Capacity-approaching codes: can they be applied to the magnetic recording channel?

Digital signal processing and coding are increasingly being recognized as a cost-efficient approach in achieving substantial areal density gains while preserving the high reliability of disk drives, although historically advances in head and media technologies have been the main driving force behind areal density growth. The recent advances in capacity-approaching codes hold the promise to push the areal density to the ultimate limit. Various configurations regarding the interplay between soft detection and soft decoding through an iterative process, as it applies to the magnetic recording channel, are presented. In particular, the state of the art in turbo and turbo-like coding, including LDPC coding, is reviewed, and the serial concatenation of these coding schemes with inner generalized PR channels in a turbo equalization structure is described. Finally, an attempt is made to assess the performance and limitations of these AWGN channel-capacity-approaching codes when applied to the magnetic recording channel.

[1]  Ajay Dholakia,et al.  Reduced-complexity decoding of low density parity check codes for generalized partial response channels , 2001 .

[2]  Hans-Andrea Loeliger,et al.  On the information rate of binary-input channels with memory , 2001, ICC 2001. IEEE International Conference on Communications. Conference Record (Cat. No.01CH37240).

[3]  Shlomo Shamai,et al.  The intersymbol interference channel: lower bounds on capacity and channel precoding loss , 1996, IEEE Trans. Inf. Theory.

[4]  Evangelos Eleftheriou,et al.  Progressive edge-growth Tanner graphs , 2001, GLOBECOM'01. IEEE Global Telecommunications Conference (Cat. No.01CH37270).

[5]  Paul H. Siegel,et al.  Turbo decoding for partial response channels , 2000, IEEE Trans. Commun..

[6]  Shu Lin,et al.  Low-density parity-check codes based on finite geometries: A rediscovery and new results , 2001, IEEE Trans. Inf. Theory.

[7]  Bane V. Vasic,et al.  Structured iteratively decodable codes based on Steiner systems and their application in magnetic recording , 2001, GLOBECOM'01. IEEE Global Telecommunications Conference (Cat. No.01CH37270).

[8]  W. Ryan.  Performance of high rate turbo codes on a PR4-equalized magnetic recording channel , 1998, ICC '98. 1998 IEEE International Conference on Communications. Conference Record. Affiliated with SUPERCOMM'98 (Cat. No.98CH36220).

[9]  Hongwei Song,et al.  Low-Density Parity Check Code Concatenated with Generalized Partial Response Equalizer for High-Capacity Magneto-Optic Recording Channels , 2002 .

[10]  Roy D. Cideciyan,et al.  Noise predictive maximum likelihood detection combined with parity-based post-processing , 2001 .

[11]  A. Glavieux,et al.  Near Shannon limit error-correcting coding and decoding: Turbo-codes. 1 , 1993, Proceedings of ICC '93 - IEEE International Conference on Communications.

[12]  B. V. Vijaya Kumar,et al.  Low-density parity check codes for partial response channels , 2004, IEEE Signal Processing Magazine.

[13]  Frank R. Kschischang.  Codes defined on graphs , 2003, IEEE Commun. Mag..

[14]  Ajay Dholakia,et al.  Near optimal reduced-complexity decoding algorithms for LDPC codes , 2002, Proceedings IEEE International Symposium on Information Theory,.

[15]  D.J.C. MacKay,et al.  Good error-correcting codes based on very sparse matrices , 1997, Proceedings of IEEE International Symposium on Information Theory.

[16]  Evangelos S. Eleftheriou,et al.  Noise-predictive maximum likelihood (NPML) detection , 1998 .

[17]  Robert G. Gallager.  Low Density Parity Check Code , 1962 .

[18]  Robert G. Gallager,et al.  Low-density parity-check codes , 1962, IRE Trans. Inf. Theory.

[19]  M. Tuchler,et al.  New rate-(N-1)/N convolutional codes with optimal spectrum , 2002, Proceedings IEEE International Symposium on Information Theory,.