  Since its invention, polar code has received a lot of attention because of
its capacity-achieving performance and low encoding and decoding complexity.
Successive cancellation decoding (SCD) and belief propagation decoding (BPD)
are two of the most popular approaches for decoding polar codes. SCD is able to
achieve good error-correcting performance and is less computationally expensive
as compared to BPD. However SCDs suffer from long latency and low throughput
due to the serial nature of the successive cancellation algorithm. BPD is
parallel in nature and hence is more attractive for high throughput
applications. However since it is iterative in nature, the required latency and
energy dissipation increases linearly with the number of iterations. In this
work, we borrow the idea of SCD and propose a novel scheme based on
sub-factor-graph freezing to reduce the average number of computations as well
as the average number of iterations required by BPD, which directly translates
into lower latency and energy dissipation. Simulation results show that the
proposed scheme has no performance degradation and achieves significant
reduction in computation complexity over the existing methods.
