Infinite-Alphabet Prefix Codes Optimal for $\beta$-Exponential Penalties

TL;DR

This paper develops methods for constructing optimal prefix codes for infinite alphabets under nonlinear exponential mean penalties, addressing applications like communication reliability and queueing buffer management.

Contribution

It introduces novel algorithms for finding optimal codes for exponential mean criteria, including specific methods for geometric and Poisson distributions.

Findings

Algorithms for geometric distributions

Algorithms for Poisson distributions

Extensions to minimizing maximum pointwise redundancy

Abstract

Let $P = \{p(i)\}$ be a measure of strictly positive probabilities on the set of nonnegative integers. Although the countable number of inputs prevents usage of the Huffman algorithm, there are nontrivial $P$ for which known methods find a source code that is optimal in the sense of minimizing expected codeword length. For some applications, however, a source code should instead minimize one of a family of nonlinear objective functions, $\beta$-exponential means, those of the form $\log_a \sum_i p(i) a^{n(i)}$, where $n(i)$ is the length of the $i$th codeword and $a$ is a positive constant. Applications of such minimizations include a problem of maximizing the chance of message receipt in single-shot communications ($a<1$) and a problem of minimizing the chance of buffer overflow in a queueing system ($a>1$). This paper introduces methods for finding codes optimal for such exponential means. One method applies to geometric distributions, while another applies to distributions with lighter tails. The latter algorithm is applied to Poisson distributions. Both are extended to minimizing maximum pointwise redundancy.