Lin M. M. Myint

An Inter-Track Interference Mitigation Technique Using Partial ITI Estimation in Patterned Media Storage

The readback signal of patterned media storage (PMS) is corrupted by a two-dimensional interference consisting of inter-symbol interference (ISI) and inter-track interference (ITI). In this paper, we apply the turbo equalization to mitigate the ITI effects. The codeword of the outer code is divided and then written on three separate tracks. After the first iteration, the bit estimates from the outer code provide partial ITI estimates for the branch metric computation in the soft-output viterbi algorithm (SOVA) detectors. Unlike previous works, the number of states of the channel trellis is due to the ISI only since the ITI information is not embedded in the parallel branches. When compared with the modified SOVA detectors with multi-parallel branches, simulation results show that a significant performance gain is achieved by our proposed method.

Serial Belief Propagation for The High-Rate LDPC Decoders and Performances in The Bit Patterned Media Systems With Media Noise

In this work, we propose to use the serial belief propagation or serial scheduling in the 2-D bit patterned media (BPM) system with media noise. The serial scheduling methods are applied to the random LDPC codes and quasi-cyclic LDPC (QC-LDPC) codes of high code rates. Both are constructed from the progress-edge growth (PEG) algorithm. We compare the performance of the LDPC codes using the serial belief propagation and the conventional belief propagation (BP) decoding. The simulation results show that the serial scheduling provides a faster convergence speed and a better bit error rate performance than the conventional BP in an AWGN channel. The serial belief propagation is also shown to offer the performance gains over the BP decoding for the BPM system with various media noise levels.

Off-Track Detection Based on the Readback Signals in Magnetic Recording

Off-track condition in magnetic recording systems degrades the system performance. It is typically detected and adjusted by the servo control loop. In this work, we propose an off-track detection based on the readback signals and improve the bit error performance using an asymmetric target depending on the detected off-track direction. Specifically, we investigate the effects of off-track events on the target-shaping equalizer coefficients when the generalized partial-response target (GPR) is fixed. For a 3 × 3 channel matrix of bit patterned media recording (BPMR) system, the asymmetric targets offer the gain of about 1 to 2 dB at BER=10-4 for the TMR level of 20% to 25%.

Modified Graph-Based Detection Methods for Two-Dimensional Interference Channels

Two-dimensional (2-D) interference channels with inter-symbol interference (ISI) and inter-track interference (ITI) exist in the magnetic recording systems at high areal density. A number of 2-D detection methods have recently been proposed for the multi-track processing of the 2-D channels. Graph-based detector with the belief propagation algorithm appears as an alternative method, but at a degraded performance and high complexity level. In this work, we propose two methods to modify the graph-based (GB) detector. One applies a serial scheduling to the GB detector, while the other modifies the GB detection by ignoring some connections during one direction of the reliability updates in the factor graph leading to the reduction of short cycles. The simulation results show that the proposed GB detectors give better bit error rate performances than the other GB detectors.

Utilization of multiple read heads for TMR prediction and correction in bit-patterned media recording

This paper proposes a utilization of multiple read heads to predict and correct a track mis-registration (TMR) in bit-patterned media recording (BPMR) based on the readback signals. We propose to use the signal energy ratio between the upper and lower tracks from multiple read heads to estimate the TMR level. Then, a pair of two-dimensional (2D) target and its corresponding 2D equalizer associated with the estimated TMR will be chosen to correct the TMR in the data detection process. Numerical results show that the proposed system can achieve a very high accuracy of TMR prediction, thus performing better than the conventional system, especially when TMR is severe.

Reduced complexity of multi-track joint 2-D Viterbi detectors for bit-patterned media recording channel

Two-dimensional (2-D) interference is one of the prominent challenges in ultra-high density recording system such as bit patterned media recording (BPMR). The multi-track joint 2-D detection technique with the help of the array-head reading can tackle this problem effectively by jointly processing the multiple readback signals from the adjacent tracks. Moreover, it can robustly alleviate the impairments due to track mis-registration (TMR) and media noise. However, the computational complexity of such detectors is normally too high and hard to implement in a reality, even for a few multiple tracks. Therefore, in this paper, we mainly focus on reducing the complexity of multi-track joint 2-D Viterbi detector without paying a large penalty in terms of the performance. We propose a simplified multi-track joint 2-D Viterbi detector with a manageable complexity level for the BPMR’s multi-track multi-head (MTMH) system. In the proposed method, the complexity of detector’s trellis is reduced with the help of the ...

Soft-information flipping approach in multi-head multi-track BPMR systems

Inter-track interference is one of the most severe impairments in bit-patterned media recording system. This impairment can be effectively handled by a modulation code and a multi-head array jointly processing multiple tracks; however, such a modulation constraint has never been utilized to improve the soft-information. Therefore, this paper proposes the utilization of modulation codes with an encoded constraint defined by the criteria for soft-information flipping during a three-track data detection process. Moreover, we also investigate the optimal offset position of readheads to provide the most improvement in system performance. The simulation results indicate that the proposed systems with and without position jitter are significantly superior to uncoded systems.

A TMR mitigation method with 3-track data detection for multi-track multi-head BPMR system

An off-track situation from misalignment between the center of read head and that of target track is also known as track mis-registration (TMR), which is one of major problems in bit-patterned media recording (BPMR), especially at high areal density (AD) [1–4].

Mitigation of TMR Using Energy Ratio and Bit-Flipping Techniques in Multitrack Multihead BPMR Systems

Track misregistration (TMR) in ultra-high density bit-patterned media recording (BPMR) is one of the crucial problems, because it can severely degrade the overall system performance. In practical, TMR can be detected and adjusted by a servo control loop system. However, this paper proposes to utilize multiple readback signals obtained from the optimized positioning of the two side read head closer to the main read head to improve the TMR prediction process in a multitrack multi-head BPMR system with position jitter noise. In addition, we also propose the soft-information exchange and the bit-flipping techniques for the multitrack data detection, so as to improve the bit-error rate (BER) performance of all three data tracks simultaneously. Simulation results indicate that the proposed system is superior to the conventional system, especially, when the amount of TMR and position jitter is high. Furthermore, we also found that the upper and lower read heads, which are moved closer to the center track by 25% of a track pitch, will provide the best BER performance with and without position jitter noise.

An optimization approach to capacity planning of aggregators and resource provisioning in cloud providers for meteorological sensor network

To forecast the weather accurately, meteorologists need the meteorological data from wireless sensor devices which are installed in different geographical areas besides from satellites. Nowadays, cloud computing technology can provide data storage and data processing tasks for the big meteorological data from numerous sensors. However, wireless sensors have short communication range to send the data to cloud. Therefore, we propose a heuristic system model with aggregator approach. The aggregator approach has responsibility to collect the data from sensors and transfer to the cloud with high speed bandwidth over long distance. Furthermore, optimization approaches are applied in capacity planning of aggregators and resource provisioning in cloud providers for system model to reduce the cost. Based on numerical results, the total cost of system model can be minimized.