77 research outputs found
Performance evaluation for ML sequence detection in ISI channels with Gauss Markov Noise
Inter-symbol interference (ISI) channels with data dependent Gauss Markov
noise have been used to model read channels in magnetic recording and other
data storage systems. The Viterbi algorithm can be adapted for performing
maximum likelihood sequence detection in such channels. However, the problem of
finding an analytical upper bound on the bit error rate of the Viterbi detector
in this case has not been fully investigated. Current techniques rely on an
exhaustive enumeration of short error events and determine the BER using a
union bound. In this work, we consider a subset of the class of ISI channels
with data dependent Gauss-Markov noise. We derive an upper bound on the
pairwise error probability (PEP) between the transmitted bit sequence and the
decoded bit sequence that can be expressed as a product of functions depending
on current and previous states in the (incorrect) decoded sequence and the
(correct) transmitted sequence. In general, the PEP is asymmetric. The average
BER over all possible bit sequences is then determined using a pairwise state
diagram. Simulations results which corroborate the analysis of upper bound,
demonstrate that analytic bound on BER is tight in high SNR regime. In the high
SNR regime, our proposed upper bound obviates the need for computationally
expensive simulation.Comment: This paper will appear in GlobeCom 201
Maximum-Likelihood Sequence Detector for Dynamic Mode High Density Probe Storage
There is an increasing need for high density data storage devices driven by
the increased demand of consumer electronics. In this work, we consider a data
storage system that operates by encoding information as topographic profiles on
a polymer medium. A cantilever probe with a sharp tip (few nm radius) is used
to create and sense the presence of topographic profiles, resulting in a
density of few Tb per in.2. The prevalent mode of using the cantilever probe is
the static mode that is harsh on the probe and the media. In this article, the
high quality factor dynamic mode operation, that is less harsh on the media and
the probe, is analyzed. The read operation is modeled as a communication
channel which incorporates system memory due to inter-symbol interference and
the cantilever state. We demonstrate an appropriate level of abstraction of
this complex nanoscale system that obviates the need for an involved physical
model. Next, a solution to the maximum likelihood sequence detection problem
based on the Viterbi algorithm is devised. Experimental and simulation results
demonstrate that the performance of this detector is several orders of
magnitude better than the performance of other existing schemes.Comment: This paper is published in IEEE Trans. on communicatio
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