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4,371 results on '"Zhang, Xiaoying"'

163. Peak-to-Average Power Ratio Analysis for OFDM-Based Mixed-Numerology Transmissions

Author

Liu, Xiaoran, Zhang, Lei, Xiong, Jun, Zhang, Xiaoying, Zhou, Li, and Wei, Jibo

Subjects
Electrical Engineering and Systems Science - Signal Processing
Abstract

In this paper, the probability distribution of the peak to average power ratio (PAPR) is analyzed for the mixed numerologies transmission based on orthogonal frequency division multiplexing (OFDM). State of the art theoretical analysis implicitly assumes continuous and symmetric frequency spectrum of OFDM signals. Thus, it is difficult to be applied to the mixed-numerology system due to its complication. By comprehensively considering system parameters, including numerology, bandwidth and power level of each subband, we propose a generic analytical distribution function of PAPR for continuous-time signals based on level-crossing theory. The proposed approach can be applied to both conventional single numerology and mixed-numerology systems. In addition, it also ensures the validity for the noncontinuous-OFDM (NC-OFDM). Given the derived distribution expression, we further investigate the effect of power allocation between different numerologies on PAPR. Simulations are presented and show the good match of the proposed theoretical results., Comment: 10 pages, 10 figures, and submitted for possible journal publication

Published
2019

164. PAPR Reduction Using Iterative Clipping/Filtering and ADMM Approaches for OFDM-Based Mixed-Numerology Systems

Author

Liu, Xiaoran, Zhang, Xiaoying, Zhang, Lei, Xiao, Pei, Wei, Jibo, Zhang, Haijun, and Leung, Victor C. M.

Subjects
Electrical Engineering and Systems Science - Signal Processing
Abstract

Mixed-numerology transmission is proposed to support a variety of communication scenarios with diverse requirements. However, as the orthogonal frequency division multiplexing (OFDM) remains as the basic waveform, the peak-to average power ratio (PAPR) problem is still cumbersome. In this paper, based on the iterative clipping and filtering (ICF) and optimization methods, we investigate the PAPR reduction in the mixed-numerology systems. We first illustrate that the direct extension of classical ICF brings about the accumulation of inter-numerology interference (INI) due to the repeated execution. By exploiting the clipping noise rather than the clipped signal, the noise-shaped ICF (NS-ICF) method is then proposed without increasing the INI. Next, we address the in-band distortion minimization problem subject to the PAPR constraint. By reformulation, the resulting model is separable in both the objective function and the constraints, and well suited for the alternating direction method of multipliers (ADMM) approach. The ADMM-based algorithms are then developed to split the original problem into several subproblems which can be easily solved with closed-form solutions. Furthermore, the applications of the proposed PAPR reduction methods combined with filtering and windowing techniques are also shown to be effective., Comment: 14 pages, 13 figures, and submitted for possible journal publication

Published
2019

168. Conversational Contextual Bandit: Algorithm and Application

Author

Zhang, Xiaoying, Xie, Hong, Li, Hang, and Lui, John C. S.

Subjects
Computer Science - Machine Learning, Computer Science - Information Retrieval, Statistics - Machine Learning
Abstract

Contextual bandit algorithms provide principled online learning solutions to balance the exploitation-exploration trade-off in various applications such as recommender systems. However, the learning speed of the traditional contextual bandit algorithms is often slow due to the need for extensive exploration. This poses a critical issue in applications like recommender systems, since users may need to provide feedbacks on a lot of uninterested items. To accelerate the learning speed, we generalize contextual bandit to conversational contextual bandit. Conversational contextual bandit leverages not only behavioral feedbacks on arms (e.g., articles in news recommendation), but also occasional conversational feedbacks on key-terms from the user. Here, a key-term can relate to a subset of arms, for example, a category of articles in news recommendation. We then design the Conversational UCB algorithm (ConUCB) to address two challenges in conversational contextual bandit: (1) which key-terms to select to conduct conversation, (2) how to leverage conversational feedbacks to accelerate the speed of bandit learning. We theoretically prove that ConUCB can achieve a smaller regret upper bound than the traditional contextual bandit algorithm LinUCB, which implies a faster learning speed. Experiments on synthetic data, as well as real datasets from Yelp and Toutiao, demonstrate the efficacy of the ConUCB algorithm., Comment: 11 pages; Accepted by WWW2020

Published
2019

177. Research status and evolution trend of pipeline transportation of hydrogen-blended natural gas based on knowledge graph

Author

WU Qibing, ZHANG Hang, ZHANG Meng, ZHANG Xiaoying, and DONG Shaohua

Subjects
pipeline transportation of hydrogen-blended natural gas, knowledge graph, green hydrogen, safety, Oils, fats, and waxes, TP670-699, Gas industry, TP751-762
Abstract

Pipeline transportation of hydrogen-blended natural gas is an effective means to solve the problems of economical, large-scale, long-distance and cross-regional transportation of hydrogen in the process of its utilization.Herein, the analysis of knowledge graph clustering, co-presenting and highlighting was performed to the references related to pipeline transportation of hydrogen-blended natural gas at home and abroad from 2006 to 2022, so as to sort out the research status and predict the evolution trend in the future. The results show that: great importance is attached by major developed countries in the world to the research on the pipeline transportation of hydrogen-blended natural gas, and the research on pipeline transportation of hydrogen-blended natural gas is relatively mature in foreign countries. The research on pipeline transportation of hydrogen-blended natural gas in China was started relatively late and it is generally in the preliminary stage though some progress has been made. From the perspective of future trends, in China, more attention is paid to the research on hydrogen refueling stations, hydrogen embrittlement, hydrogen energy, and the equipment and environment closely related to pipeline transportation of hydrogen-blended natural gas, while foreign researches mainly focus on the pipeline material, and the systematic and modeled solutions for pipeline transportation of hydrogen-blended natural gas.

Published
2022
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