Hui Gao

Nanjing University of Posts and Telecommunications

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Tiejun Lv

Beijing University of Posts and Telecommunications

135

Yueming Lu

Beijing University of Posts and Telecommunications

R. Schuch

Stockholm University

Ruohan Cao

Beijing University of Posts and Telecommunications

W. Zong

Qingdao University

D. R. DeWitt

Stockholm University

Wenjun Xu

Beijing University of Posts and Telecommunications

Chau Yuen

Nanyang Technological University

Taotao Wang

Shaanxi University of Technology

Shaoshi Yang

Beijing University of Posts and Telecommunications

Cooperative Institutions

Chinese Academy of Sciences

165

Beijing University of Posts and Telecommunications

136

Thomas Jefferson National Accelerator Facility

130

University of Chinese Academy of Sciences

Tsinghua University

Institute of Modern Physics

Argonne National Laboratory

Mississippi State University

Brookhaven National Laboratory

University of Science and Technology of China

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Codebook-Based Beam Tracking for Conformal ArrayEnabled UAV MmWave Networks

arXiv (Cornell University) (2020)

Jinglin Zhang Wenjun Xu Hui Gao Miao Pan Zhu Han

Millimeter wave (mmWave) communications can potentially meet the high data-rate requirements of unmanned aerial vehicle (UAV) networks. However, as the prerequisite of mmWave communications, the narrow directional beam tracking is very challenging because of the three-dimensional (3D) mobility and attitude variation of UAVs. Aiming to address the beam tracking difficulties, we propose to integrate the conformal array (CA) with the surface of each UAV, which enables the full spatial coverage and the agile beam tracking in highly dynamic UAV mmWave networks. More specifically, the key contributions of our work are three-fold. 1) A new mmWave beam tracking framework is established for the CA-enabled UAV mmWave network. 2) A specialized hierarchical codebook is constructed to drive the directional radiating element (DRE)-covered cylindrical conformal array (CCA), which contains both the angular beam pattern and the subarray pattern to fully utilize the potential of the CA. 3) A codebook-based multiuser beam tracking scheme is proposed, where the Gaussian process machine learning enabled UAV position/attitude predication is developed to improve the beam tracking efficiency in conjunction with the tracking-error aware adaptive beamwidth control. Simulation results validate the effectiveness of the proposed codebook-based beam tracking scheme in the CA-enabled UAV mmWave network, and demonstrate the advantages of CA over the conventional planner array in terms of spectrum efficiency and outage probability in the highly dynamic scenarios.

Beamwidth

Tracking (education)

10.48550/arxiv.2005.14064

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Citations (1)

Cooperation spectrum sensing method based on adaptive threshold

Hui-Yang Wang Jim Zhu Hui Gao

Considering every secondary user(SU) has its own credibility of sensed results since its different sensed environment in actual environment, this paper proposes an adaptive threshold-based cooperative spectrum sensing scheme, which adjusts the local false-alarm probability of SUs based on the credibility of each SU, and adjusts thethreshold of each SU adaptively. The simulation results show that, the proposed method has improved system detection probability obviously, comparing with traditional cooperation spectrum sensing methods.

False alarm

10.1109/csae.2012.6272638

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On energy efficiency optimization in downlink MIMO-NOMA

2022 IEEE International Conference on Communications Workshops (ICC Workshops) (2017)

Pan Wu Jie Zeng Xin Su Hui Gao Tiejun Lv

Non-orthogonal multiple access (NOMA) is a promising technique for the fifth generation mobile communication system due to its high spectral efficiency (SE). Previous works focus on user scheduling or/and power allocation to achieve the maximization of sum rate. However, the energy efficiency (EE) has not been well studied for NOMA systems. In this paper, we aim to optimize user scheduling and power allocation to maximize the EE of the downlink multiple-input multiple-output (MIMO) NOMA system. There are two scheduling schemes with low complexity and signaling overhead. In the signal space alignment (SSA) based user scheduling scheme, we use the SSA with reference signal space to schedule the users. In the max-collinearity user scheduling approach, we schedule the users considering maximum collinearity among users. Furthermore, we use the sequential convex approximation (SCA) to transform the original optimal problem into a convex optimization problem, so that an optimal power allocation strategy can be obtained. The results show that our algorithms can achieve higher EE when the transmitting power is relatively low. Besides, the sum rate of the center users is higher using the second scheduling approach.

