Low Complexity Belief Propagation Polar Code Decoder

Since their invention, polar codes have received a lot of attention because of their capacity-achieving performance and low encoding and decoding complexity. Successive cancellation decoding (SCD) and belief propagation decoding (BPD) are two approaches for decoding polar codes. SCD is able to achieve good error-correcting performance and is less computationally expensive as compared to BPD. However SCD suffers from long latency due to the serial nature of the successive cancellation algorithm. BPD is parallel in nature and hence is more attractive for low latency applications. However, since it is iterative, 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.