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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.
List of contents
1. Introduction to Magnetic Recording Channels.- 1. Magnetic Recoding Systems.- 2. Magnetic Recording Channel Model.- 3. Challenges in Read/Write Electronics Design.- 4. Read Channel Detectors.- 5. Outline of Book.- 2. Turbo Codes and Turbo Equalization.- 1. Introduction.- 2. Turbo Encoder and Coding Gain.- 3. Soft Iterative Decoding with BCJR Algorithm.- 4. Turbo Equalization for Magnetic Recording Channels.- 5. Summary.- APPENDIX 2.A Recursive Algorithms for ?'s and ?'s.- APPENDIX 2.B Approximation for the Log-Sum operation.- 3. Low-Density Parity-Check Codes.- 1. Introduction.- 2. Low-Density Parity-Check Codes.- 3. Iterative Detection and Belief Propagation.- 4. LDPC Codes for Magnetic Recording Channels.- 5. Summary and Discussion.- 4. Turbo Decision Aided Equalization.- 1. Decision Aided Equalization for Channel APP Detection.- 2. Implementation and Analysis of Turbo-DAE.- 3. Simulation Results.- 4. Turbo-DAE with Local BCJR.- 5. Summary and Conclusion.- APPENDIX 4.A APP Detection for Binary Markov Source with Finite Input Memory.- 1. Markov Source with Finite Input Memory.- 2. Modified BCJR Algorithm for Binary Markov Source with Finite Input Memory.- 5. Interleaved Parity Check Codes and Reduced Complexity Detection.- 1. Introduction.- 2. Error-events for the E2PR4 Channel.- 3. Interleaved Parity Check Codes.- 4. Reduced Complexity Detection for Interleaved Parity Check Codes.- 5. Performance of Interleaved Parity Check Codes.- 6. Summary and Conclusion.- 6. Interpolated Timing Recovery.- 1. Introduction.- 2. Conventional VCO-based Timing Recovery Loop.- 3. MMSE Interpolation Filter.- 4. FIR-ITR Loop Structure.- 5. Practical Issues.- 6. Simulation Results.- 7. Summary and Conclusion.- 7. Summary and Discussion.- 1. Speeding Turbo Decoding.- 2. TimingRecovery Schemes for Low SNR Channels.- 3. Turbo Decision Aided Equalization for Other Types of Channels.- References.
