Coding on Dual-Parameter Barrier Channels beyond Worst-Case Correction
Yuval Ben-Hur, Yuval Cassuto · 2021 IEEE Global Communications Conference (GLOBECOM) · 2021
This paper studies coding on channels with the barrier property: only errors to and from a special barrier state are possible. This model is motivated by storage media that have heterogeneous state structure, not admitting the usual multi-bit scaling of the representation states. Our contributions include derivation of the channel capacity, efficient maximum-likelihood and list decoding algorithms, and finite-block-length analysis using random codes. This work is the first that addresses a barrier channel with separate parameters for the transitions into and out of the barrier state. Earlier work addressed special-case single-parameter models, and focused primarily on the worst-case coding performance.