206 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

    Time-Interleaved Analog-to-Digital Converter (TIADC) Compensation Using Multichannel Filters

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    Published methods that employ a filter bank for compensating the timing and bandwidth mismatches of an M-channel time-interleaved analog-to-digital converter (TIADC) were developed based on the fact that each sub-ADC channel is a downsampled version of the analog input. The output of each sub-ADC is filtered in such a way that, when all the filter outputs are summed, the aliasing components are minimized. If each channel of the filter bank has N coefficients, the optimization of the coefficients requires computing the inverse of an MN times MN matrix if the weighted least squares (WLS) technique is used as the optimization tool. In this paper, we present a multichannel filtering approach for TIADC mismatch compensation. We apply the generalized sampling theorem to directly estimate the ideal output of each sub-ADC using the outputs of all the sub-ADCs. If the WLS technique is used as the optimization tool, the dimension of the matrix to be inversed is N times N. For the same number of coefficients (and also the same spurious component performance given sufficient arithmetic precision), our technique is computationally less complex and more robust than the filter-bank approach. If mixed integer linear programming is used as the optimization tool to produce filters with coefficient values that are integer powers of two, our technique produces a saving in computing resources by a factor of approximately (100.2N(M- 1)/(M-1) in the TIADC filter design.published_or_final_versio

    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

    Design of Energy-Efficient A/D Converters with Partial Embedded Equalization for High-Speed Wireline Receiver Applications

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    As the data rates of wireline communication links increases, channel impairments such as skin effect, dielectric loss, fiber dispersion, reflections and cross-talk become more pronounced. This warrants more interest in analog-to-digital converter (ADC)-based serial link receivers, as they allow for more complex and flexible back-end digital signal processing (DSP) relative to binary or mixed-signal receivers. Utilizing this back-end DSP allows for complex digital equalization and more bandwidth-efficient modulation schemes, while also displaying reduced process/voltage/temperature (PVT) sensitivity. Furthermore, these architectures offer straightforward design translation and can directly leverage the area and power scaling offered by new CMOS technology nodes. However, the power consumption of the ADC front-end and subsequent digital signal processing is a major issue. Embedding partial equalization inside the front-end ADC can potentially result in lowering the complexity of back-end DSP and/or decreasing the ADC resolution requirement, which results in a more energy-effcient receiver. This dissertation presents efficient implementations for multi-GS/s time-interleaved ADCs with partial embedded equalization. First prototype details a 6b 1.6GS/s ADC with a novel embedded redundant-cycle 1-tap DFE structure in 90nm CMOS. The other two prototypes explain more complex 6b 10GS/s ADCs with efficiently embedded feed-forward equalization (FFE) and decision feedback equalization (DFE) in 65nm CMOS. Leveraging a time-interleaved successive approximation ADC architecture, new structures for embedded DFE and FFE are proposed with low power/area overhead. Measurement results over FR4 channels verify the effectiveness of proposed embedded equalization schemes. The comparison of fabricated prototypes against state-of-the-art general-purpose ADCs at similar speed/resolution range shows comparable performances, while the proposed architectures include embedded equalization as well

    A 0.9-Nyquist-Band Digital Timing Mismatch Correction for Time-Interleaved ADCs Achieving Delay Tuning Range of 0.12-Sample-Period

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    Time-interleaved analog-to-digital converters (TIADC) require channel matching in terms of offset, gain, and sampling clock skew to achieve best data conversion performance. Conventionally, correction of skew mismatch is realized with analog delay lines, making it challenging for high-speed ADC designs to achieve fine delay resolution over wide tuning range while maintaining low clock jitter. Digital skew correction allows greater flexibility than analog solutions, but is hindered by a significant hardware footprint. This paper demonstrates digital filter-based timing skew correction approach suitable for on-chip implementation. In a 10-bit 8-channel TI-ADC the proposed structure corrects mismatch magnitudes up to 0.12 sample period across 0.9 Nyquist band while requiring only 65% hardware of similar architectures of equivalent performance. The presented digital circuit uses reduced combinational paths and operates at a clock rate of single ADC channel, making it applicable for digitally-assisted high-speed TI-ADCs.acceptedVersionPeer reviewe

    New iterative framework for frequency response mismatch correction in time-interleaved ADCs: Design and performance analysis

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    This paper proposes a new iterative framework for the correction of frequency response mismatch in time-interleaved analog-to-digital converters. Based on a general time-varying linear system model for the mismatch, we treat the reconstruction problem as a linear inverse problem and establish a flexible iterative framework for practical implementation. It encumbrances a number of efficient iterative correction algorithms and simplifies their design, implementation, and performance analysis. In particular, an efficient Gauss-Seidel iteration is studied in detail to illustrate how the correction problem can be solved iteratively and how the proposed structure can be efficiently implemented using Farrow-based variable digital filters with few general-purpose multipliers. We also study important issues, such as the sufficient convergence condition and reconstructed signal spectrum, derive new lower bound of signal-to-distortion-and-noise ratio in order to ensure stable operation, and predict the performance of the proposed structure. Furthermore, we propose an extended iterative structure, which is able to cope with systems involving more than one type of mismatches. Finally, the theoretical results and the effectiveness of the proposed approach are validated by means of computer simulations. © 2011 IEEE.published_or_final_versio
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