Near Optimal Decoding of Polar-based Turbo Product Codes
Meng Ruan, Ming Jiang, Tao Zou, Yi Sun, Chunming Zhao · 2019
In this paper, an efficient decoding algorithm for the turbo product code (TPC) with short-block constituent polar codes (polar-TPC) is proposed. We show that the constituent codes can be either systematic or non-systematic, and they can be decoded in parallel. A flipping-based successive cancellation list (SCL) decoder is employed to decode each constituent code and provide a larger code set, from which extrinsic information can be obtained to update the soft input in the next decoding iteration. Simulation results show that the polar-TPC employing our decoding scheme can outperform the BCH-TPC. This decoding scheme, which is compatible with any SCL decoding based acceleration algorithm, offers an effective solution to decrease the decoding latency of long codes while similar decoding performance can be guaranteed.