On Path Memory in List Successive Cancellation Decoder of Polar Codes

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.