REVIEW 3 cited by
Achievable Rates for Probabilistic Shaping
Not yet reviewed by Pith; the record is open.
This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.
SPECIMEN: schema-true, not a live event
T0 review · schema-true
One-sentence machine reading of the paper's core claim.
pith:XXXXXXXX · record.json · timestamp
Signed reviews
read the original abstract
For a layered probabilistic shaping (PS) scheme with a general decoding metric, an achievable rate is derived using Gallager's error exponent approach and the concept of achievable code rates is introduced. Several instances for specific decoding metrics are discussed, including bit-metric decoding, interleaved coded modulation, and hard-decision decoding. It is shown that important previously known achievable rates can also be achieved by layered PS. A practical instance of layered PS is the recently proposed probabilistic amplitude shaping (PAS).
Forward citations
Cited by 3 Pith papers
-
End-to-End Learning of Probabilistic Constellation Shaping through Importance Sampling
Importance-sampling weighted loss functions enable autoencoder-based probabilistic constellation shaping with exact automatic-differentiation gradients, matching prior methods in AWGN and IM/DD simulations.
-
Joint Detection and Decoding: A Graph Neural Network Approach
Graph neural networks operating on channel factor graphs and code Tanner graphs achieve near-optimal detection and joint detection and decoding on ISI channels, outperforming feasible classical baselines.
-
On Product Codes with Probabilistic Amplitude Shaping for High-Throughput Fiber-Optic Systems
Probabilistic amplitude shaping with product codes and hard-decision decoding achieves up to 2.7 dB gain and 1 bpcu spectral efficiency improvement over uniform signaling, with component-code parameters constrained by...
Discussion (0). Continue with ORCID to comment.