Quasi-Reduced-State Soft-Output Viterbi Detector for Magnetic Recording Read Channel

• Published in: IEEE transactions on magnetics Vol. 43; no. 10; pp. 3921 - 3924
• Main Authors: Sun, Fei, Zhang, Tong
• Format: Journal Article
• Language: English
• Published: New York, NY IEEE 01.10.2007; Institute of Electrical and Electronics Engineers; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Blocking; Channels; Computation; Critical path; Cross-disciplinary physics: materials science; rheology; Data storage; Design methodology; Detectors; E2PR4 channel; Energy consumption; Exact sciences and technology; Feedback; Feedback circuits; Magnetic recording; Magnetism; Materials science; Memory; Other topics in materials science; Physics; Pipeline processing; Potential energy; reduced-state sequence detector; soft-output Viterbi algorithm (SOVA); State feedback; Studies; Viterbi algorithm; E2PR4 channel; reduced-state sequence detector; soft-output Viterbi algorithm (SOVA); Magnetic recording; Magnetic properties
• DOI: 10.1109/TMAG.2007.904190
• ISSN: 0018-9464

Reduced-state trellis detection with decision feedback is widely used to reduce the energy consumption of trellis detectors, particularly for soft-output trellis detectors that are energy-hungry by nature. However, the decision feedback tends to increase the circuit critical path and, more important, makes it difficult to apply some well-proven high-speed trellis detector design techniques such as bit-level pipelining. This paper presents a method, referred to as quasi-reduced-state trellis detection, to tackle such speed bottlenecks. The basic idea is to simply obviate the use of decision feedback by mapping only the data storage block of the trellis detector onto a reduced-state trellis and keeping the trellis state metric computation on the original full-state trellis. This makes sense because the data storage block tends to dominate the overall energy consumption while the decision feedback is due to the reduced-state trellis metric computation. Therefore, it is intuitive that such quasi-reduced-state detectors may largely maintain the energy saving potentials of reduced-state trellis detection without being subject to decision-feedback-induced speed bottlenecks. We demonstrated the effectiveness of this proposed design method by using soft-output Viterbi algorithm (SOVA) detection for a magnetic recording read channel as a test vehicle.