743 research outputs found
Performance Metrics for Systems with Soft-Decision FEC and Probabilistic Shaping
High-throughput optical communication systems utilize binary soft-decision
forward error correction (SD-FEC) with bit interleaving over the bit channels.
The generalized mutual information (GMI) is an achievable information rate
(AIR) in such systems and is known to be a good predictor of the bit error rate
after SD-FEC decoding (post-FEC BER) for uniform signaling. However, for
probabilistically shaped (nonuniform) signaling, we find that the normalized
AIR, defined as the AIR divided by the signal entropy, is less correlated with
the post-FEC BER. We show that the information quantity based on the
distribution of the single bit signal, and its asymmetric loglikelihood ratio,
are better predictors of the post-FEC BER. In simulations over the Gaussian
channel, we find that the prediction accuracy, quantified as the peak-to-peak
deviation of the post-FEC BER within a set of different modulation formats and
distributions, can be improved more than 10 times compared with the normalized
AIR.Comment: 4 pages, 3 figure
Ultra-Sparse Non-Binary LDPC Codes for Probabilistic Amplitude Shaping
This work shows how non-binary low-density parity-check codes over GF()
can be combined with probabilistic amplitude shaping (PAS) (B\"ocherer, et al.,
2015), which combines forward-error correction with non-uniform signaling for
power-efficient communication. Ultra-sparse low-density parity-check codes over
GF(64) and GF(256) gain 0.6 dB in power efficiency over state-of-the-art binary
LDPC codes at a spectral efficiency of 1.5 bits per channel use and a
blocklength of 576 bits. The simulation results are compared to finite length
coding bounds and complemented by density evolution analysis.Comment: Accepted for Globecom 201
Capacity-Achieving Codes with Bounded Graphical Complexity on Noisy Channels
We introduce a new family of concatenated codes with an outer low-density
parity-check (LDPC) code and an inner low-density generator matrix (LDGM) code,
and prove that these codes can achieve capacity under any memoryless
binary-input output-symmetric (MBIOS) channel using maximum-likelihood (ML)
decoding with bounded graphical complexity, i.e., the number of edges per
information bit in their graphical representation is bounded. In particular, we
also show that these codes can achieve capacity on the binary erasure channel
(BEC) under belief propagation (BP) decoding with bounded decoding complexity
per information bit per iteration for all erasure probabilities in (0, 1). By
deriving and analyzing the average weight distribution (AWD) and the
corresponding asymptotic growth rate of these codes with a rate-1 inner LDGM
code, we also show that these codes achieve the Gilbert-Varshamov bound with
asymptotically high probability. This result can be attributed to the presence
of the inner rate-1 LDGM code, which is demonstrated to help eliminate high
weight codewords in the LDPC code while maintaining a vanishingly small amount
of low weight codewords.Comment: 17 pages, 2 figures. This paper is to be presented in the 43rd Annual
Allerton Conference on Communication, Control and Computing, Monticello, IL,
USA, Sept. 28-30, 200
Bit-Metric Decoding of Non-Binary LDPC Codes with Probabilistic Amplitude Shaping
A new approach for combining non-binary low-density parity-check (NB-LDPC)
codes with higher-order modulation and probabilistic amplitude shaping (PAS) is
presented. Instead of symbol-metric decoding (SMD), a bit-metric decoder (BMD)
is used so that matching the field order of the non-binary code to the
constellation size is not needed, which increases the flexibility of the coding
scheme. Information rates, density evolution thresholds and finite-length
simulations show that the flexibility comes at no loss of performance if PAS is
used.Comment: Accepted for IEEE Communication Letter
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