A 0.18 μm CMOS low noise, highly linear continuous-time seventh-order elliptic low-pass filter

This paper presents a fast procedure for the system-level evaluation of noise and distortion in continuous-time integrated filters. The presented approach is based on Volterra's series theory and matrix algebra manipulation. This procedure has been integrated in a constrained optimization routine to improve the dynamic range of the filter while keeping the area and power consumption at a minimum. The proposed approach is demonstrated with the design, from system- to physical-level, of a seventh-order low-pass continuous-time elliptic filter for a high-performance broadband power-line communication receiver. The filter shows a nominal cut-off frequency of fc = 34MHz, less than 1dB ripple in the pass-band, and a maximum stop-band rejection of 65dB. Additionally, the filter features 12dB programmable boost in the pass-band to counteract high frequency components attenuation. Taking into account its wideband transfer characteristic, the filter has been implemented using G m-C techniques. The basic building block of its structure, the transconductor, uses a source degeneration topology with local feedback for linearity improving and shows a worst-case intermodulation distortion of -70 dB for two tones close to the passband edge, separated by 1MHz, with 70mV of amplitude. The filter combines very low noise (peak root spectral noise density below 56nV/√Hz) and high linearity (more than 64dB of MTPR for a DMT signal of 0.5Vpp amplitude) properties. The filter has been designed in a 0.18μm CMOS technology and it is compliant with industrial operation conditions (-40 to 85°C temperature variation and ±5% power supply deviation). The filter occupies 13mm2 and exhibits a typical power consumption of 450 mW from a 1.8V voltage supply.Ministerio de Ciencia y Tecnología TIC2003-0235

Engineering Education and Research Using MATLAB

MATLAB is a software package used primarily in the field of engineering for signal processing, numerical data analysis, modeling, programming, simulation, and computer graphic visualization. In the last few years, it has become widely accepted as an efficient tool, and, therefore, its use has significantly increased in scientific communities and academic institutions. This book consists of 20 chapters presenting research works using MATLAB tools. Chapters include techniques for programming and developing Graphical User Interfaces (GUIs), dynamic systems, electric machines, signal and image processing, power electronics, mixed signal circuits, genetic programming, digital watermarking, control systems, time-series regression modeling, and artificial neural networks

Optics for AI and AI for Optics

Artificial intelligence is deeply involved in our daily lives via reinforcing the digital transformation of modern economies and infrastructure. It relies on powerful computing clusters, which face bottlenecks of power consumption for both data transmission and intensive computing. Meanwhile, optics (especially optical communications, which underpin today’s telecommunications) is penetrating short-reach connections down to the chip level, thus meeting with AI technology and creating numerous opportunities. This book is about the marriage of optics and AI and how each part can benefit from the other. Optics facilitates on-chip neural networks based on fast optical computing and energy-efficient interconnects and communications. On the other hand, AI enables efficient tools to address the challenges of today’s optical communication networks, which behave in an increasingly complex manner. The book collects contributions from pioneering researchers from both academy and industry to discuss the challenges and solutions in each of the respective fields

Teaching old sensors New tricks: archetypes of intelligence

In this paper a generic intelligent sensor software architecture is described which builds upon the basic requirements of related industry standards (IEEE 1451 and SEVA BS- 7986). It incorporates specific functionalities such as real-time fault detection, drift compensation, adaptation to environmental changes and autonomous reconfiguration. The modular based structure of the intelligent sensor architecture provides enhanced flexibility in regard to the choice of specific algorithmic realizations. In this context, the particular aspects of fault detection and drift estimation are discussed. A mixed indicative/corrective fault detection approach is proposed while it is demonstrated that reversible/irreversible state dependent drift can be estimated using generic algorithms such as the EKF or on-line density estimators. Finally, a parsimonious density estimator is presented and validated through simulated and real data for use in an operating regime dependent fault detection framework

