BICM-compatible Rate Adaptive Geometric Constellation Shaping Using Optimized Many-to-one Labeling
In this paper, a rate adaptive geometric constellation shaping (GCS) scheme which is fully backward-compatible with existing state of the art bit-interleaved coded modulation (BICM) systems is proposed and experimentally demonstrated. The system relies on optimization of the positions of the quadrature amplitude modulation (QAM) points on the I/Q plane for maximized achievable information rate, while maintaining quantization and fiber nonlinear noise robustness. Furthermore, dummy' bits are multiplexed with coded bits before mapping to symbols. Rate adaptivity is achieved by tuning the ratio of coded and dummy' bits, while maintaining a fixed forward error-correction block and a fixed modulation format size. The points' positions and their labeling are optimized using automatic differentiation. The proposed GCS scheme is compared to a time-sharing hybrid (TH) QAM modulation and the now mainstream probabilistic amplitude shaping (PAS) scheme. The TH without shaping is outperformed for all studied data rates in a simulated linear channel by up to 0.7 dB. In a linear channel, PAS is shown to outperform the proposed GCS scheme, while similar performances are reported for PAS and the proposed GCS in a simulated nonlinear fiber channel. The GCS scheme is experimentally demonstrated in a multi-span recirculating loop coherent optical fiber transmission system with a total distance of up to 3000 km. Near-continuous zero-error flexible throughput is reported as a function of the transmission distance. Up to 1-2 spans of increased reach gains are achieved at the same net data rate w.r.t. conventional QAM. At a given distance, up to 0.79 bits/2D symbol of gain w.r.t. conventional QAM is achieved. In the experiment, similar performance to PAS is demonstrated.
Code (0)
등록된 구현이 없습니다.
Tasks
QuantizationSimilar Papers 제목 키워드 기반
End-to-end Learning for GMI Optimized Geometric Constellation Shape
Autoencoder-based geometric shaping is proposed that includes optimizing bit mappings. Up to 0.2 bits/QAM symbol gain in GMI is achieved for a variety of data rates and in the presence of transceiver impairments. The gai…
Experimental Demonstration of 16D Voronoi Constellation with Two-Level Coding over 50km Four-Core Fiber
A 16-dimensional Voronoi constellation concatenated with multilevel coding is experimentally demonstrated over a 50km four-core fiber transmission system. The proposed scheme reduces the required launch power by 6dB and …
Rate Adaptive Geometric Constellation Shaping Using Autoencoders and Many-To-One Mapping
A many-to-one mapping geometric constellation shaping scheme is proposed with a fixed modulation format, fixed FEC engine and rate adaptation with an arbitrarily small step. An autoencoder is used to optimize the labelin…
Geometric Constellation Shaping for Fiber Optic Communication Systems via End-to-end Learning
In this paper, an unsupervised machine learning method for geometric constellation shaping is investigated. By embedding a differentiable fiber channel model within two neural networks, the learning algorithm is optimizi…
BIG-bench Machine LearningExperimental Validation of Sequence-Wise Predistorter for Evaluation of Geometrically Shaped 128-QAM
A predistorter for transmitter nonlinearities is applied to the evaluation of a geometrically shaped constellation, such that constellation points are transmitted correctly during the evaluation of the geometrically shap…