362 research outputs found

    Analog‐to‐Digital Conversion for Cognitive Radio: Subsampling, Interleaving, and Compressive Sensing

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    This chapter explores different analog-to-digital conversion techniques that are suitable to be implemented in cognitive radio receivers. This chapter details the fundamentals, advantages, and drawbacks of three promising techniques: subsampling, interleaving, and compressive sensing. Due to their major maturity, subsampling- and interleaving-based systems are described in further detail, whereas compressive sensing-based systems are described as a complement of the previous techniques for underutilized spectrum applications. The feasibility of these techniques as part of software-defined radio, multistandard, and spectrum sensing receivers is demonstrated by proposing different architectures with reduced complexity at circuit level, depending on the application requirements. Additionally, the chapter proposes different solutions to integrate the advantages of these techniques in a unique analog-to-digital conversion process

    Digital background calibration algorithm and its FPGA implementation for timing mismatch correction of time-interleaved ADC

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    Sample time error can degrade the performance of time-interleaved analog to digital converters (TIADCs). A fully digital background algorithm is presented in this paper to estimate and correct the timing mismatch errors between four interleaved channels, together with its hardware implementation. The proposed algorithm provides low computation burden and high performance. It is based on the simplified representation of the coefficients of the Lagrange interpolator. Simulation results show that it can suppress error tones in all of the Nyquist band. Results show that, for a four-channel TIADC with 10-bit resolution, the proposed algorithm improves the signal to noise and distortion ratio (SNDR) and spurious-free dynamic range (SFDR) by 19.27 dB and 35.2 dB, respectively. This analysis was done for an input signal frequency of 0.09fs. In the case of an input signal frequency of 0.45fs, an improvement by 33.06 dB and 43.14 dB is respectively achieved in SNDR and SFDR. In addition to the simulation, the algorithm was implemented in hardware for real-time evaluation. The low computational burden of the algorithm allowed an FPGA implementation with a low logic resource usage and a high system clock speed (926.95 MHz for four channel algorithm implementation). Thus, the proposed architecture can be used as a post-processing algorithm in host processors for data acquisition systems to improve the performance of TIADC

    A 16-b 10Msample/s Split-Interleaved Analog to Digital Converter

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    This work describes the integrated circuit design of a 16-bit, 10Msample/sec, combination ‘split’ interleaved analog to digital converter. Time interleaving of analog to digital converters has been used successfully for many years as a technique to achieve faster speeds using multiple identical converters. However, efforts to achieve higher resolutions with this technique have been difficult due to the precise matching required of the converter channels. The most troublesome errors in these types of converters are gain, offset and timing differences between channels. The ‘split ADC’ is a new concept that allows the use of a deterministic, digital, self calibrating algorithm. In this approach, an ADC is split into two paths, producing two output codes from the same input sample. The difference of these two codes is used as the calibration signal for an LMS error estimation algorithm that drives the difference error to zero. The ADC is calibrated when the codes are equal and the output is taken as the average of the two codes. The ‘split’ ADC concept and interleaved architecture are combined in this IC design to form the core of a high speed, high resolution, and self-calibrating ADC system. The dual outputs are used to drive a digital calibration engine to correct for the channel mismatch errors. This system has the speed benefits of interleaving while maintaining high resolution. The hardware for the algorithm as well as the ADC can be implemented in a standard 0.25um CMOS process, resulting in a relatively inexpensive solution. This work is supported by grants from Analog Devices Incorporated (ADI) and the National Science Foundation (NSF)

