7,285 research outputs found
Belief propagation decoding of quantum channels by passing quantum messages
Belief propagation is a powerful tool in statistical physics, machine
learning, and modern coding theory. As a decoding method, it is ubiquitous in
classical error correction and has also been applied to stabilizer-based
quantum error correction. The algorithm works by passing messages between nodes
of the factor graph associated with the code and enables efficient decoding, in
some cases even up to the Shannon capacity of the channel. Here we construct a
belief propagation algorithm which passes quantum messages on the factor graph
and is capable of decoding the classical-quantum channel with pure state
outputs. This gives explicit decoding circuits whose number of gates is
quadratic in the blocklength of the code. We also show that this decoder can be
modified to work with polar codes for the pure state channel and as part of a
polar decoder for transmitting quantum information over the amplitude damping
channel. These represent the first explicit capacity-achieving decoders for
non-Pauli channels.Comment: v3: final version for publication; v2: improved discussion of the
algorithm; 7 pages & 2 figures. v1: 6 pages, 1 figur
Decoder-in-the-Loop: Genetic Optimization-based LDPC Code Design
LDPC code design tools typically rely on asymptotic code behavior and are
affected by an unavoidable performance degradation due to model imperfections
in the short length regime. We propose an LDPC code design scheme based on an
evolutionary algorithm, the Genetic Algorithm (GenAlg), implementing a
"decoder-in-the-loop" concept. It inherently takes into consideration the
channel, code length and the number of iterations while optimizing the
error-rate of the actual decoder hardware architecture. We construct short
length LDPC codes (i.e., the parity-check matrix) with error-rate performance
comparable to, or even outperforming that of well-designed standardized short
length LDPC codes over both AWGN and Rayleigh fading channels. Our proposed
algorithm can be used to design LDPC codes with special graph structures (e.g.,
accumulator-based codes) to facilitate the encoding step, or to satisfy any
other practical requirement. Moreover, GenAlg can be used to design LDPC codes
with the aim of reducing decoding latency and complexity, leading to coding
gains of up to dB and dB at BLER of for both AWGN and
Rayleigh fading channels, respectively, when compared to state-of-the-art short
LDPC codes. Also, we analyze what can be learned from the resulting codes and,
as such, the GenAlg particularly highlights design paradigms of short length
LDPC codes (e.g., codes with degree-1 variable nodes obtain very good results).Comment: in IEEE Access, 201
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