Initially, several turbo equalization systems for two-dimensional intersymbol interference (2D-ISI) channels are proposed. The systems' receivers consist of joint 2D-ISI equalizers with an irregular repeat accumulate (IRA) LDPC code.

With magnetic storage devices already achieving storage densities of up to 400 Gigabits per square inch (Gb/in2), the state of the art is rapidly approaching theoretical limits (dictated by thermal stability concerns). Hence, there is an eort in the industry to develop alternative magnetic storage technologies. Two-dimensional magnetic recording (TDMR) is one such candidate technology. In contrast to other technologies(e.g. heat-assisted magnetic recording [1], bit-patterned media [2]) which rely on signicant changes being made to the recording medium, TDMR relies on the use of traditional recording media, while relying on signal processing to make improvements in the recording density. Though advantageous due to the fact that no drastic re-engineering of media is required, there are signicant challenges that need to be addressed in order to make TDMR a viable candidate for next-generation recordingsystems. The main challenges involved in TDMR arise due to (i) the small bit-area, along with an aggressive write/read process, which leads to a large amount of noise, and (ii) the two-dimensional nature of the recording process { so far not encountered in today's systems. Thus, a gamut of 2D signal processing algorithms need be developed for the compensation of errors occurring due to the aggressive write/read processes. In this dissertation, we present some of the work done with regard to the signal processing tasks involved in TDMR. In particular, we describe our work on (i) channel modelling, (ii) detection strategies, and (iii) error-correction coding strategies targetted at TDMR.

The advent of the internet age has produced enormous demand for in creased storage capacity and for the consequent increases in the amount of information that can be stored in a small space. While physical and media improvements have driven the majority of improvement in modern storage systems, signal processing and coding methods have increasing ly been used to augment those improvements. Run-length-limited codes and partial-response detection methods have come to be the norm in an industry that once rejected any sophistication in the read or write pro cessing circuits. VLSI advances now enable increasingly sophisticated signal processing methods for negligible cost and complexity, a trend sure to continue even as disk access speeds progress to billions of bits per second and terabits per square inch in the new millennium of the in formation age. This new book representing the Ph. D. dissertation work of Stanford's recent graduate Dr. Zining Wu is an up-to-date and fo cused review of the area that should be of value to those just starting in this area and as well those with considerable expertise. The use of saturation recording, i. e. the mandated restriction of two-level inputs, creates interesting twists on the use of communica tion/transmission methods in recording.

Implementing new architectures and designs for the magnetic recording read channel have been pushed to the limits of modern integrated circuit manufacturing technology. This book reviews advanced coding and signal processing techniques and architectures for magnetic recording systems. Beginning with the basic principles, it examines read/write operations, data organization, head positioning, sensing, timing recovery, data detection, and error correction. It also provides an in-depth treatment of all recording channel subsystems inside a read channel and hard disk drive controller. The final section reviews new trends in coding, particularly emerging codes for recording channels.

Generally speaking, a communication channel refers to a medium through which an information-bearing signal is corrupted by noise and distortion. A communication channel may result from data storage over time or data transmission through space. A primary task for communication engineers is to mathematically characterize the channel to facilitate the design of appropriate detection and coding systems. In this dissertation, two different channel modeling challenges for ultra-high density magnetic storage are investigated: two-dimensional magnetic recording (TDMR) and bit-patterned magnetic recording (BPMR). In the case of TDMR, we characterize the error mechanisms during the write/read process of data on a TDMR medium by a finite-state machine, and then design a state-based detector that provides soft decisions for use by an outer decoder. In the case of BPMR, we employ an insertion/deletion (I/D) model. We propose a LDPC-CRC product coding scheme that enables the error detection without the involvement of Marker codes specifically designed for an I/D channel. We also propose a generalized Gilbert-Elliott (GE) channel to approximate the I/D channel in the sense of an equivalent I/D event rate. A lower bound of the channel capacity for the BPMR channel is derived, which supports our claim that commonly used error-correction codes are effective on the I/D channel under the assumption that I/D events are limited to a finite length. Another channel model we investigated is perpendicular magnetic recording model. Advanced signal processing for the pattern-dependent-noise-predictive channel detectors is our focus. Specifically, we propose an adaptive scheme for a hardware design that reduces the complexity of the detector and the truncation/saturation error caused by a fix-point representation of values in the detector. Lastly, we designed a sequence detector for compressively sampled Bluetooth signals, thus allowing data recovery via sub-Nyquist sampling. This detector skips the conventional step of reconstructing the original signal from compressive samples prior to detection. We also propose an adaptive design of the sampling matrix, which almost achieves Nyquist sampling performance with a relatively high compression ratio. Additionally, this adaptive scheme can automatically choose an appropriate compression ratio as a function of.