    Concepts for smart AD and DA converters

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    This thesis studies the `smart' concept for application to analog-to-digital and digital-to-analog converters. The smart concept aims at improving performance - in a wide sense - of AD/DA converters by adding on-chip intelligence to extract imperfections and to correct for them. As the smart concept can correct for certain imperfections, it can also enable the use of more efficient architectures, thus yielding an additional performance boost. Chapter 2 studies trends and expectations in converter design with respect to applications, circuit design and technology evolution. Problems and opportunities are identfied, and an overview of performance criteria is given. Chapter 3 introduces the smart concept that takes advantage of the expected opportunities (described in chapter 2) in order to solve the anticipated problems. Chapter 4 applies the smart concept to digital-to-analog converters. In the discussed example, the concept is applied to reduce the area of the analog core of a current-steering DAC. It is shown that a sub-binary variable-radix approach reduces the area of the current-source elements substantially (10x compared to state-of-the-art), while maintaining accuracy by a self-measurement and digital pre-correction scheme. Chapter 5 describes the chip implementation of the sub-binary variable-radix DAC and discusses the experimental results. The results confirm that the sub-binary variable-radix design can achieve the smallest published current-source-array area for the given accuracy (12bit). Chapter 6 applies the smart concept to analog-to-digital converters, with as main goal the improvement of the overall performance in terms of a widely used figure-of-merit. Open-loop circuitry and time interleaving are shown to be key to achieve high-speed low-power solutions. It is suggested to apply a smart approach to reduce the effect of the imperfections, unintentionally caused by these key factors. On high-level, a global picture of the smart solution is proposed that can solve the problems while still maintaining power-efficiency. Chapter 7 deals with the design of a 500MSps open-loop track-and-hold circuit. This circuit is used as a test case to demonstrate the proposed smart approaches. Experimental results are presented and compared against prior art. Though there are several limitations in the design and the measurement setup, the measured performance is comparable to existing state-of-the-art. Chapter 8 introduces the first calibration method that counteracts the accuracy issues of the open-loop track-and-hold. A description of the method is given, and the implementation of the detection algorithm and correction circuitry is discussed. The chapter concludes with experimental measurement results. Chapter 9 introduces the second calibration method that targets the accuracy issues of time-interleaved circuits, in this case a 2-channel version of the implemented track-and-hold. The detection method, processing algorithm and correction circuitry are analyzed and their implementation is explained. Experimental results verify the usefulness of the method

    A 6-bit 2GS/s CMOS Time-Interleaved ADC for Analysis of Mixed-Signal Calibration Techniques

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    A 6-bit 2-GS/s time interleaved (TI) successive approximation register (SAR) analog-to-digital converter (ADC) is designed and fabricated in a 0.13 μm CMOS process. The architecture uses 8 time-interleaved track-and-hold amplifiers (THA), and 16 SARADC’s. Thechipincludes (i) a programmable delay cell array to adjust the interleaved sampling phase, and (ii) a 12 Gbps low voltage differential signaling (LVDS) interface. These blocks make the fabricated ADC an excellent platform to evaluate mixed-signal calibration techniques, which are of great interest for application in high-speed optical systems. Measurements of the fabricated ADC show 33.9 dB of peak signal-to-noise-and-distortion ratio (SNDR) and 192 mW of power consumption at 1.2 Vhttp://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=6820267Fil: Reyes, Benjamín. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas, Físicas y Naturales; Argentina.Fil: Tealdi, Lucas. Fundación Fulgor; Argentina.Fil: Paulina, German. Fundación Fulgor; Argentina.Fil: Labat, Emanuel. Fundación Fulgor; Argentina.Fil: Sánchez, Raúl. Fundación Fulgor; Argentina.Fil: Mandolesi, Pablo. Universidad Nacional del Sur. Grupo de Investigación en Sistemas Electrónicos y Electromecatrónicos (GISEE). Laboratorio de Micro y Nano Electrónica (LMNE); Argentina.Fil: Hueda, Mario. Universidad Nacional de Córdoba. Consejo Nacional de Investigaciones Científicas y Técnicas. Laboratorio de Comunicaciones Digitales; Argentina.Fil: Reyes, Benjamín. Consejo Nacional de Investigaciones Científicas y Técnicas. Laboratorio de Comunicaciones Digitales; Argentina.Telecomunicacione
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