  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.
