Feedback Capacity and Coding for the $(0,k)$-RLL Input-Constrained BEC
Ori Peled, Oron Sabag, Haim H. Permuter

TL;DR
This paper derives the feedback capacity of the input-constrained binary erasure channel with a $(0,k)$-RLL constraint, showing it can be achieved with zero-error, variable length coding, and that non-causal knowledge does not increase capacity for this case.
Contribution
The paper provides a closed-form expression for the feedback capacity of the $(0,k)$-RLL input-constrained BEC and proves that non-causal knowledge does not improve capacity in this setting.
Findings
Feedback capacity is explicitly characterized for all $k\\geq 1$.
Zero-error, variable length coding achieves the feedback capacity.
Non-causal knowledge does not increase capacity for the $(0,k)$-RLL BEC.
Abstract
The input-constrained binary erasure channel (BEC) with strictly causal feedback is studied. The channel input sequence must satisfy the -runlength limited (RLL) constraint, i.e., no more than consecutive `'s are allowed. The feedback capacity of this channel is derived for all , and is given by where is the erasure probability, and is the binary entropy function. The maximization is only over , while the parameters for are straightforward functions of . The lower bound is obtained…
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