a signal to extract information regarding deviation from Gaussianity and the presence of phase relations. Higher order spectra, also known as polyspectra, are spectral representations of higher order statistics, i.e. moments and cumulants of third order and beyond. HOS (higher order statistics or higher order spectra) can detect deviations from linearity, stationarity or Gaussianity in the signal. Most of the biomedical signals are non-linear, non-stationary and non-Gaussian in nature and therefore it can be more advantageous to analyze them with HOS compared to the use of second order correlations and power spectra. In this paper we have discussed the application of HOS for different bio-signals. HOS methods of analysis are explained using a typical heart rate variability (HRV) signal and applications to other signals are reviewed.

Fast and robust stereo matching algorithms for mining automation

The mining environment, being complex, irregular and time varying, presents a challenging prospect for stereo vision. For this application, speed, reliability, and the ability to produce a dense depth map are of foremost importance. This paper evaluates a number of matching techniques for possible use in a stereo vision sensor for mining automation applications. Area-based techniques have been investigated because they have the potential to yield dense maps, are amenable to fast hardware implementation, and are suited to textured scenes. In addition, two non-parametric transforms, namely, the rank and census, have been investigated. Matching algorithms using these transforms were found to have a number of clear advantages, including reliability in the presence of radiometric distortion, low computational complexity, and amenability to hardware implementation.

An efficient online secondary path estimation for feedback active noise control systems

In practical cases for active noise control (ANC), the secondary path has usually a time varying behavior. For these cases, an online secondary path modeling method that uses a white noise as a training signal is required to ensure convergence of the system. The modeling accuracy and the convergence rate are increased when a white noise with a larger variance is used. However, the larger variance increases the residual noise, which decreases performance of the system and additionally causes instability problem to feedback structures. A sudden change in the secondary path leads to divergence of the online secondary path modeling filter. To overcome these problems, this paper proposes a new approach for online secondary path modeling in feedback ANC systems. The proposed algorithm uses the advantages of white noise with larger variance to model the secondary path, but the injection is stopped at the optimum point to increase performance of the algorithm and to prevent the instability effect of the white noise. In this approach, instead of continuous injection of the white noise, a sudden change in secondary path during the operation makes the algorithm to reactivate injection of the white noise to correct the secondary path estimation. In addition, the proposed method models the secondary path without the need of using off-line estimation of the secondary path. Considering the above features increases the convergence rate and modeling accuracy, which results in a high system performance. Computer simulation results shown in this paper indicate effectiveness of the proposed method.