A Reduced-Complexity Successive Cancellation List Decoding of Polar Codes

Polar codes are the first constructive and provable capacity-achieving codes. In finite code length cases, successive cancellation list (SCL) decoding algorithm is reported to have performance very close to maximum-likelihood (ML) decoding. In this paper, a reduced-complexity version of SCL decoding algorithm is proposed to boost the finite-length performance of polar codes. By regarding the SCL decoding algorithm as a path searching procedure in a code tree representation, a tree-pruning technique is used to avoid unnecessary path searching operations. With only a negligible loss of performance, the computational complexity of pruned SCL decoder can be very close to that of the successive cancellation (SC) decoder in the moderate and high signal-to-noise ratio (SNR) regime.