Symbol timing recovery for low-SNR partial response recording channels

Future very high density data storage systems will exhibit significantly more intersymbol interference (ISI) and significantly lower signal-to-noise ratio (SNR). Advanced signal detection algorithms, such as noise predictive maximum likelihood (NPML) and iterative soft decoding, are aimed at coping with such lower SNRs and higher ISI. However, at such low SNRs, because of their large residual timing jitter, current timing recovery schemes suffer frequently from loss of lock (the event where the estimated phase drift differs significantly from the actual phase drift for a significantly long duration leading to misindexing of the detected bits and thus error bursts) potentially offsetting the SNR gains provided by advanced detection methods. The main contribution of this paper is that by approximating the phase drifts present in recording systems as a piecewise linear phase drift model, we propose a novel timing recovery scheme, which is named frequency offset feedforward symbol timing recovery (FOSTR). For such a piecewise linear phase drift model, the problem of estimating the time-changing phase drift can be transformed to the problem of estimating the slopes (i.e., frequency offsets) and initial phase offsets of several linear ramps. The performance of the timing recovery based on this approach will be better than current methods in low SNR because the number of parameters to be estimated is significantly smaller. Bit-by-bit simulations with iterative soft decoding (low density parity check (LDPC) code of rate 16/17 and codeword size 4352 bits is used) show that FOSTR results in a significantly smaller residual timing jitter than that of the conventional decision-directed PLL-based feedback timing recovery schemes, although the adjusted ("adjusted" means the sectors suffering from loss of lock are not taken into account in bit error rate calculation) bit error rate (BER) performance of FOSTR is only about 0.6 dB better for a target adjusted BER of 1/spl times/10/sup -5/ than that of the conventional timing recovery scheme because iterative soft decoding is robust to residual timing jitter. However, the loss of lock rate (i.e., the fraction of sectors suffering from loss of lock) is significantly reduced by FOSTR.

[1]  Pervez M. Aziz,et al.  Symbol rate timing recovery for higher order partial response channels , 2001, IEEE J. Sel. Areas Commun..

[2]  Xiaowei Jin,et al.  Cycle-slip detection using soft-output information , 2001, ICC 2001. IEEE International Conference on Communications. Conference Record (Cat. No.01CH37240).

[3]  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.

[4]  Joachim Hagenauer,et al.  A Viterbi algorithm with soft-decision outputs and its applications , 1989, IEEE Global Telecommunications Conference, 1989, and Exhibition. 'Communications Technology for the 1990s and Beyond.

[5]  S. Haykin,et al.  Adaptive Filter Theory , 1986 .

[6]  H. K. Thapar,et al.  Feed-forward timing recovery for digital magnetic recording , 1991, ICC 91 International Conference on Communications Conference Record.

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

[8]  S. W. McLaughlin,et al.  Iterative decoding for partial response (PR), equalized, magneto-optical (MO) data storage channels , 2001, IEEE J. Sel. Areas Commun..

[9]  Fulvio Spagna Phase locked loop using delay compensation techniques , 2000, Proceedings ISCC 2000. Fifth IEEE Symposium on Computers and Communications.

[10]  K. Mueller,et al.  Timing Recovery in Digital Synchronous Data Receivers , 1976, IEEE Trans. Commun..

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

[12]  B. V. K. Vijaya Kumar,et al.  Use of adaptive filter for timing recovery for data storage channels , 2000, 2000 IEEE International Conference on Communications. ICC 2000. Global Convergence Through Communications. Conference Record.

[13]  Jan W. M. Bergmans,et al.  Digital baseband transmission and recording , 1996 .