Gilbert-Varshamov Bound for Codes in Metric using Multivariate Analytic Combinatorics
arXiv:2402.14712 · doi:10.1109/TIT.2024.3483303
Abstract
Analytic combinatorics in several variables refers to a suite of tools that provide sharp asymptotic estimates for certain combinatorial quantities. In this paper, we apply these tools to determine the Gilbert--Varshamov lower bound on the rate of optimal codes in metric. Several different code spaces are analyzed, including the simplex and the hypercube in , all of which are inspired by concrete data storage and transmission models such as the sticky insertion channel, the permutation channel, the adjacent transposition (bit-shift) channel, the multilevel flash memory channel, etc.
33 pages, 3 figures, submitted to IEEE Transactions on Information Theory
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