On Path Memory in List Successive Cancellation Decoder of Polar Codes

TL;DR

This paper proposes two innovative schemes to optimize path memory in list successive cancellation decoders for polar codes, significantly reducing area costs while maintaining decoding performance.

Contribution

It introduces a folded path memory architecture and a memory removal scheme, addressing high area costs in large-scale polar code decoders.

Findings

Folded path memory reduces area by 30%.

Memory removal scheme eliminates the need for path memory.

Experimental results confirm area savings without performance loss.

Abstract

Polar code is a breakthrough in coding theory. Using list successive cancellation decoding with large list size L, polar codes can achieve excellent error correction performance. The L partial decoded vectors are stored in the path memory and updated according to the results of list management. In the state-of-the-art designs, the memories are implemented with registers and a large crossbar is used for copying the partial decoded vectors from one block of memory to another during the update. The architectures are quite area-costly when the code length and list size are large. To solve this problem, we propose two optimization schemes for the path memory in this work. First, a folded path memory architecture is presented to reduce the area cost. Second, we show a scheme that the path memory can be totally removed from the architecture. Experimental results show that these schemes effectively reduce the area of path memory.