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Maximum Likelihood Decoder for High Density Partial Response Class IV Channel

IP.com Disclosure Number: IPCOM000108769D
Original Publication Date: 1992-Jun-01
Included in the Prior Art Database: 2005-Mar-22
Document File: 3 page(s) / 116K

Publishing Venue

IBM

Related People

Feig, E: AUTHOR [+2]

Abstract

A technique is described whereby a maximum likelihood decoder is used for high density partial response class IV channels where the output of the channel is a deterministic signal buried in additive white noise.

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Maximum Likelihood Decoder for High Density Partial Response Class IV Channel

       A technique is described whereby a maximum likelihood
decoder is used for high density partial response class IV channels
where the output of the channel is a deterministic signal buried in
additive white noise.

      Although not suitable for very high density channels, a second
nonlinear component of noise, due to timing jitter, becomes
increasingly significant as density increases. Therefore, the decoder
takes this component into account.

      Typically, a pulse amplitude modulation (PAM) channel output
would adhere to the form:

                            (Image Omitted)

where ak are elements from a finite alphabet (the code to be
transmitted), h(t) is some designated low-bandwidth channel function,
and T is the timing interval for the channel.  A partial response
channel is a PAM channel in which intersymbol interference is
introduced in a calculated way and whose output is not necessarily
sampled at its peak values.  The class IV channel takes on the form:
When sampled at integer multiples of T, this channel outputs

      Communication channels are far from ideal.  Actually, the
observed output takes a form very close to:
where is a random "jitter" and n(t) is additive noise. Most coding,
modulation and decoding schemes ignore the jitter problem, although
this problem is becoming increasingly relevant as transmission rates
become greater. In order to take into account jitter statistics, the
concept described herein presents a sequential maximum likelihood
decoder where the output sequence is viewed as a Markov process with
finite error memory.  The decoder is highly parallelized and will
yield excellent results.

      Assume that the additive noise is Gaussian with mean 0 and a
known variance     and that the jitter sequence     is normally
distributed around 0 with a known variance    . Two fixed global
constants a1, a2 are pre-compu...