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We propose an Gaussian Mixture Model (GMM) learning algorithm, based on our previous work of GMM expansion idea. The new algorithm brings more robustness and simplicity than classic Expectation Maximization (EM) algorithm. It also improves…

Machine Learning · Computer Science 2023-09-07 Weiguo Lu , Xuan Wu , Deng Ding , Gangnan Yuan

Constellation shaping is reviewed and revised for a WDM unrepeated system with high spectral efficiency. It is shown that for a constellation size-constrained system, previous optimization techniques can be highly sub-optimal, and a…

Optimization and Control · Mathematics 2019-11-06 Metodi P. Yankov

The probabilistic shaping scheme from Honda and Yamamoto (2013) for polar codes is used to enable power-efficient signaling for on-off keying (OOK). As OOK has a non-symmetric optimal input distribution, shaping approaches that are based on…

Information Theory · Computer Science 2019-07-22 Thomas Wiegart , Fabian Steiner , Patrick Schulte , Peihong Yuan

This work shows how non-binary low-density parity-check codes over GF($2^p$) can be combined with probabilistic amplitude shaping (PAS) (B\"ocherer, et al., 2015), which combines forward-error correction with non-uniform signaling for…

Information Theory · Computer Science 2017-08-21 Fabian Steiner , Gianluigi Liva , Georg Böcherer

Hardware distortions (HWD) render drastic effects on the performance of communication systems. They are recently proven to bear asymmetric signatures; and hence can be efficiently mitigated using improper Gaussian signaling (IGS), thanks to…

Signal Processing · Electrical Eng. & Systems 2020-09-14 Sidrah Javed , Ahmed Elzanaty , Osama Amin , Basem Shihada , Mohamed-Slim Alouini

Integrated sensing and communications (ISAC) promises new use cases for mobile communication systems by reusing the communication signal for radar-like sensing. However, sensing and communications (S&C) impose conflicting requirements on…

Signal Processing · Electrical Eng. & Systems 2026-02-23 Benedikt Geiger , Fan Liu , Shihang Lu , Andrej Rode , Daniel Gil Gaviria , Charlotte Muth , Laurent Schmalen

This letter proposes superposing two Generalized Quadratic Noise Modulators (GQNM) by simply adding their outputs. It creates a 16-ary noise modulator that resembles QAM modulators in classical communication. It modulates the information…

Signal Processing · Electrical Eng. & Systems 2025-10-03 Hadi Zayyani , Mohammad Salman , Felipe A. P. de Figueiredo , Rausley A. A. de Souza

We study the theoretical performance of a combined approach to demodulation and decoding of binary continuous-phase modulated signals under repetition-like codes. This technique is motivated by a need to transmit packetized or framed data…

Information Theory · Computer Science 2014-04-28 Gaurav Thakur

A new geometric shaping method is proposed, leveraging unsupervised machine learning to optimize the constellation design. The learned constellation mitigates nonlinear effects with gains up to 0.13 bit/4D when trained with a simplified…

Information Theory · Computer Science 2018-05-11 Rasmus T. Jones , Tobias A. Eriksson , Metodi P. Yankov , Darko Zibar

The wideband regime of bit-interleaved coded modulation (BICM) in Gaussian channels is studied. The Taylor expansion of the coded modulation capacity for generic signal constellations at low signal-to-noise ratio (SNR) is derived and used…

Information Theory · Computer Science 2007-10-23 Alfonso Martinez , Albert Guillen i Fabregas , Giuseppe Caire , Frans Willems

Estimating probabilistic deformable template models is a new approach in the fields of computer vision and probabilistic atlases in computational anatomy. A first coherent statistical framework modelling the variability as a hidden random…

Computation · Statistics 2009-01-16 Stéphanie Allassonnière , Estelle Kuhn

Learning parameters from voluminous data can be prohibitive in terms of memory and computational requirements. We propose a "compressive learning" framework where we estimate model parameters from a sketch of the training data. This sketch…

Machine Learning · Computer Science 2017-05-08 Nicolas Keriven , Anthony Bourrier , Rémi Gribonval , Patrick Pérez

In this paper, we investigate the signal shaping in a two-user discrete time memoryless Gaussian multiple-access channel (MAC) with computation. It is shown that by optimizing input probability distribution, the transmission rate per…

Information Theory · Computer Science 2017-01-26 Zhiyong Chen , Hui Liu

Probabilistic amplitude shaping (PAS) is on track to become the de facto coded modulation standard for communication systems aiming to operate close to channel capacity at high transmission rates. The essential component of PAS that breeds…

Information Theory · Computer Science 2022-08-16 Yunus Can Gültekin , Frans M. J. Willems , Alex Alvarado

We consider a trainable point-to-point communication system, where both transmitter and receiver are implemented as neural networks (NNs), and demonstrate that training on the bit-wise mutual information (BMI) allows seamless integration…

Information Theory · Computer Science 2020-06-08 Sebastian Cammerer , Fayçal Ait Aoudia , Sebastian Dörner , Maximilian Stark , Jakob Hoydis , Stephan ten Brink

A new coded modulation scheme is proposed. At the transmitter, the concatenation of a distribution matcher and a systematic binary encoder performs probabilistic signal shaping and channel coding. At the receiver, the output of a bitwise…

Information Theory · Computer Science 2015-04-23 Georg Böcherer , Patrick Schulte , Fabian Steiner

Spatial modulation (SM) transmits additional information bits by the selection of antennas. Generalized spatial modulation (GSM), as an advanced type of SM, can be divided into diversity and multiplexing (MUX) schemes according to the…

Information Theory · Computer Science 2024-04-16 Xinghao Guo , Yin Xu , Hanjiang Hong , De Mi , Ruiqi Liu , Dazhi He , Wenjun Zhang , Yi-yan Wu

This work develops a rate-distortion-based approach to stochastic Chase decoding of algebraic codes over binary memoryless symmetric (BMS) channels, replacing the heuristics traditionally used to determine flip probabilities with…

Information Theory · Computer Science 2026-05-20 Amit Berman , Ariel Doubchak , Uri Erez , Tal Philosof , Ilya Shapir

Bit-interleaved coded modulation with iterative decoding (BICM-ID) offers very good error performance over additive white Gaussian noise (AWGN) and fading channels if it uses a wisely designed signal mapping. Further, error performance of…

Information Theory · Computer Science 2017-01-06 Hassan M. Navazi , Md. Jahangir Hossain

Shaping modulation formats in multi-dimensional (MD) space is an effective approach to harvest spectral efficiency gains in both the additive white Gaussian noise (AWGN) channel and the optical fiber channel. In the first part of this…

Information Theory · Computer Science 2023-02-08 Bin Chen , Yi Lei , Gabriele Liga , Zhiwei Liang , Wei Ling , Xuwei Xue , Alex Alvarado
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