High-Throughput and Energy-Efficient Belief Propagation Polar Code Decoder - 2017


Owing to their capacity-achieving performance and low encoding and decoding complexity, polar codes have received significant attention recently. Successive cancellation decoding (SCD) and belief propagation decoding (BPD) are two popular approaches for decoding polar codes. SCD, despite having less computational complexity compared with BPD, suffers from long latency thanks to the serial nature of the SC algorithm. BPD, on the other hand, is parallel in nature and is more engaging for low-latency applications. However, because of the iterative nature of BPD, the specified latency and energy dissipation increase linearly with the quantity of iterations. In this paper, we tend to propose a completely unique theme based mostly on subfactor-graph freezing to cut back the typical number of computations plus the average range 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 vital reduction in computation complexity over the existing strategies. Moreover, the hardware design for the proposed theme is developed and compared with the state-of-the-art BPD implementations for (1024, 512) polar codes. A decoding throughput of thirteen.9 Gb/s is achieved together with a 60percent-73percent improvement in energy reduction and 2 times increase in hardware efficiency compared with the prevailing BPD implementations.

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