Multihead Multitrack Detection for Next Generation Magnetic Recording, Part II: Complexity Reduction - Algorithms and Performance Analysis

To achieve large storage capacity on magnetic hard disk drives, very high track density is required, causing severe intertrack interference (ITI). Multihead multitrack (MHMT) detection has been proposed to better combat the effects of ITI. Such detection, however, has prohibitive implementation comp...

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Vydané v:IEEE transactions on communications Ročník 65; číslo 4; s. 1649 - 1661
Hlavní autori: Bing Fan, Thapar, Hemant K., Siegel, Paul H.
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: New York IEEE 01.04.2017
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:
Algorithm design and analysis
Algorithms
Complexity
Complexity theory
Computer simulation
Detectors
Disk drives
Error analysis
intertrack interference
Magnetic recording
Magnetic tape
Matrix decomposition
multitrack multihead detection
Partitioning algorithms
Quadrature amplitude modulation
reduced-state sequence estimation
Shingled magnetic recording
Storage capacity
System effectiveness
ISSN:0090-6778, 1558-0857
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Popis
Shrnutí:To achieve large storage capacity on magnetic hard disk drives, very high track density is required, causing severe intertrack interference (ITI). Multihead multitrack (MHMT) detection has been proposed to better combat the effects of ITI. Such detection, however, has prohibitive implementation complexity. Reduced-state sequence estimation (RSSE) is a promising technique for significantly reducing the complexity, while retaining good performance. In this paper, several different MHMT models are considered, including symmetric and asymmetric 2H2T systems, and a symmetric 3H3T system. By carefully evaluating the effective distance between two input symbols, we propose optimized set partition trees for each channel model. Different trellis configurations for RSSE are constructed based on the desired performance/complexity tradeoff. Simulation results show that the reduced MHMT detector can achieve near maximum-likelihood (ML) performance with a small fraction of the original number of trellis states. We also use error event analysis to explain the behavior of RSSE. The proposed algorithm could be potentially applied to next generation magnetic recording systems, especially when the ML detector is infeasible due to the high computational complexity.
Bibliografia:ObjectType-Article-1
SourceType-Scholarly Journals-1
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content type line 14
ISSN:0090-6778
1558-0857
DOI:10.1109/TCOMM.2017.2652456