36 research outputs found
Temporal Properties of Enumerative Shaping:Autocorrelation and Energy Dispersion Index
We study the effective SNR behavior of various enumerative amplitude shaping algorithms. We show that their relative behavior can be explained via the temporal autocorrelation function or via the energy dispersion index
Reducing the Error Floor of the Sign-Preserving Min-Sum LDPC Decoder via Message Weighting of Low-Degree Variable Nodes
Some low-complexity LDPC decoders suffer from error floors. We apply iteration-dependent weights to the degree-3 variable nodes to solve this problem. When the 802.3ca EPON LDPC code is considered, an error floor decrease of more than 3 orders of magnitude is achieve
Low-Complexity Soft-Decision Detection for Combating DFE Burst Errors in IM/DD Links
The deployment of non-binary pulse amplitude modulation (PAM) and soft
decision (SD)-forward error correction (FEC) in future intensity-modulation
(IM)/direct-detection (DD) links is inevitable. However, high-speed IM/DD links
suffer from inter-symbol interference (ISI) due to bandwidth-limited hardware.
Traditional approaches to mitigate the effects of ISI are filters and
trellis-based algorithms targeting symbol-wise maximum a posteriori (MAP)
detection. The former approach includes decision-feedback equalizer (DFE), and
the latter includes Max-Log-MAP (MLM) and soft-output Viterbi algorithm (SOVA).
Although DFE is easy to implement, it introduces error propagation. Such burst
errors distort the log-likelihood ratios (LLRs) required by SD-FEC, causing
performance degradation. On the other hand, MLM and SOVA provide near-optimum
performance, but their complexity is very high for high-order PAM. In this
paper, we consider a one-tap partial response channel model, which is relevant
for high-speed IM/DD links. We propose to combine DFE with either MLM or SOVA
in a low-complexity architecture. The key idea is to allow MLM or SOVA to
detect only 3 typical DFE symbol errors, and use the detected error information
to generate LLRs in a modified demapper. The proposed structure enables a
tradeoff between complexity and performance: (i) the complexity of MLM or SOVA
is reduced and (ii) the decoding penalty due to error propagation is mitigated.
Compared to SOVA detection, the proposed scheme can achieve a significant
complexity reduction of up to 94% for PAM-8 transmission. Simulation and
experimental results show that the resulting SNR loss is roughly 0.3 to 0.4 dB
for PAM-4, and becomes marginal 0.18 dB for PAM-8.Comment: This manuscript has been submitted to JL
Exponentially-Weighted Energy Dispersion Index for the Nonlinear Interference Analysis of Finite-Blocklength Shaping
A metric called exponentially-weighted energy dispersion index (EEDI) is
proposed to explain the blocklength-dependent effective signal-to-noise ratio
(SNR) in probabilistically shaped fiber-optic systems. EEDI is better than
energy dispersion index (EDI) at capturing the dependency of the effective SNR
on the blocklength for long-distance transmission
Amplitude shaping method, receiving method, processing unit and generator unit for an amplitude shaper, and an amplitude shaper
Amplitude shaping method, receiving method, processing unit and generator unit for an amplitude shaper, and an amplitude shaper
DFE State-Tracking Demapper for Soft-Input FEC in 800G Data Center Interconnects
A simple one-step state model is used to track the DFE error propagation for 4-PAM. The knowledge of DFE output states is used to improve LLR accuracy. Demapping via DFE state tracking outperforms bit-interleaving and precoding schemes for the 802.3ca LDPC code by 0.76 dB
DFE State-Tracking Demapper for Soft-Input FEC in 800G Data Center Interconnects
A simple one-step state model is used to track the DFE error propagation for 4-PAM. The knowledge of DFE output states is used to improve LLR accuracy. Demapping via DFE state tracking outperforms bit-interleaving and precoding schemes for the 802.3ca LDPC code by 0.76 dB