noma

Spectral Efficiency

Maximization

10.1109/iccw.2017.7962690

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Citations (9)

A Novel Wireless Sensor Network Evolution Model Based on Energy-Efficiency

International Journal of Online and Biomedical Engineering (iJOE) (2017)

Hui Gao Zhixian Yang

The Barabási–Albert (BA) model is a famous complex network model that generates scale-free networks. Wireless sensor networks (WSNs) had been thought to be approximately scale-free through lots of empirical research. Based on the BA model, we propose an evolution model for WSNs. According to actual influence factors such as the remainder energy of each sensor and physical link capability of each sensor, our evolution model constructs WSNs by using a preferential attachment mechanism. Through simulation and analysis, we can prove that our evolution model would make the total energy consumption of the WSNs more efficient and have a superior random node error tolerance.

10.3991/ijoe.v13i03.6855

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Personalized Context-aware Collaborative Online Activity Prediction

Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies (2019)

Yali Fan Zhen Tu Yong Li Xiang Chen Hui Gao

With the rapid development of Internet services and mobile devices, nowadays, users can connect to online services anytime and anywhere. Naturally, user's online activity behavior is coupled with time and location contexts and highly influenced by them. Therefore, personalized context-aware online activity modelling and prediction is very meaningful and necessary but also very challenging, due to the complicated relationship between users, activities, spatial and temporal contexts and data sparsity issues. To tackle the challenges, we introduce offline check-in data as auxiliary data and build a user-location-time-activity 4D-tensor and a location-time-POI 3D-tensor, aiming to model the relationship between different entities and transfer semantic features of time and location contexts among them. Accordingly, in this paper we propose a transfer learning based collaborative tensor factorization method to achieve personalized context-aware online activity prediction. Based on real-world datasets, we compare the performance of our method with several state-of-the-arts and demonstrate that our method can provide more effective prediction results in the high sparsity scenario. With only 30% of observed time and location contexts, our solution can achieve 40% improvement in predicting user's Top5 activity behavior in new time and location scenarios. Our study is the first step forward for transferring knowledge learned from offline check-in behavior to online activity prediction to provide better personalized context-aware recommendation services for mobile users.

Spatial contextual awareness

Context model

10.1145/3369829

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Citations (15)

Reactions of cooled ions with cold electrons in CRYRING

Acta Physica Polonica B (1996)

R. Schuch S. Asp C. Biedermann D. R. DeWitt Hui Gao

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A Hybrid Relative Distance Based Cluster Scheme for Energy Efficiency in Wireless Sensor Networks

Hui Gao Hongkun Li Yu Cheng

Energy efficiency is of great importance for the wireless sensor network (WSN). A popular way to save energy is to construct clusters for data aggregation and forwarding. This paper studies the distributed cluster algorithm to improve the energy consumption efficiency. We observe that the cluster head has to lie within the transmission range of the base station (sink node) and the distance between cluster head and base station is critical for the energy consumption performance, we propose a hybrid relative distance based clustering scheme (HRDCS), which considers the relative distance to the base station and the residual energy level during the cluster head selection stage. Consequently we could better balance the chance of being cluster head for all nodes. Simulation results show that our scheme is able to result in longer network lifetime than the well-known protocol LEACH.

Sink (geography)

10.1109/glocom.2010.5683388

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Citations (8)

Emotion Classification of Infant Voice Based on Features Derived from Teager Energy Operator

Congress on Image and Signal Processing (2008)

Hui Gao Shanguang Chen SU Guang-chuan

To study effective speech features which can represent different emotion styles in infant voice, nonlinear features based on Teager Energy Operator are investigated. Neutral state and 4 emotional states (i.e. happiness, impatience, anger and fear) are classified from the infant voice database. MFCC extraction and HMM-based emotion classification are used as baseline system to evaluate the emotional classification performance of nonlinear features. In comparison with MFCC, relative improvements which are 2%, 2% , 2% and 10% of classification capacity are obtained when using NFD_Mel , AF_Mel, DAF_Mel and TEO_SBCC. But the performance of emotion classification decreases respectively by 14% for using AM_SBCC.

Mel-frequency cepstrum

Energy operator

10.1109/cisp.2008.623

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Citations (3)

Ultra-Wideband Optically Controlled Frequency Selective Surface

IEEE Conference Proceedings (2019)

Hui Gao Qiang Zhang

Wideband

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