Look-Up-Table Decoding and Architecture Optimization for Scale-Min-Sum Polar Decoders

As to realize believe propagation (BP) for polar decoding, the scaled min-sum (SMS) algorithm is widely used in hardware realization for polar decoders. However, the decoding performance of SMS algorithm is still not good as the length of polar codes increase, and its computing architecture,which called processing elements (PE) needs to be further optimized due to its long critical path. In this paper, referring to the method used in LDPC/Turbo decoding, a look-up-table (LUT) algorithm and its modified version called LUT-SMS are proposed for polar decoding. The simulation result shows that, compared with the SMS algorithm, the proposed LUT-SMS algorithm can lead to 0.3 dB extra decoding gain when the code length up to 2048. For a different trade-off, a new SMS computing architecture which has shorter computing path is proposed to solve the long delay of the polar decoders. The hardware implementation result shows that, the optimized SMS computing architecture can also achieve more than 32% increase in throughput for the case of (256,128) polar decoder without much extra hardware consumption. As a result, both these two optimization schemes have good promotion for polar decoding.