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Deep neural networks (NNs) have exhibited considerable potential for efficiently balancing the performance and complexity of multiple-input and multiple-output (MIMO) detectors. We propose a receiver framework that enables efficient online…

Signal Processing · Electrical Eng. & Systems 2020-12-09 Jing Zhang , Yunfeng He , Yu-Wen Li , Chao-Kai Wen , Shi Jin

In time-varying fading channels, channel coefficients are estimated using pilot symbols that are transmitted every coherence interval. For channels with high Doppler spread, the rapid channel variations over time will require considerable…

Information Theory · Computer Science 2022-03-24 Sandesh Rao Mattu , Lakshmi Narasimhan T , A. Chockalingam

We propose a framework for the derivation and evaluation of distributed iterative algorithms for receiver cooperation in interference-limited wireless systems. Our approach views the processing within and collaboration between receivers as…

Information Theory · Computer Science 2012-04-18 Mihai-Alin Badiu , Carles Navarro Manchón , Vasile Bota , Bernard Henri Fleury

The rapid development of the mobile communications requires ever higher spectral efficiency. The non-orthogonal multiple access (NOMA) has emerged as a promising technology to further increase the access efficiency of wireless networks.…

Information Theory · Computer Science 2017-10-25 Weijie Yuan , Nan Wu , Qinghua Guo , Yonghui Li , Chengwen Xing , Jingming Kuang

We revisit the analysis of equalization-enhanced phase noise (EEPN) arising in coherent receivers from the interaction between the chromatic dispersion compensation by an electronic equalizer and the phase noise of the local oscillator.…

Signal Processing · Electrical Eng. & Systems 2019-10-23 Aymeric Arnould , Amirhossein Ghazisaeidi

Seeking the external equitable partitions (EEPs) of networks under unknown structures is an emerging problem in network analysis. The special structure of EEPs has found widespread applications in many fields such as cluster synchronization…

Optimization and Control · Mathematics 2025-11-25 Wenshun Teng , Qingna Li

Expectation propagation is a general approach to fast approximate inference for graphical models. The existing literature treats models separately when it comes to deriving and coding expectation propagation inference algorithms. This comes…

Methodology · Statistics 2018-01-17 Wilson Y. Chen , Matt P. Wand

Bayesian inference is a popular method to build learning algorithms but it is hampered by the fact that its key object, the posterior probability distribution, is often uncomputable. Expectation Propagation (EP) (Minka (2001)) is a popular…

Machine Learning · Statistics 2016-12-16 Guillaume P. Dehaene

Exact inference in the linear regression model with spike and slab priors is often intractable. Expectation propagation (EP) can be used for approximate inference. However, the regular sequential form of EP (R-EP) may fail to converge in…

Machine Learning · Statistics 2011-12-13 José Miguel Hernández-Lobato , Daniel Hernández-Lobato

Generalized Vector Approximate Message Passing (GVAMP) is an efficient iterative algorithm for approximately minimum-mean-squared-error estimation of a random vector $\mathbf{x}\sim p_{\mathbf{x}}(\mathbf{x})$ from generalized linear…

Information Theory · Computer Science 2018-06-27 Christopher A. Metzler , Philip Schniter , Richard G. Baraniuk

This letter deals with the application of the expectation propagation (EP) algorithm to turbo equalization. The EP has been successfully applied to obtain either a better approximation at the output of the equalizer or at the output of the…

Signal Processing · Electrical Eng. & Systems 2020-02-19 Irene Santos , Juan José Murillo-Fuentes , Eva Arias-de-Reyna

We propose a novel approach for nonlinear regression using a two-layer neural network (NN) model structure with sparsity-favoring hierarchical priors on the network weights. We present an expectation propagation (EP) approach for…

Machine Learning · Statistics 2015-01-23 Pasi Jylänki , Aapo Nummenmaa , Aki Vehtari

We investigate the problem of approximate Bayesian inference for a general class of observation models by means of the expectation propagation (EP) framework for large systems under some statistical assumptions. Our approach tries to…

Information Theory · Computer Science 2016-08-24 Burak Çakmak , Manfred Opper , Bernard H. Fleury , Ole Winther

This paper addresses the issue of phase noise in OFDM systems. Phase noise (PHN) is a transceiver impairment resulting from the non-idealities of the local oscillator. We present a case for designing a turbo receiver for systems corrupted…

Information Theory · Computer Science 2010-01-14 Gokul Sridharan , Teng Joon Lim

In a typical multi-standard military communication receiver, fast and reliable spectrum sensing unit is required to extract the information of multiple channels (frequency bands) present in a wideband input signal. In this paper, an energy…

Information Theory · Computer Science 2016-08-16 S. J. Darak , A. P. Vinod , E. M-K. Lai

Exceptional points (EP) are non-Hermitian spectral degeneracies where both eigenvalues and their corresponding eigenvectors coalesce. Recently, EPs have attracted a lot of attention as a means to enhance the responsivity of sensors, via the…

Applied Physics · Physics 2022-02-22 Rodion Kononchuk , Jizhe Cai , Fred Ellis , Ramathasan Thevamaran , Tsampikos Kottos

This paper serves as a correction to the conference version. In this work, we explore uplink communication in cell-free (CF) massive multiple-input multiple-output (MaMIMO) systems, employing semi-blind transmission structures to mitigate…

Information Theory · Computer Science 2024-10-03 Zilu Zhao , Dirk Slock

We propose a novel receiver for orthogonal frequency division multiplexing (OFDM) transmissions in impulsive noise environments. Impulsive noise arises in many modern wireless and wireline communication systems, such as Wi-Fi and powerline…

Information Theory · Computer Science 2015-06-16 Marcel Nassar , Philip Schniter , Brian L. Evans

Continuous phase modulation (CPM) has extensive applications in wireless communications due to its high spectral and power efficiency. However, its nonlinear characteristics pose significant challenges for detection in frequency selective…

Information Theory · Computer Science 2024-08-15 Zilong Liu , Yi Song , Qinghua Guo , Peng Sun , Kexian Gong , Zhongyong Wang

Current quantum computers suffer from non-stationary noise channels with high error rates, which undermines their reliability and reproducibility. We propose a Bayesian inference-based adaptive algorithm that can learn and mitigate quantum…

Quantum Physics · Physics 2023-08-30 Samudra Dasgupta , Arshag Danageozian , Travis S. Humble