Sw. Mclaughlin et Dl. Neuhoff, SOURCE-CHANNEL CODING OF ANALOG DATA FOR DIGITAL MAGNETIC RECORDING, IEEE transactions on magnetics, 30(1), 1994, pp. 128-144
In the traditional approach of storing analog data (such as speech sam
ples or image pixels) in digital magnetic recording, a binary represen
tation of the analog data is stored with great reliability. Since such
high reliability is unnecessary for many types of analog data, it is
hypothesized that more data can be stored by increasing the density wi
th which bits are placed on the media and using source-channel coding
to both compress the data and protect it from the resulting increased
bit error rate. This paper estimates the gains achievable with this ap
proach. Central to this work is a model for the digital magnetic recor
ding channel that contains a linear filter representing the Lorentzian
step response and additive Gaussian processes representing electronic
and media noises. The model differs from previous ones in that lineal
bit density, as well as track density, are parameters that may be var
ied. Parameters for this model that typify disk storage systems are id
entified and the gains in data density for the proposed approach are e
stimated in two ways: by estimating the capacity of the channel model
and by simulating a family of source-channel codes. From capacity boun
ds developed in a companion paper, it is estimated that data density m
ay ultimately be increased by a factor of 20 or more. To assess the ga
ins achievable with a practical system, a tree-structured family of so
urce-channel codes is proposed and analyzed. It is found that these ar
e much simpler than optimal unstructured source-channel codes, yet hav
e comparable performance. By simulating them on a Gaussian source and
the given channel model, it is estimated that gains on the order of 3
to 4 in data density are achievable with peak detection demodulation a
nd gains of 2 to 3 are achievable with 1-D2 partial response maximum l
ikelihood demodulation, each with moderate increases in bit density. C
omparable gains are anticipated for speech and images.