An effective AMS Top-Down Methodology Applied to the Design of a Mixed-SignalUWB System-on-Chip

The design of Ultra Wideband (UWB) mixed-signal SoC for localization applications in wireless personal area networks is currently investigated by several researchers. The complexity of the design claims for effective top-down methodologies. We propose a layered approach based on VHDL-AMS for the first design stages and on an intelligent use of a circuit-level simulator for the transistor-level phase. We apply the latter just to one block at a time and wrap it within the system-level VHDL-AMS description. This method allows to capture the impact of circuit-level design choices and non-idealities on system performance. To demonstrate the effectiveness of the methodology we show how the refinement of the design affects specific UWB system parameters such as bit-error rate and localization estimations

A VHDL-AMS Simulation Environment for an UWB Impulse Radio Transceiver

Ultra-Wide-Band (UWB) communication based on the impulse radio paradigm is becoming increasingly popular. According to the IEEE 802.15 WPAN Low Rate Alternative PHY Task Group 4a, UWB will play a major role in localization applications, due to the high time resolution of UWB signals which allow accurate indirect measurements of distance between transceivers. Key for the successful implementation of UWB transceivers is the level of integration that will be reached, for which a simulation environment that helps take appropriate design decisions is crucial. Owing to this motivation, in this paper we propose a multiresolution UWB simulation environment based on the VHDL-AMS hardware description language, along with a proper methodology which helps tackle the complexity of designing a mixed-signal UWB System-on-Chip. We applied the methodology and used the simulation environment for the specification and design of an UWB transceiver based on the energy detection principle. As a by-product, simulation results show the effectiveness of UWB in the so-called ranging application, that is the accurate evaluation of the distance between a couple of transceivers using the two-way-ranging metho

A Mixed-Signal Demodulator for a Low-Complexity IR-UWB Receiver: Methodology, Simulation and Design

This works presents an integrated 0.18μm CMOS 2-PPM demodulator based on a switched capacitor network for an Energy Detection Impulse-Radio UWB receiver. The circuit has been designed using a top-down methodology that allows to discover the impact of low-level non-idealities on system-level performance. Through the use of a mixed signal simulation environment, performance figures have been obtained which helped evaluate the influence at system-level of the non-idealities of the most critical block. Results show that the circuit allows the replacement of the ADC typically employed in Energy Detection receivers and provides about infinite equivalent quantization resolution. The demodulator achieves 190 pJ/bit at 1.8V

