Multitrack Detection for Magnetic Recording

The thesis develops advanced signal processing algorithms for magnetic recording to increase areal density. The exploding demand for cloud storage is motivating a push for higher areal densities, with narrower track pitches and shorter bit lengths. The resulting increase in interference and media noise requires improvements in read channel signal processing to keep pace. This thesis proposes the multitrack pattern-dependent noise-prediction algorithm as a solution to the joint maximum-likelihood multitrack detection problem in the face of pattern-dependent autoregressive Gaussian noise. The magnetic recording read channel has numerous parameters that must be carefully tuned for best performance; these include not only the equalizer coefficients but also any parameters inside the detector. This thesis proposes two new tuning strategies: one is to minimize the bit-error rate after detection, and the other is to minimize the frame-error rate after error-control decoding. Furthermore, this thesis designs a neural network read channel architecture and compares the performance and complexity with these traditional signal processing techniques.Ph.D

Synchronization and detection for two-dimensional magnetic recording

This thesis develops efficient synchronization and detection algorithms for two-dimensional magnetic recording (TDMR) under a low latency constraint. TDMR is a new technology for increasing data density of hard disk drives up to 10 Tera bits per square inch of the medium. TDMR read channel suffers from two-dimensional interference, bit position (timing) uncertainty, and data dependent noise, to name a few. The problem of timing uncertainty is addressed with synchronization. This thesis focuses on the synchronization component of the read channel and develops synchronization solutions which effectively compensate for the asynchrony between the phase of the received readback waveforms and the phase of the sampling clocks. In particular, this thesis proposes solutions to reduce the computational cost of current generation of read channels, where only one data track is detected at a time. For future generations of TDMR read channels, where multiple tracks will be detected jointly, this thesis provides a first-time solution to the synchronization problem for joint detection of multiple asynchronous tracks.Ph.D

ON REDUCING THE DECODING COMPLEXITY OF SHINGLED MAGNETIC RECORDING SYSTEM

Shingled Magnetic Recording (SMR) has been recognised as one of the alternative technologies to achieve an areal density beyond the limit of the perpendicular recording technique, 1 Tb/in2, which has an advantage of extending the use of the conventional method media and read/write head. This work presents SMR system subject to both Inter Symbol Interference (ISI) and Inter Track Interference (ITI) and investigates different equalisation/detection techniques in order to reduce the complexity of this system. To investigate the ITI in shingled systems, one-track one-head system model has been extended into two-track one-head system model to have two interfering tracks. Consequently, six novel decoding techniques have been applied to the new system in order to find the Maximum Likelihood (ML) sequence. The decoding complexity of the six techniques has been investigated and then measured. The results show that the complexity is reduced by more than three times with 0.5 dB loss in performance. To measure this complexity practically, perpendicular recording system has been implemented in hardware. Hardware architectures are designed for that system with successful Quartus II fitter which are: Perpendicular Magnetic Recording (PMR) channel, digital filter equaliser with and without Additive White Gaussian Noise (AWGN) and ideal channel architectures. Two different hardware designs are implemented for Viterbi Algorithm (VA), however, Quartus II fitter for both of them was unsuccessful. It is found that, Simulink/Digital Signal Processing (DSP) Builder based designs are not efficient for complex algorithms and the eligible solution for such designs is writing Hardware Description Language (HDL) codes for those algorithms.The Iraqi Governmen

Multihead Multitrack Detection for Next Generation Magnetic Recording Systems

Two dimensional magnetic recording (TDMR) is one of the leading technologies proposed to achieve ultra high storage density in the next generation hard disk drives. A typical read channel of TDMR can be approximated by a multihead multitrack (MHMT) model which is characterized by the intersymbol interference (ISI) in the downtrack direction and intertrack interference (ITI) in the crosstrack direction. In this dissertation, we aim to address two challenging problems that can potentially make the maximum likelihood (ML) detection for the MHMT channel impractical. One problem associated with the conventional ML detector is the ITI dependency of the ML trellis, which makes it inefficient to adapt to a time-varying ITI environment. We propose a novel detection method, called the weighted sum-subtract joint detection (WSSJD), to solve this issue. We show that the ITI interfering channels in MHMT system can be transformed to several parallel subchannels, whose joint trellis is independent of ITI. For the case when the receiver lacks the knowledge of ITI, we propose a gain loop structure which can be incorporated into WSSJD to efficiently track the ITI estimates. We present the implementation of WSSJD and simulation results for several widely-studied MHMT models including the 2H2T channel, the 3H3T channel, and the 3H2T channel.Another challenging problem is the exponentially increased computational complexity of the ML detector due to its multitrack processing scheme. We propose to use the reduced-state sequence estimation (RSSE) to mitigate this issue. The underlying idea is to drop less likely paths at early state during the detection by using a heavily reduced subset trellis. To apply RSSE to the MHMT channel, we find that the channel transformation developed in WSSJD offers a natural set partition principle on the input constellation that is necessary to successfully implement RSSE. The theoretical error event analysis shows a good consistency with the simulation results.Flash memory has faster access speed, lower power consumption, and better data integrity, which make it more attractive than the magnetic recording in many applications. However, the lifetime of flash memory is limited by the program/erase cycles. Write-once memory (WOM) codes are proposed to extend the flash memory lifetime by constraining the unidirectional changes of cell levels. In this work, we study the expected performance of WOM codes. Dynamic programming based algorithm is proposed to construct the optimal WOM updating function of a given labeling function

Multihead Multitrack Detection for Next Generation Magnetic Recording Systems

Two dimensional magnetic recording (TDMR) is one of the leading technologies proposed to achieve ultra high storage density in the next generation hard disk drives. A typical read channel of TDMR can be approximated by a multihead multitrack (MHMT) model which is characterized by the intersymbol interference (ISI) in the downtrack direction and intertrack interference (ITI) in the crosstrack direction. In this dissertation, we aim to address two challenging problems that can potentially make the maximum likelihood (ML) detection for the MHMT channel impractical. One problem associated with the conventional ML detector is the ITI dependency of the ML trellis, which makes it inefficient to adapt to a time-varying ITI environment. We propose a novel detection method, called the weighted sum-subtract joint detection (WSSJD), to solve this issue. We show that the ITI interfering channels in MHMT system can be transformed to several parallel subchannels, whose joint trellis is independent of ITI. For the case when the receiver lacks the knowledge of ITI, we propose a gain loop structure which can be incorporated into WSSJD to efficiently track the ITI estimates. We present the implementation of WSSJD and simulation results for several widely-studied MHMT models including the 2H2T channel, the 3H3T channel, and the 3H2T channel.Another challenging problem is the exponentially increased computational complexity of the ML detector due to its multitrack processing scheme. We propose to use the reduced-state sequence estimation (RSSE) to mitigate this issue. The underlying idea is to drop less likely paths at early state during the detection by using a heavily reduced subset trellis. To apply RSSE to the MHMT channel, we find that the channel transformation developed in WSSJD offers a natural set partition principle on the input constellation that is necessary to successfully implement RSSE. The theoretical error event analysis shows a good consistency with the simulation results.Flash memory has faster access speed, lower power consumption, and better data integrity, which make it more attractive than the magnetic recording in many applications. However, the lifetime of flash memory is limited by the program/erase cycles. Write-once memory (WOM) codes are proposed to extend the flash memory lifetime by constraining the unidirectional changes of cell levels. In this work, we study the expected performance of WOM codes. Dynamic programming based algorithm is proposed to construct the optimal WOM updating function of a given labeling function