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2nd IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference, IMCEC 2018

作者： Khan, Irfanullah Zhang, Tiankui Xu, Xiaogeng Shan, Siyang Khan, Adil Ahmad, Shabeer Beijing Laboratory of Advanced Information Networks Beijing Key Laboratory of Network System Architecture and Convergence Beijing University of Posts and Telecommunications School of Information and Communication Engineering Beijing100876 China

ISBN: (纸本)9781538618035

In Content Centric Vehicular network (CCVN), content forwarding priority is a crucial issue in content dissemination scenario considering the content urgency. To guarantee the prompt and reliable delivery of the contents, a Priority-based Content Dissemination (PCD) scheme is designed for CCVN. In the proposed scheme, content provided to vehicles are broadly classified into safety and non-safety. Safety contents always have higher priority than non-safety contents. The priority of the safety and non-safety contents are assigned based on the content expiration time and the request volume respectively. Contents are propagated according to this priority through wireless communication. The workflow of the proposed PCD scheme is illustrated. The simulation results show that the proposed scheme can reduce the transmission delay of all safety contents and the popular non-safety contents. © 2018 IEEE.

关键词： Safety Reliability Broadcasting systems architecture Data models Vehicular ad hoc networks History

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Inductive Embedding Learning on Attributed Heterogeneous networks via Multi-task Sequence-to-Sequence Learning

Inductive Embedding Learning on Attributed Heterogeneous Net...

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IEEE International Conference on Data Mining (ICDM)

作者： Yunfei Chu Caili Guo Tongze He Yaqing Wang Jenq-Neng Hwang Chunyan Feng Beijing Key Laboratory of Network System Architecture and Convergence Bejing University of Posts and Telecommunications Beijing China Beijing Laboratory of Advanced Information Networks Beijing China Department of Electrical Engineering University of Washington Seatle USA

In the paper, we study the problem of inductive embedding learning on attributed heterogeneous networks, and propose a Multi-task sequence-to-sequence learning based Inductive network Embedding framework (MINE) capturing the attribute similarity, network proximity, and partial label information simultaneously. In particular, MINE trains an encoder function that aggregates information from a node's long-range scope of contexts, with the node attribute sequences generated by the proposed type-guided heterogeneous random walk as inputs. We present an one-to-many multi-task sequence-to-sequence model where the encoder is shared between two related tasks: an unsupervised node identity sequence generation task to learn context-aware embeddings, and a semi-supervised label prediction task to learn semantics-rich embeddings. Extensive experiments on real-world datasets demonstrate that the proposed method significantly outperforms several state-of-the-art methods.

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Inferring land use type in urban area with mobile big data 4

Inferring land use type in urban area with mobile big data

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4th IEEE International Conference on Computer and Communications, ICCC 2018

作者： Xing, Zhizhuang Lin, Wenhui Qiao, Yuanyuan Zhang, Hao Sun, Kewu Yang, Jie Beijing Laboratory of Advanced Information Networks Beijing Key Laboratory of Network System Architecture and Convergence Beijing University of Posts and Telecommunications Beijing China Technology Research Institute Aisino Corporation Beijing China

ISBN: (纸本)9781538683392

Research on the detection of land use has been a challenge for urban sensing and is of great significance to smart city construction. With the popularity of smart phones and the unprecedented growth of mobile phone data, there emerge numerous studies on land use detection with CDR (Call Detail Records), SMS (Short Messaging Service) and mobile traffic data. This is also a combination of urban sensing based on mobile big data and smart city construction. In this paper, we propose a methodology based on existing studies on land use detection with CDR, text data, and mobile traffic data. We propose a new traffic signature that combines the advantages of the above studies and apply it to a real-world dataset collected in northeast of China. We choose the POI (point of interest) data as ground truth data that the obtained land use types are compared with. We find that our method can accurately detect the POI collections of specific types, which proves the effectiveness of our method. After extracting base components of land use types, an NMF (non-negative matrix factorization) based method is applied to explore the mix of land use types in urban areas. Then, we provide reasonable explanations for different areas with mixed land use types. The result of proposed method is evaluated from both components perspective and urban area perspective. © 2018 IEEE.

关键词： Big data

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Polarization-based Cross-tier Interference Alignment in Cognitive Heterogeneous Cellular network 15

Polarization-based Cross-tier Interference Alignment in Cogn...

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15th International Symposium on Wireless Communication systems, ISWCS 2018

作者： Gao, Xiaofang Guo, Caili Chen, Shuo Beijing Laboratory of Advanced Information Networks Beijing University of Posts and Telecommunications Beijing100876 China Beijing Key Laboratory of Network System Architecture and Convergence Beijing University of Posts and Telecommunications Beijing100876 China

ISBN: (纸本)9781538650059

To eliminate the cross-tier interference and optimize the bit-error-rate performance of small cell for downlink underlay cognitive heterogeneous cellular network, a novel polarization-based cross-tier interference alignment scheme is proposed in this paper by exploiting the polarization resource of two-tier network. The transmitting and receiving polarization states of small cell are designed by interference alignment-like behaviors of the minimum total mean squared error optimization model under interference power constraint. An analytical and noncooperative closed form solution is provided for the model. Simulation results show the proposed scheme outperforms the existing schemes in bit-error-rate performance of small cell while keeping the maximum sum rate of overall system. And the tradeoff between bit-error-rate performances of macro cell and small cell is also evaluated. © 2018 IEEE.