Identification of the dynamic characteristics of nonlinear structures

Imperial Users onl

ワイヤレス通信のための先進的な信号処理技術を用いた非線形補償法の研究

The inherit nonlinearity in analogue front-ends of transmitters and receivers have had primary impact on the overall performance of the wireless communication systems, as it gives arise of substantial distortion when transmitting and processing signals with such circuits. Therefore, the nonlinear compensation (linearization) techniques become essential to suppress the distortion to an acceptable extent in order to ensure sufficient low bit error rate. Furthermore, the increasing demands on higher data rate and ubiquitous interoperability between various multi-coverage protocols are two of the most important features of the contemporary communication system. The former demand pushes the communication system to use wider bandwidth and the latter one brings up severe coexistence problems. Having fully considered the problems raised above, the work in this Ph.D. thesis carries out extensive researches on the nonlinear compensations utilizing advanced digital signal processing techniques. The motivation behind this is to push more processing tasks to the digital domain, as it can potentially cut down the bill of materials (BOM) costs paid for the off-chip devices and reduce practical implementation difficulties. The work here is carried out using three approaches: numerical analysis & computer simulations; experimental tests using commercial instruments; actual implementation with FPGA. The primary contributions for this thesis are summarized as the following three points: 1) An adaptive digital predistortion (DPD) with fast convergence rate and low complexity for multi-carrier GSM system is presented. Albeit a legacy system, the GSM, however, has a very strict requirement on the out-of-band emission, thus it represents a much more difficult hurdle for DPD application. It is successfully implemented in an FPGA without using any other auxiliary processor. A simplified multiplier-free NLMS algorithm, especially suitable for FPGA implementation, for fast adapting the LUT is proposed. Many design methodologies and practical implementation issues are discussed in details. Experimental results have shown that the DPD performed robustly when it is involved in the multichannel transmitter. 2) The next generation system (5G) will unquestionably use wider bandwidth to support higher throughput, which poses stringent needs for using high-speed data converters. Herein the analog-to-digital converter (ADC) tends to be the most expensive single device in the whole transmitter/receiver systems. Therefore, conventional DPD utilizing high-speed ADC becomes unaffordable, especially for small base stations (micro, pico and femto). A digital predistortion technique utilizing spectral extrapolation is proposed in this thesis, wherein with band-limited feedback signal, the requirement on ADC speed can be significantly released. Experimental results have validated the feasibility of the proposed technique for coping with band-limited feedback signal. It has been shown that adequate linearization performance can be achieved even if the acquisition bandwidth is less than the original signal bandwidth. The experimental results obtained by using LTE-Advanced signal of 320 MHz bandwidth are quite satisfactory, and to the authors’ knowledge, this is the first high-performance wideband DPD ever been reported. 3) To address the predicament that mobile operators do not have enough contiguous usable bandwidth, carrier aggregation (CA) technique is developed and imported into 4G LTE-Advanced. This pushes the utilization of concurrent dual-band transmitter/receiver, which reduces the hardware expense by using a single front-end. Compensation techniques for the respective concurrent dual-band transmitter and receiver front-ends are proposed to combat the inter-band modulation distortion, and simultaneously reduce the distortion for the both lower-side band and upper-side band signals.電気通信大学201

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

Bacterial Foraging Based Channel Equalizers

A channel equalizer is one of the most important subsystems in any digital communication receiver. It is also the subsystem that consumes maximum computation time in the receiver. Traditionally maximum-likelihood sequence estimation (MLSE) was the most popular form of equalizer. Owing to non-stationary characteristics of the communication channel MLSE receivers perform poorly. Under these circumstances ‘Maximum A-posteriori Probability (MAP)’ receivers also called Bayesian receivers perform better. Natural selection tends to eliminate animals with poor “foraging strategies” and favor the propagation of genes of those animals that have successful foraging strategies since they are more likely to enjoy reproductive success. After many generations, poor foraging strategies are either eliminated or shaped into good ones (redesigned). Logically, such evolutionary principles have led scientists in the field of “foraging theory” to hypothesize that it is appropriate to model the activity of foraging as an optimization process. This thesis presents an investigation on design of bacterial foraging based channel equalizer for digital communication. Extensive simulation studies shows that the performance of the proposed receiver is close to optimal receiver for variety of channel conditions. The proposed receiver also provides near optimal performance when channel suffers from nonlinearities