Enhanced SVM Detection for Probabilistically-shaped 16QAM with Markov Chain Monte Carlo
YuZhong Feng; ShaoHua Hu; Jing Zhang; PingPing Lei; Bi Tang; Kun Qiu;
Enhanced SVM Detection for Probabilistically-shaped 16QAM with Markov Chain Monte Carlo
We propose and experimentally demonstrate a MCMC-aided SVM for PS-16QAM systems. This method mitigates the inequality in probabilities of PS-16QAM and part fiber nonlinearity, which enable it has a performance gain compared with MAP decision.
- University of Electronic Science and Technology of China China (People's Republic of)
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These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
Citations provided by BIP!popularityPopularity provided by BIP!
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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