A PRML system for digital magnetic recording

Cideciyan, R.D.; Dolivo, F.; Hermann, R.; Hirt, W.; Schott, W.

doi:10.1109/49.124468

Cited by 264 publications

(90 citation statements)

References 36 publications

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“…2 and based on a matched filter h(−t), a sampler at symbol rate, a PR4 equalizer [18] and linear prediction applied to colored Gaussian thermal noise and transition noise. We compare its performance with that obtained using oversampling and linear prediction applied to transition noise.…”

Section: A Mmspe Analysismentioning

confidence: 99%

Oversampled Detector for Transition-Noise-Limited Digital Storage Systems

Pighi

Amadei

Raheli

2006

2006 IEEE International Conference on Communications

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Abstract-In the last decade, significant research has been performed on detection algorithms capable of mitigating the effects of colored Gaussian thermal noise and transition noise in digital storage systems. In this paper, we present a new Maximum A-Posteriori Probability (MAP) sequence detection scheme based on oversampling and linear prediction. The proposed solution improves the Bit Error Rate (BER) performance with respect to conventional systems and makes the detector more robust against transition noise. The results obtained for a magnetic channel can be also extended to optical storage systems.

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Section: A Mmspe Analysismentioning

confidence: 99%

Oversampled Detector for Transition-Noise-Limited Digital Storage Systems

Pighi

Amadei

Raheli

2006

2006 IEEE International Conference on Communications

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“…In this technique, spectral shaping of read back signal is performed using a combination of a continuous time and a digital finite-impulse response (FIR) filter [2]. Using the Viterbi algorithm, the most likely symbol sequence is detected on a trellis which results due to the spectral shaping operation.…”

Section: Introductionmentioning

confidence: 99%

Low power techniques and design tradeoffs in adaptive FIR filtering for PRML read channels

Khurshid

Staszewski

Balsara³

2000

ISLPED'00: Proceedings of the 2000 International Symposium on Low Power Electronics and Design (Cat. No.00TH8514)

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In this paper, we describe area and power reduction techniques for a low-latency adaptive finite-impulse response filter for magnetic recording read channel applications. Various techniques are used to reduce area and power dissipation while speed remains as the main performance criterion for the target application. A parallel transposed direct form architecture operates on real-time input data samples and employs a fast, low-area multiplier based on selection of radix-8 pre-multiplied coefficients in conjunction with one-hot encoded bus leading to a very compact layout and reduced power dissipation. Area, speed and power comparisons with other lowpower implementation options are also shown. The proposed filter has been fabricated using a 0.18 m L-effective CMOS technology and operates at 550 MSamples/s.

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“…Such systems are known as partial response maximumlikelihood (PRML) systems. PRML systems are widely used in digital recording [3] to combat the extensive ISI, caused by the channel, especially at high recording densities.…”

Section: Introductionmentioning

confidence: 99%

Near-Minimum Bit-Error Rate Equalizer Adaptation for PRML Systems

Riani

Beneden

Bergmans

et al. 2007

IEEE Trans. Commun.

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Abstract-Receivers for partial response maximum-likelihood systems typically use a linear equalizer followed by a Viterbi detector. The equalizer tries to confine the channel intersymbol interferenceto a short span in order to limit the implementation complexity of the Viterbi detector. Equalization is usually made adaptive in order to compensate for channel variations. Conventional adaptation techniques, e.g., LMS, are, in general, suboptimal in terms of bit-error rate (BER). In this paper, we present a new equalizer adaptation algorithm that seeks to minimize the BER at the Viterbi detector output. The algorithm extracts information from the sequenced amplitude margin (SAM) histogram and incorporates a selection mechanism that focuses adaptation on particular data and noise realizations. The selection mechanism is based on the reliability of the add compare select (ACS) operations in the Viterbi detector. From a complexity standpoint, the algorithm is essentially as simple as the conventional LMS algorithm. Moreover, we present a further simplified version of the algorithm that does not require any hardware multiplications. Simulation results, for an idealized optical storage channel, confirm a substantial performance improvement relative to existing adaptation algorithms.Index Terms-Adaptive equalizers, intersymbol interference, partial response signaling, sequenced amplitude margin (SAM), Viterbi detection.

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A PRML system for digital magnetic recording

Cited by 264 publications

References 36 publications

Oversampled Detector for Transition-Noise-Limited Digital Storage Systems

Oversampled Detector for Transition-Noise-Limited Digital Storage Systems

Low power techniques and design tradeoffs in adaptive FIR filtering for PRML read channels

Near-Minimum Bit-Error Rate Equalizer Adaptation for PRML Systems

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