Shannon Meets Turing: Non-Computability and Non-Approximability of the Finite State Channel Capacity
Holger Boche, Rafael F. Schaefer, H. Vincent Poor

TL;DR
This paper proves that the capacity of finite state channels cannot be computed or approximated algorithmically, highlighting fundamental limits on characterizing their capacity with finite-letter formulas.
Contribution
It establishes the non-computability and non-approximability of FSC capacity using Turing machine theory, revealing intrinsic computational barriers.
Findings
FSC capacity is not Banach-Mazur computable.
No algorithm can compute the capacity of a given FSC.
FSC capacity cannot be approximated or characterized finitely.
Abstract
The capacity of finite state channels (FSCs) has been established as the limit of a sequence of multi-letter expressions only and, despite tremendous effort, a corresponding finite-letter characterization remains unknown to date. This paper analyzes the capacity of FSCs from a fundamental, algorithmic point of view by studying whether or not the corresponding achievability and converse bounds on the capacity can be computed algorithmically. For this purpose, the concept of Turing machines is used which provide the fundamental performance limits of digital computers. To this end, computable continuous functions are studied and properties of computable sequences of such functions are identified. It is shown that the capacity of FSCs is not Banach-Mazur computable which is the weakest form of computability. This implies that there is no algorithm (or Turing machine) that can compute the…
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