Simulation and Design of an UWB Imaging System for Breast Cancer Detection

Breast cancer is the most frequently diagnosed cancer among women. In recent years, the mortality rate due to this disease is greatly decreased thanks to both enormous progress in cancer research, and screening campaigns which have allowed the increase in the number of early diagnoses of the disease. In fact, if the tumor is identied in its early stage, e.g. when it has a diameter of less than one centimeter, the possibility of a cure can reach 93%. However, statistics show that more young aged women are suered breast cancer. The goal of screening exams for early breast cancer detection is to nd cancers before they start to cause symptoms. Regular mass screening of all women at risk is a good option to achieve that. Instead of meeting very high diagnostic standards, it is expected to yield an early warning, not a denitive diagnosis. In the last decades, X-ray mammography is the most ecient screening technique. However, it uses ionizing radiation and, therefore, should not be used for frequent check-ups. Besides, it requires signicant breast compression, which is often painful. In this scenario many alternative technologies were developed to overcome the limitations of mammography. Among these possibilities, Magnetic Resonance Imaging (MRI) is too expensive and time-consuming, Ultrasound is considered to be too operatordependent and low specicity, which are not suitable for mass screening. Microwave imaging techniques, especially Ultra WideBand (UWB) radar imaging, is the most interesting one. The reason of this interest relies on the fact that microwaves are non-ionizing thus permitting frequent examinations. Moreover, it is potentially lowcost and more ecient for young women. Since it has been demonstrated in the literatures that the dielectric constants between cancerous and healthy tissues are quite dierent, the technique consists in illuminating these biological tissues with microwave radiations by one or more antennas and analyzing the re ected signals. An UWB imaging system consists of transmitters, receivers and antennas for the RF part, the transmission channel and of a digital backend imaging unit for processing the received signals. When an UWB pulse strikes the breast, the pulse is re ected due to the dielectric discontinuity in tissues, the bigger the dierence, the bigger the backscatter. The re ected signals are acquired and processed to create the energy maps. This thesis aims to develop an UWB system at high resolution for the detection of carcinoma breast already in its initial phase. To favor the adoption of this method in screening campaigns, it is necessary to replace the expensive and bulky RF instrumentation used so far with ad-hoc designed circuits and systems. In order to realize that, at the very beginning, the overall system environment must be built and veried, which mainly consists of the transmission channel{the breast model and the imaging unit. The used transmission channel data come from MRI of the prone patient. In order to correctly use this numerical model, a simulator was built, which was implemented in Matlab, according to the Finite-Dierence-Time- Domain (FDTD) method. FDTD algorithm solves the electric and magnetic eld both in time and in space, thus, simulates the propagation of electromagnetic waves in the breast model. To better understand the eect of the system non-idealities, two 2D breast models are investigated, one is homogeneous, the other is heterogeneous. Moreover, the modeling takes into account all critical aspects, including stability and medium dispersion. Given the types of tissues under examination, the frequency dependence of tissue dielectric properties is incorporated into wideband FDTD simulations using Debye dispersion parameters. A performed further study is in the implementation of the boundary conditions. The Convolution Perfectly Matched Layer (CPML) is used to implement the absorbing boundaries. The objective of the imaging unit is to obtain an energy map representing the amount of energy re ected from each point of the breast, by recombining the sampled backscattered signals. For this purpose, the study has been carried out on various beamforming in the literature. The basic idea is called as "delay and sum", which is to align the received signals in such a way as to focus a given point in space and then add up all the contributions, so as to obtain a constructive interference at that point if this is a diseased tissue. In this work, Microwave Imaging via Space Time (MIST) Beamforming algorithm is applied, which is based on the above principle and add more elaborations of the signals in order to make the algorithm less sensitive to propagation phenomena in the medium and to the non-idealities of the system. It is divided into two distinct steps: the rst step, called SKin Artifact Removal (SKAR), takes care of removing the contributions from the signal caused by the direct path between the transmitter and receiver, the re ection of skin, as they are orders of magnitude higher compared to the re ections caused by cancers; the second step, which is BEAmForming (BEAF), performs the algorithm of reconstruction by forming a weighted combination of time delayed version of the calibrated re ected signals. As discussed above, more attention must be paid on the implementation of the ad-hoc integration circuits. In this scenario, due to the strict requirements on the RF receiver component, two dierent approaches of the implementation of the RF front-end, Direct Conversion (DC) receiver and Coherent Equivalent Time Sampling (CETS) receiver are compared. They are modeled behaviorally and the eects of various impairments, such as thermal, jitter, and phase noise, as well as phase inaccuracies, non-linearity, ADC quantization noise and distortion, on energy maps and on quantitative metrics such as SCR and SMR are evaluated. Dierential Gaussian pulse is chosen as the exciting source. Results show that DC receiver performs higher sensitivity to phase inaccuracies, which makes it less robust than the CETS receiver. Another advantage of the CETS receiver is that it can work in time domain with UWB pulses, other than in frequency domain with stepped frequency continuous waves like the DC one, which reduces the acquisition time without impacting the performance. Based on the results of the behavioral simulations, low noise amplier (LNA) and Track and Hold Amplier (THA) can be regarded as the most critical parts for the proposed CETS receiver, as well as the UWB antenna. This work therefore focuses on their hardware implementations. The LNA, which shows critical performance limitation at bandwidth and noise gure of receiver, has been developed based on common-gate conguration. And the THA based on Switched Source Follower (SSF) scheme has been presented and improved to obtain high input bandwidth, high sampling rate, high linearity and low power consumption. LNA and THA are implemented in CMOS 130nm technology and the circuit performance evaluation has been taken place separately and together. The small size UWB wide-slot antenna is designed and simulated in HFSS. Finally, in order to evaluate the eect of the implemented transistor level components on system performance, a multi-resolution top-down system methodology is applied. Therfore, the entire ow is analyzed for dierent levels of the RF frontend. Initially the system components are described behaviorally as ideal elements. The main activity consists in the analysis and development of the entire frontend system, observing and complementing each other blocks in a single ow simulation, clear and well-dened in its various interfaces. To achieve that the receiver is modeled and analyzed using VHDL-AMS language block by block, moreover, the impact of quantization, noise, jitter, and non-linearity is also evaluated. At last, the behavioral description of antenna, LNA and THA is replaced with a circuit-level one without changing the rest of the system, which permits a system-level assessment of low-level issues

