학술논문

An Upgrading Algorithm With Optimal Power Law
Document Type
Periodical
Source
IEEE Transactions on Information Theory IEEE Trans. Inform. Theory Information Theory, IEEE Transactions on. 67(12):7822-7836 Dec, 2021
Subject
Communication, Networking and Broadcast Technologies
Signal Processing and Analysis
Polar codes
Approximation algorithms
Random variables
Probability distribution
Mutual information
Markov processes
Costs
Channel upgradation
channel degradation
polar codes
quantization
Language
ISSN
0018-9448
1557-9654
Abstract
Consider a channel $W$ along with a given input distribution $P_{X}$ . In certain settings, such as in the construction of polar codes, the output alphabet of $W$ is ‘too large’, and hence we replace $W$ by a channel $Q$ having a smaller output alphabet. We say that $Q$ is upgraded with respect to $W$ if $W$ is obtained from $Q$ by processing its output. In this case, the mutual information $I(P_{X},W)$ between the input and output of $W$ is upper-bounded by the mutual information $I(P_{X},Q)$ between the input and output of $Q$ . In this paper, we present an algorithm that produces an upgraded channel $Q$ from $W$ , as a function of $P_{X}$ and the required output alphabet size of $Q$ , denoted $L$ . We show that the difference in mutual informations is ‘small’. Namely, it is $O(L^{-2/(| \mathcal {X}|-1)})$ , where $| \mathcal {X}|$ is the size of the input alphabet. This power law of $L$ is optimal. We complement our analysis with numerical experiments which show that the developed algorithm improves upon the existing state-of-the-art algorithms also in non-asymptotic setups.