Deterministic list codes for state-constrained arbitrarily varying channels

Anand D. Sarwate, Michael Gastpar

Abstract: List decoding for arbitrarily varying channels (AVCs) under state constraints is investigated. It is shown that rates within $\epsilon$ of the randomized coding capacity of AVCs with input-dependent state can be achieved under maximal error with list decoding using lists of size $O(1/\epsilon)$. Under average error an achievable rate region and converse bound are given for lists of size $L$. These bounds are based on two different notions of symmetrizability and do not coincide in general. An example is given that shows that for list size $L$ the capacity may be positive but strictly smaller than the randomized coding capacity. This behavior is different than the situation without state constraints.