Ms. Yanhua Shi Profile

Yanhua Shi

at Univ of Colorado at Boulder

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Proceedings Article | 8 November 2001 Paper

Turbo equalization and decoding for magnetic recording channels with signal-dependent noise

Yanhua Shi, Mahesh Varanasi

Proceedings Volume 4534, (2001) https://doi.org/10.1117/12.448020

KEYWORDS: Interference (communication), Sensors, Computer programming, Magnetism, Autoregressive models, Forward error correction, Signal detection, Data storage, Signal processing, Electronic filtering

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In high-density magnetic recording systems, long channel memories and strong signal dependent noise are the two main factors that degrade system performance. The equalized Lorentzian channel can be seen to be equivalent to a partial response channel. As the density becomes higher, the length of the partial response becomes longer which makes the problem of achieving low bit error rates more challenging. The turbo principle is very promising for such channels, since equalization and coding can be combined together seamlessly. For simplicity, a serially concatenated turbo code is used here. A recursive systematic convolutional code is used as the outer code while the inner code is the modified partial response channel. In decoding, two a posteriori probability (APP) detectors are connected to form a loop. The outer code APP detector takes the output of the inner code APP detector as its input and then feeds back its output as the new input to inner code APP detector. This decoding procedure is carried on in an iterative manner. In decoding, it is often assumed that the noise component is white Gaussian for simplicity. We will consider signal dependent noise because it has the dominant effect when the recording density is high. We will demonstrate the improvement in bit error rate over the scheme that assumes white Gaussian noise.

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