Technical Report MSC-1996-01

TR#:MSC-1996-01
Class:MSC
Title: Encoding for Input-Constrained Channels
Authors: Gitit Ruckenstein (Ronny Roth)
PDFMSC-1996-01.pdf
Abstract: Input-constrained channels are models for describing the read-write requirements of secondary storage systems, such as magnetic disks or optical devices. Examples for such requirements are the widely used (d,k)-run-length-limited (RLL) constraints, where each run of 0's between consecutive 1's in a binary sequence must have length at least d and at most k. A constrained system S is defined as the set of constrained sequences obtained by reading the labels of paths of a finite labelled directed graph G. The graph G is then called the presentation of S. One goal in the study of constrained systems is designing encoders that map unconstrained sequences into constrained sequences of a given constrained system S. A fixed rate p:q finite-state encoder for S encodes p-blocks of input bits to q-blocks in S, in a state-dependent and lossless manner. The anticipation (or decoding look-ahead) of an encoder is the smallest integer A, if any, such that the encoder state at each time slot t, together with the q-blocks generated at times t,t+1,...,t+A, determine uniquely the p-block input at time slot t. One of the well known schemes for constructing finite-state encoders is the Adler-Coppersmith-Hassner algorithm, also known as the state-splitting algorithm. Any encoder obtained by the state-splitting algorithm from a deterministic presentation G has finite anticipation. In this work, we present lower bounds on the anticipation of encoders for given constrained systems, while strengthening the universality of the state-splitting algorithm. It is shown that if there exists an encoder with anticipation A for a given system, then an unreduced version of this encoder can be obtained by the state-splitting algorithm, using A rounds of splitting. Furthermore, by specifying several properties of those splittings, we obtain a lower bound on the anticipation of any encoder for a given constrained system. The new lower bound improves on previous known bounds and in particular, it is tight for several known and widely used systems, such as the (1,7)-RLL and the (2,7)-RLL constrained systems.
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