1 research outputs found
Decoder-tailored Polar Code Design Using the Genetic Algorithm
We propose a new framework for constructing polar codes (i.e., selecting the
frozen bit positions) for arbitrary channels, and tailored to a given decoding
algorithm, rather than based on the (not necessarily optimal) assumption of
successive cancellation (SC) decoding. The proposed framework is based on the
Genetic Algorithm (GenAlg), where populations (i.e., collections) of
information sets evolve successively via evolutionary transformations based on
their individual error-rate performance. These populations converge towards an
information set that fits both the decoding behavior and the defined channel.
Using our proposed algorithm over the additive white Gaussian noise (AWGN)
channel, we construct a polar code of length 2048 with code rate 0.5, without
the CRC-aid, tailored to plain successive cancellation list (SCL) decoding,
achieving the same error-rate performance as the CRC-aided SCL decoding, and
leading to a coding gain of 1 dB at BER of . Further, a belief
propagation (BP)-tailored construction approaches the SCL error-rate
performance without any modifications in the decoding algorithm itself. The
performance gains can be attributed to the significant reduction in the total
number of low-weight codewords. To demonstrate the flexibility, coding gains
for the Rayleigh channel are shown under SCL and BP decoding. Besides
improvements in error-rate performance, we show that, when required, the GenAlg
can be also set up to reduce the decoding complexity, e.g., the SCL list size
or the number of BP iterations can be reduced, while maintaining the same
error-rate performance.Comment: This work has been submitted to the IEEE for possible publication.
Manuscript submitted September 20, 2018; revised January 28, 2019; date of
current version January 28, 2019. arXiv admin note: substantial text overlap
with arXiv:1901.0644