Learning Approaches to Analog and Mixed Signal Verification and Analysis

The increased integration and interaction of analog and digital components within a system has amplified the need for a fast, automated, combined analog, and digital verification methodology. There are many automated characterization, test, and verification methods used in practice for digital circuits, but analog and mixed signal circuits suffer from long simulation times brought on by transistor-level analysis. Due to the substantial amount of simulations required to properly characterize and verify an analog circuit, many undetected issues manifest themselves in the manufactured chips. Creating behavioral models, a circuit abstraction of analog components assists in reducing simulation time which allows for faster exploration of the design space. Traditionally, creating behavioral models for non-linear circuits is a manual process which relies heavily on design knowledge for proper parameter extraction and circuit abstraction. Manual modeling requires a high level of circuit knowledge and often fails to capture critical effects stemming from block interactions and second order device effects. For this reason, it is of interest to extract the models directly from the SPICE level descriptions so that these effects and interactions can be properly captured. As the devices are scaled, process variations have a more profound effect on the circuit behaviors and performances. Creating behavior models from the SPICE level descriptions, which include input parameters and a large process variation space, is a non-trivial task. In this dissertation, we focus on addressing various problems related to the design automation of analog and mixed signal circuits. Analog circuits are typically highly specialized and fined tuned to fit the desired specifications for any given system reducing the reusability of circuits from design to design. This hinders the advancement of automating various aspects of analog design, test, and layout. At the core of many automation techniques, simulations, or data collection are required. Unfortunately, for some complex analog circuits, a single simulation may take many days. This prohibits performing any type of behavior characterization or verification of the circuit. This leads us to the first fundamental problem with the automation of analog devices. How can we reduce the simulation cost while maintaining the robustness of transistor level simulations? As analog circuits can vary vastly from one design to the next and are hardly ever comprised of standard library based building blocks, the second fundamental question is how to create automated processes that are general enough to be applied to all or most circuit types? Finally, what circuit characteristics can we utilize to enhance the automation procedures? The objective of this dissertation is to explore these questions and provide suitable evidence that they can be answered. We begin by exploring machine learning techniques to model the design space using minimal simulation effort. Circuit partitioning is employed to reduce the complexity of the machine learning algorithms. Using the same partitioning algorithm we further explore the behavior characterization of analog circuits undergoing process variation. The circuit partitioning is general enough to be used by any CMOS based analog circuit. The ideas and learning gained from behavioral modeling during behavior characterization are used to improve the simulation through event propagation, input space search, complexity and information measurements. The reduction of the input space and behavioral modeling of low complexity, low information primitive elements reduces the simulation time of large analog and mixed signal circuits by 50-75%. The method is extended and applied to assist in analyzing analog circuit layout. All of the proposed methods are implemented on analog circuits ranging from small benchmark circuits to large, highly complex and specialized circuits. The proposed dependency based partitioning of large analog circuits in the time domain allows for fast identification of highly sensitive transistors as well as provides a natural division of circuit components. Modeling analog circuits in the time domain with this partitioning technique and SVM learning algorithms allows for very fast transient behavior predictions, three orders of magnitude faster than traditional simulators, while maintaining 95% accuracy. Analog verification can be explored through a reduction of simulation time by utilizing the partitions, information and complexity measures, and input space reduction. Behavioral models are created using supervised learning techniques for detected primitive elements. We will show the effectiveness of the method on four analog circuits where the simulation time is decreased by 55-75%. Utilizing the reduced simulation method, critical nodes can be found quickly and efficiently. The nodes found using this method match those found by an experienced layout engineer, but are detected automatically given the design and input specifications. The technique is further extended to find the tolerance of transistors to both process variation and power supply fluctuation. This information allows for corrections in layout overdesign or guidance in placing noise reducing components such as guard rings or decoupling capacitors. The proposed approaches significantly reduce the simulation time required to perform the tasks traditionally, maintain high accuracy, and can be automated