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1,117 results on '"Li, Youming"'

11. Steady-state joint distribution for first-order stochastic reaction kinetics

Author

Li, Youming, Jiang, Da-Quan, and Jia, Chen

Subjects
Quantitative Biology - Molecular Networks
Abstract

While the analytical solution for the marginal distribution of a stochastic chemical reaction network has been extensively studied, its joint distribution, i.e. the solution of a high-dimensional chemical master equation, has received much less attention. Here we develop a novel method of computing the exact joint distributions of a wide class of first-order stochastic reaction systems in steady-state conditions. The effectiveness of our method is validated by applying it to four gene expression models of biological significance, including models with 2A peptides, nascent mRNA, gene regulation, translational bursting, and alternative splicing., Comment: 33 pages, 6 figures

Published
2021
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19. Detailed balance, local detailed balance, and global potential for stochastic chemical reaction networks

Author

Jia, Chen, Jiang, Da-Quan, and Li, Youming

Subjects
Mathematics - Probability
Abstract

Detailed balance of a chemical reaction network can be defined in several different ways. Here we investigate the relationship among four types of detailed balance conditions: deterministic, stochastic, local, and zero-order local detailed balance. We show that the four types of detailed balance are equivalent when different reactions lead to different species changes and are not equivalent when some different reactions lead to the same species change. Under the condition of local detailed balance, we further show that the system has a global potential defined over the whole space, which plays the central role in the large deviation theory and the Freidlin-Wentzell-type metastability theory of chemical reaction networks. Finally, we provide a new sufficient condition for stochastic detailed balance, which is applied to construct a class of high-dimensional chemical reaction networks that both satisfies stochastic detailed balance and displays multistability., Comment: 33 pages, 3 figures

Published
2019

22. On the Secrecy Unicast Throughput Performance of NOMA Assisted Multicast-Unicast Streaming With Partial Channel Information

Author

Chen, Bo, Shi, Qingjiang, Cai, Yunlong, and Li, Youming

Subjects
Computer Science - Information Theory
Abstract

This paper considers a downlink single-cell non-orthogonal multiple access (NOMA) network with uniformly deployed users, while a mixed multicast and unicast traffic scenario is taken into account. By guaranteeing the quality of service (QoS) of the multicast traffic, the multicast outage and secrecy unicast throughput performance is evaluated. In particular, two types of partial channel state information (CSI), namely the imperfect CSI and CSI based on second order statistics (SOS), are investigated in the analytical framework. For both two cases, the closed-form approximations for the multicast outage probability and secrecy unicast throughput are derived except that the approximation for the secrecy unicast throughput in SOS-based CSI only concerns two users. As to the multicast outage probability, the simulation results demonstrate that the NOMA scheme considered in both two cases achieves superior performance compared to the traditional orthogonal multiple access (OMA) scheme, while for the secrecy unicast throughput, the NOMA scheme shows great advantages over the OMA scheme in good condition (high signal-to-noise ratio (SNR)), but is inferior to the OMA scheme in poor condition (low SNR). Moreover, both two cases achieve similar performance except that the NOMA scheme with imperfect CSI obtains larger secrecy unicast throughput than that based on SOS under high SNR condition. Finally, the provided numerical results also confirm that the derived approximations of both two cases for the multicast outage probability and secrecy unicast throughput match well with the Monte Carlo simulations., Comment: 14 pages, 5 figures

Published
2018

28. Robust RSS-Based Localization in Mixed LOS/NLOS Environments

Author

Sun, Yinghao, Wang, Gang, Li, Youming, Akan, Ozgur, Editorial Board Member, Bellavista, Paolo, Editorial Board Member, Cao, Jiannong, Editorial Board Member, Coulson, Geoffrey, Editorial Board Member, Dressler, Falko, Editorial Board Member, Ferrari, Domenico, Editorial Board Member, Gerla, Mario, Editorial Board Member, Kobayashi, Hisashi, Editorial Board Member, Palazzo, Sergio, Editorial Board Member, Sahni, Sartaj, Editorial Board Member, Shen, Xuemin (Sherman), Editorial Board Member, Stan, Mircea, Editorial Board Member, Jia, Xiaohua, Editorial Board Member, Zomaya, Albert Y., Editorial Board Member, Gao, Honghao, editor, Feng, Zhiyong, editor, Yu, Jun, editor, and Wu, Jun, editor

Published
2020
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31. Joint channel and impulsive noise estimation method based on approximate message passing for NOMA systems.

Author

LI Youming, MA Chongya, WU Yonghong, and GUO Qiang

Abstract

To address the channel estimation problem for non-orthogonal multiple access (NOMA) systems under non-Gaussian impulsive noise, a joint channel and impulsive noise estimation method based on approximate message passing was proposed, by exploiting the joint sparsity of the channel and impulsive noise. Firstly, based on sparse Bayesian learning theory, a compressed sensing equation was constructed by using all subcarriers, and then a joint estimation optimization problem for the channel, impulsive noise, and data symbols was proposed. To address this hyperparameter nonlinear non-convex problem, an expectation maximization (EM) implementation algorithm based on Gaussian generalized approximation message passing and sparse Bayesian learning (SBL) theory was designed. Simulation results show that compared to the SBL method based on EM, the proposed algorithm exhibited a slight degradation in terms of mean square error (MSE) for channel and impulsive noise estimation, bit error rate (BER). However, the complexity of the proposed algorithm was reduced by one order of magnitude. [ABSTRACT FROM AUTHOR]

Published
2024
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42. Impulsive Noise Suppression Based on ℓq-norm and Graph Laplacian Regularization for NOMA System

Author

Cai, Wanyuan, Li, Youming, Zhang, Xiaolong, Jiang, Tao, and Qi, Qinke

Abstract

This letter proposes a method for impulsive noise (IN) suppression in non-orthogonal multiple access (NOMA) downlink system by leveraging the graph signal processing (GSP) and $\ell _{q}$ -norm-based sparse signal recovery theories. Within GSP framework, we propose a graph-based representation to characterize the underlying structure of the sub-carriers. Accordingly, the graph Laplacian regularization (GLR) is defined to capture the similarities between sub-carriers. Then, the IN suppression problem is formulated as a constraint optimization problem, incorporating the $\ell _{q}$ -norm and GLR, which can efficiently characterize the sparsity of IN and the underlying structure of the sub-carriers. Finally, an augment Lagrange multiplier (ALM) framework is introduced to solve the optimization problem. Numerical experiment results illustrate the effectiveness of the proposed method in comparison with existing methods.

Published
2024
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