Construction of polar codes for arbitrary discrete memoryless channels

TL;DR

This paper presents a practical algorithm for constructing polar codes over arbitrary discrete memoryless channels, reducing complexity and improving efficiency for larger alphabets while maintaining near-capacity performance.

Contribution

It introduces a novel alphabet reduction algorithm for polar code construction applicable to general input alphabets, with complexity analysis and capacity-preserving symbol merging techniques.

Findings

Algorithm achieves construction for alphabets of size 16+

Complexity scales as O(Nμ^4) with quantization parameter μ

Codes constructed with the method have small gap to capacity

Abstract

It is known that polar codes can be efficiently constructed for binary-input channels. At the same time, existing algorithms for general input alphabets are less practical because of high complexity. We address the construction problem for the general case, and analyze an algorithm that is based on successive reduction of the output alphabet size of the subchannels in each recursion step. For this procedure we estimate the approximation error as $O(\mu^{-1/(q-1)}),$ where $\mu$ is the "quantization parameter," i.e., the maximum size of the subchannel output alphabet allowed by the algorithm. The complexity of the code construction scales as $O(N\mu^4),$ where $N$ is the length of the code. We also show that if the polarizing operation relies on modulo-$q$ addition, it is possible to merge subsets of output symbols without any loss in subchannel capacity. Performing this procedure before each approximation step results in a further speed-up of the code construction, and the resulting codes have smaller gap to capacity. We show that a similar acceleration can be attained for polar codes over finite field alphabets. Experimentation shows that the suggested construction algorithms can be used to construct long polar codes for alphabets of size $q=16$ and more with acceptable loss of the code rate for a variety of polarizing transforms.