  Polar codes have been gaining a lot of interest due to it being the first
coding scheme to provably achieve the symmetric capacity of a binary memoryless
channel with an explicit construction. However, the main drawback of polar
codes is the low throughput of its successive cancellation (SC) decoding.
Simplified SC decoding algorithms of polar codes can be used to reduce the
latency of the polar decode by faster processing of specific sub-codes in the
polar code. By combining simplified SC with a list decoding technique, such as
SC list (SCL) decoding, polar codes can cater to the two conflicting
requirements of high reliability and low latency in ultra-reliable low-latency
(URLLC) communication systems. Simplified SC algorithm recognizes some special
nodes in the SC decoding tree, corresponding to the specific subcodes in the
polar code construction, and efficiently prunes the SC decoding tree, without
traversing the sub-trees and computing log-likelihood ratios (LLRs) for each
child node. However, this decoding process still suffers from the latency
associated with the serial nature of SC decoding. We propose some new
algorithms to process new types of node patterns that appear within multiple
levels of pruned sub-trees and it enables to process of certain nodes in
parallel. In short blocklength polar codes, our proposed algorithm can achieve
up to $13\%$ latency reduction from fast-simplified SC \cite{Sarkis2013}
without any performance degradation. Furthermore, it can achieve up to $27\%$
latency reduction if small error-correcting performance degradation is allowed.
