A 35 Mb/s mixed-signal decision-feedback equalizer for disk drives in 2-μm CMOS

Brown, J. E.; Hurst, P.J.; Der, L.

doi:10.1109/4.535409

Cited by 14 publications

(5 citation statements)

References 33 publications

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“…Moreover, there are also calibration techniques specifically devised either for static (i.e., gain and offset) or dynamic errors (i.e., clock skew). For example, an alternative method for calibrating the static mismatches is to employ a DAC (digital-to-analog converter) with enough resolution to meet the requirements [37], using one of these DACs for each ADC in the interleaved structure. A common alternative to reduce the cost of the extra circuitry due to the added DACs is to implement the gain and offset calibrations after a FFT (fast Fourier transform) evaluation, via software, achieving the compensation from the study of the output spectrum [38].…”

Section: Cognitive Radiomentioning

confidence: 99%

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

Oya¹,

Chavero²,

Martı́n-Clemente³

2017

Cognitive Radio

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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 interleavingbased 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.

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Section: Cognitive Radiomentioning

confidence: 99%

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

Oya¹,

Chavero²,

Martı́n-Clemente³

2017

Cognitive Radio

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“…In fact, the forward equalizer of the MSE-DFE is given by mse (13) and the feedback equalizer of the MSE-DFE is given by mse (14) So this MSE-designed optimal PRML/VA detector can be related to the MSE-DFE as shown in the Fig. 8.…”

Section: Fdts/df Detectionmentioning

confidence: 99%

“…P ARTIAL response maximum likelihood detection using the Viterbi algorithm (PRML/VA) [9], decision feedback equalization (DFE) [10], [13], and fixed-delay tree search with decision feedback (FDTS/DF) [2] are the three sampling detection techniques most often considered for digital magnetic recording. In a previous paper, detailed performance analyses for each of these different detection techniques were provided and their relative performances in different situations were compared [11].…”

Section: Introductionmentioning

confidence: 99%

Performance and implementation of adaptive partial response maximum likelihood detection

Han

Spencer²

1998

IEEE Trans. Magn.

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Motivated by previous comparison work, a configuration for partial response maximum likelihood detection using the Viterbi algorithm (PRML/VA) detectors with adaptive target polynomials is examined. In this configuration, a mean-quared error decision feedback equalization (MSE-DFE) is used to adapt both the forward equalizer and the target channel for the Viterbi detector. The performance of this adaptive PRML/VA is analyzed and compared with other detection techniques. The issue of convergence speed is also studied.Index Terms-Adaptive target polynomials, analytical performance comparison, partial response maximum likelihood detection. ).Publisher Item Identifier S 0018-9464(98)06135-4. Fig. 1. Block diagram of the magnetic recording read channel.

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“…However, the implementation of FIR filter requires analog delay elements [3], which make them less practical, especially at higher data rates. On the other hand, alternatives to FIR filters include conventional high-frequency boost circuits that have a rational transfer function [4]. The locations of poles and zeros could be adjusted to fit a desired transfer function to arbitrary accuracy.…”

Section: The Proposed Equalizermentioning

confidence: 99%