Architecture and optimization of high-throughput belief propagation decoding of polar codes
Shuanghong Sun, Zhengya Zhang · 2016
Belief propagation (BP) is one common decoding algorithm for polar codes. BP can be implemented using a forward-backward flooding schedule that removes the data dependency. The intrinsic parallelism of the BP algorithm permits a high throughput. In this paper, we present a parallel BP decoder design space exploration. Through gate-level implementations, we analyze the silicon area, throughput, and power consumption of each design. We present adaptive quantization and early convergence detection to improve the error-correcting performance and throughput of BP decoders.