Noise-predictive Maximum-likelihood Detection Research Articles

123 Gbit/in<sup>2</sup> Recording Areal Density on Barium Ferrite Tape

The recording performance of a prototype magnetic tape based on perpendicularly oriented barium ferrite particles is investigated using an enhanced field tape write head and a 90 nm wide giant-magnetoresistive reader. A linear density of 680 kbits/in with a postdetection byte-error rate (BER) <;3.2e-2 is demonstrated based on recorded data processed by a software read channel with noise-predictive maximum likelihood detection. With this detector error rate, a user BER of <;1e-20 can be achieved by means of product error correction coding and iterative decoding. Several advances in the area of track-following servo control are also presented. Specifically, we describe a new timing-based servo pattern, which in combination with an optimized servo channel enables the generation of position estimates with nanoscale resolution and a high update rate. Track-following experiments are performed using an experimental low-noise tape transport, a prototype high-bandwidth actuator, and a set of speed-optimized H-infinity-based track-following controllers. Combining these technologies, we demonstrate a position-error signal (PES) with a standard deviation of 5.9 nm or less over a tape speed range of 1.23-4.08 m/s. This magnitude of PES in combination with a 90 nm wide reader allows operation with 140 nm wide tracks. Combined with a linear density of 680 kbits/in, this leads to an equivalent areal density of 123 Gbits/in <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> .

Generalized Partial Response Equalization and Data-Dependent Noise Predictive Signal Detection Over Media Models for TDMR

Two-dimensional magnetic recording (2-D TDMR) is an emerging technology that aims to achieve areal densities as high as 10 Tb/in2 using sophisticated 2-D signal-processing algorithms. High areal densities are achieved by reducing the size of a bit to the order of the size of magnetic grains, resulting in severe 2-D intersymbol interference (ISI). Jitter noise due to irregular grain positions on the magnetic medium is more pronounced at these areal densities. Therefore, a viable read-channel architecture for TDMR requires 2-D signal-detection algorithms that can mitigate 2-D ISI and combat noise comprising jitter and electronic components. Partial response maximum likelihood (PRML) detection scheme allows controlled ISI as seen by the detector. With the controlled and reduced span of 2-D ISI, the PRML scheme overcomes practical difficulties such as Nyquist rate signaling required for full response 2-D equalization. As in the case of 1-D magnetic recording, jitter noise can be handled using a data-dependent noise-prediction (DDNP) filter bank within a 2-D signal-detection engine. The contributions of this paper are threefold: 1) we empirically study the jitter noise characteristics in TDMR as a function of grain density using a Voronoi-based granular media model; 2) we develop a 2-D DDNP algorithm to handle the media noise seen in TDMR; and 3) we also develop techniques to design 2-D separable and nonseparable targets for generalized partial response equalization for TDMR. This can be used along with a 2-D signal-detection algorithm. The DDNP algorithm is observed to give a 2.5 dB gain in SNR over uncoded data compared with the noise predictive maximum likelihood detection for the same choice of channel model parameters to achieve a channel bit density of 1.3 Tb/in2 with media grain center-to-center distance of 10 nm. The DDNP algorithm is observed to give $\sim$ 10% gain in areal density near 5 grains/bit. The proposed signal-processing framework can broadly scale to various TDMR realizations and areal density points.

Adaptive noise-predictive maximum-likelihood (NPML) data detection for magnetic tape storage systems

Advanced data detection will be one of the key enablers to achieving the very high areal recording densities of future tape storage systems. Departing from the partial-response maximum-likelihood (PRML)-based read channel design traditionally used in tape systems, this paper describes noise-predictive maximum-likelihood (NPML) detection, which is a technique that has been known for many years in the hard-disk-drive industry but has been introduced for the first time in the tape storage industry in IBM tape drives. In the NPML read channel design, the readback signals are conditioned prior to data detection so that their noise components are statistically decorrelated and reduced in power. This paper describes the basic principles of NPML detection and its application to tape systems in the form of a 16-state detector. It is argued that, because of the inherent variability of the recording channel characteristics in tape drives, fully adaptive NPML detection needs to be realized in order to optimize detection performance. Actual readback waveforms of data recorded on metal particulate as well as barium-ferrite particulate tape media are used to illustrate the error rate performance achieved by 16-state and 32-state NPML detectors. It is shown that, under realistic worst-case channel conditions, a 16-state NPML detector could offer an improvement in error rate after an error-correcting code of approximately two orders of magnitude.

6.7 ${\hbox{Gb/in}}^{2}$ Recording Areal Density on Barium Ferrite Tape

We investigated the performance of a barium ferrite tape medium in linear tape recording, using a giant-magnetoresistive read head of 0.5 mum track width. A linear density of 400 kbpi with an error rate of 6 times 10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-5</sup> was demonstrated based on measured recording data and a simulated channel with advanced noise predictive maximum likelihood detection schemes. Using a timing-based servo format that reduces the position error signal (PES) due to medium jitter and servo-writer velocity variations, we achieved a PES of 0.07 mum standard deviation and a maximum PES (in a 10-s interval) of 0.35 mum. This PES magnitude allows the writing and reading of 1.5-mum tracks at 400 kbpi, for an equivalent areal density of 6.7 Gb/in <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> .

Adaptive noise-predictive maximum likelihood detection using tentative decision and partial path selection

We present a noise-predictive maximum likelihood (NPML) detection scheme considering both low complexity and effective adaptation. First, for achieving low complexity, we exploit the modified Viterbi decoding method that partially selects the survival paths. The partial path selection method limits the number of selected paths among all survival paths at the Viterbi trellis and selects a path with minimum metric among the selected paths while the original Viterbi algorithm considers all paths and decides the best path. Next, for effective adaptation, we propose an adaptive NPML scheme exploiting a tentative decision value of the Viterbi decoding process.

Noise-Predictive Viterbi Detector with Pattern-Dependent Distortion Canceller for High-Density Optical Recording

We propose noise-predictive maximum-likelihood (NPML) detection with a pattern-dependent distortion canceller (PDDC) to cancel nonlinear distortion. NPML detection and NPML/PDDC detection were applied to a Blu-ray disc with a capacity of 27 Gbytes. The detection performance was investigated. And the results are reported. Both the NPML detector and the NPML/PDDC detector lower bit error rate (BER), and improve the radial-tilt margin and spherical-aberration margin. Only the NPML/PDDC detector could improve tangential-tilt margin, however.

Noise predictive maximum likelihood detection combined with parity-based post-processing

The performance of magnetic recording systems that include conventional modulation codes combined with multiple parity bits is studied. Various performance measures, including bit error rate at the output of time inverse precoder, byte error probability at the input of the Reed-Solomon (RS) decoder and sector error rate, are used to evaluate the performance of various coding/detection schemes. Suboptimum detection/decoding schemes consisting of a 16-state noise-predictive maximum-likelihood (NPML) detector followed by parity-based noise-predictive post-processing, and maximum-likelihood sequence detection/decoding on the combined channel/parity trellis are considered. For conventional modulation codes, it is shown that although the dual-parity post-processor gains 0.5 dB over the single-parity post-processor in terms of bit- and byte-error-rate performance, the sector-error-rate performance of both schemes is almost the same. Furthermore, the sector-error-rate performance of optimum 64-state combined channel/parity detection for the dual-parity code is shown to be approximately 0.1 dB better than that of optimum 32-state combined channel/parity detection for the single-parity code. These performance gains can be even more substantial if appropriate coding techniques that eliminate certain error events and minimize error burst length or multiparity codes in conjunction with combined parity/channel detection are used.