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The decoding performance of polar codes strongly depends on the decodingalgorithm used, while also the decoder throughput and its latency mainly dependon the decoding algorithm. In this work, we implement the powerful successivecancellation list (SCL) decoder on a GPU and identify the bottlenecks of thisalgorithm with respect to parallel computing and its difficulties. The inherentserial decoding property of the SCL algorithm naturally limits the achievablespeed-up gains on GPUs when compared to CPU implementations. In order toincrease the decoding throughput, we use a hybrid decoding scheme based on thebelief propagation (BP) decoder, which can be intra and inter-frameparallelized. The proposed scheme combines excellent decoding performance andhigh throughput within the signal-to-noise ratio (SNR) region of interest.

Combining Belief Propagation and Successive Cancellation List Decoding of Polar Codes on a GPU Platform