Abstract
We examine the well-known problem of determining the capacity of multi-dimensional run-length-limited constrained systems. By recasting the problem, which is essentially a combinatorial counting problem, into a probabilistic setting, we are able to derive new lower and upper bounds on the capacity of (0,k)-RLL systems. These bounds are better than all previously-known bounds for k ≥ 2, and are even tight asymptotically. Thus, we settle the open question: what is the rate at which the capacity of (0,k)-RLL systems converges to 1 as k → ∞? While doing so, we also provide the first ever non-trivial upper bound on the capacity of general (d,k)-RLL systems.
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Schwartz, M., Vardy, A. (2006). New Bounds on the Capacity of Multi-dimensional RLL-Constrained Systems. In: Fossorier, M.P.C., Imai, H., Lin, S., Poli, A. (eds) Applied Algebra, Algebraic Algorithms and Error-Correcting Codes. AAECC 2006. Lecture Notes in Computer Science, vol 3857. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11617983_22
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DOI: https://doi.org/10.1007/11617983_22
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-31423-3
Online ISBN: 978-3-540-31424-0
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