Soft-output Viterbi Algorithm Detector Research Articles

User Areal Density Optimization for Conventional and 2-D Detectors/Decoders

The magnetic recording industry is perennially trying to grow the areal density by optimizing the head/media, the coding/signal processing, and the bit length (BL) and track pitch (TP) of the data written on the medium. Writing data at smaller BL or TP on the medium lead to loss of SNR during readback, which can be corrected by the coding and signal processing subsystem at the cost of the code rate $R$ . The optimization of the BL, TP, and code rate for a given head and media is the task of the system integrator. In this paper, we make use of an advanced channel model: the grain-flipping probability model, to perform an equivalent optimization together with a software recording channel that is able to include the impact of the generalized partial response equalizer, soft-output Viterbi algorithm detector, and low density parity check decoder on the final performance. In this paper, we vary the BL, TP, and code rate $R$ in the simulations to search for the highest user areal density achievable for a given head/medium setup. We investigate the effect of having a constant reader width (RW) as well as with RW proportionate to TP in our channel model. We also investigate the effect of more advanced 2-D coding and detection schemes on the final system performance.

Multilevel Reed–Solomon Codes for PMR Channels

Reed–Solomon (RS) codes are commonly utilized in magnetic recording systems to correct error bursts. A soft-output Viterbi algorithm (SOVA) is a commonly used detector to provide soft information to error-correcting decoders. We propose a novel architecture of a multilevel interleaved RS coding scheme that not only provides better performance but also has less complexity than an equivalent RS code. This architecture implements an error event detector using the soft information generated by the SOVA detector. The performance and complexity of the decoding technique are compared with the well-known soft-decoding techniques, such as generalized minimum distance decoding and Chase decoding techniques.

Design of Low-Complexity 2-D SOVA Detector for Shingled Magnetic Recording

Shingled magnetic recording emerges as a promising near-term option to sustain the historical areal density growth of hard-disk drives while retaining conventional heads and media. Highly scaled shingled magnetic recording is subject to severe intertrack interference, which naturally demands 2-D read channel signal processing. By concurrently detecting multitrack read-back signals from a read head array, joint 2-D signal detection can fully exploit the 2-D interference to maximize the detection performance at the penalty of very high computational complexity. As modern read channel employs iterative signal detection and decoding and hard-disk drives are very cost sensitive, it is highly desirable to effectively reduce the 2-D signal detection computational complexity and hence silicon cost at minimal detection performance loss. This paper presents two low-complexity 2-D soft-output Viterbi algorithm (SOVA) detector design strategies for realizing multitrack joint 2-D detection, which represent different complexity versus performance tradeoffs. By carrying out simulations and application-specific integrated circuit design, this paper shows that, compared with the best symbol-based 2-D SOVA, it is feasible to achieve almost the same detection performance and meanwhile reduce the silicon area by more than 60% in three-track joint detection.

Novel Joint Detection and Decoding Schemes for TDMR Channels

Two-dimensional magnetic recording (TDMR) relies on advanced signal processing and coding techniques to enable storage of data at higher densities. Various detection and decoding schemes have been proposed in the literature. In this paper, a recently proposed joint detection and decoding scheme known as the joint Viterbi detector decoder (JVDD) is presented for TDMR channels. The JVDD operates on a trellis and attempts to find a sequence in the trellis that belongs to a legal codeword with minimum metric. It does so by using a metric thresholding and parity checking technique over the same trellis structure. The iterative detector/decoder consisting of a soft-output Viterbi algorithm detector and low-density parity check decoder is used as a performance benchmark for the JVDD. In this paper, we perform the comparison with various equalization/detection techniques consisting of: 1) a 1-D general partial response equalization scheme followed by a 1-D-detector as used in today’s Partial Response Maximum Likelihood Detection (PRML) channels; 2) a 2-D equalization scheme that equalizes to a 1-D target [fully equalizing away the intertrack interference (ITI)], followed by a series of parallel 1-D-detectors to handle the intersymbol interference (ISI); and 3) a 2-D-equalization scheme followed by 2-D detector to combat both ITI and ISI.