关键词： Polarization

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Location-Aware Hypergraph Coloring Based Spectrum Allocation for D2D Communication 15

Location-Aware Hypergraph Coloring Based Spectrum Allocation...

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15th International Symposium on Wireless Communication systems, ISWCS 2018

作者： Li, Zheng Guo, Caili Chen, Shuo Beijing Laboratory of Advanced Information Networks Beijing University of Posts and Telecommunications Beijing100876 China Beijing Key Laboratory of Network System Architecture and Convergence Beijing University of Posts and Telecommunications Beijing100876 China

ISBN: (纸本)9781538650059

Device-to-device (D2D) communication underlaying cellular networks has been recognized as a promising technique to improve spectrum efficiency. However, densely deployed D2D pairs could cause severe interference to cellular user equipments (CUEs) without proper spectrum allocation. Since the CUEs are the primary users of the spectrum band, the quality of service(QoS) of CUEs should be guaranteed. Therefore, the location-aware hypergraph coloring (LAHC) based spectrum allocation algorithm is proposed in uplink D2D underlaying cellular networks. For a particular CUE, the entire cell area is divided into location-aware regions. A set of D2D pairs identified by these regions are limited when sharing spectrum with the CUE to protect the CUE from connection interruption. In addition, we study spectrum allocation using hypergraph coloring method to eliminate cumulative interference from multiple D2D pairs. Simulation indicates that the proposed spectrum allocation algorithm can both guarantee that D2D links will not cause service disruption to CUEs and significantly improve the system capacity. © 2018 IEEE.

关键词： Spectrum efficiency

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Improving Simulation of Lognormal Sum Distributions With Hyperspace Replication

Improving Simulation of Lognormal Sum Distributions With Hyp...

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IEEE Global Communications Conference

作者： Norman C. Beaulieu Gan Luan School of Information and Communication Engineering the Beijing Key Laboratory for Network System Architecture and Convergence Beijing University of Posts and Telecommunications Beijing China School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing China

ISBN: (数字)9781728109626

ISBN: (纸本)9781728109633

Simulation is widely used to estimate the distributions of sums of lognormal random variables because the characteristic function of the lognormal random variable is not known and numerical integration of multiple integrals is difficult. The left tail of the lognormal sum distribution is the outage probability for some wireless systems, while the right tail represents cochannel interference, both crucial design issues. Importance sampling is sometimes used but becomes less effective as the number of summands increases. A novel simulation procedure dubbed hyperspace replication is proposed and studied. The method achieves estimator variance reductions greater than 64 times in the left tail for practical values of outage probability, and 2 to 3 times in the right tail compared to traditional Monte Carlo simulation. The method can be used in cascade with importance sampling and reduces the variances of the distribution estimates by the same amounts as it does for Monte Carlo simulation.

关键词： Random variables Monte Carlo methods Power system reliability Probability distribution Probability density function Distribution functions

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Federated learning for task and resource allocation in wireless high altitude balloon networks

arXiv

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arXiv 2020年

作者： Wang, Sihua Chen, Mingzhe Yin, Changchuan Saad, Walid Hong, Choong Seon Cui, Shuguang Vincent Poor, H. Beijing Laboratory of Advanced Information Network Beijing Key Laboratory of Network System Architecture and Convergence Beijing University of Posts and Telecommunications Beijing100876 China Department of Electrical Engineering Princeton University PrincetonNJ08544 United States Wireless@VT Bradley Department of Electrical and Computer Engineering Virginia Tech BlacksburgVA24060 United States Department of Computer Science and Engineering Kyung Hee University Korea Republic of Chinese University of Hong Kong Shenzhen518172 China Department of Electrical Engineering Princeton University PrincetonNJ08544 United States

In this paper, the problem of minimizing energy and time consumption for task computation and transmission is studied in a mobile edge computing (MEC)-enabled balloon network. In the considered network, each user needs to process a computational task in each time instant, where high-altitude balloons (HABs), acting as flying wireless base stations, can use their powerful computational abilities to process the tasks offloaded from their associated users. Since the data size of each user's computational task varies over time, the HABs must dynamically adjust the user association, service sequence, and task partition scheme to meet the users' needs. This problem is posed as an optimization problem whose goal is to minimize the energy and time consumption for task computing and transmission by adjusting the user association, service sequence, and task allocation scheme. To solve this problem, a support vector machine (SVM)-based federated learning (FL) algorithm is proposed to determine the user association proactively. The proposed SVM-based FL method enables each HAB to cooperatively build an SVM model that can determine all user associations without any transmissions of either user historical associations or computational tasks to other HABs. Given the prediction of the optimal user association, the service sequence and task allocation of each user can be optimized so as to minimize the weighted sum of the energy and time consumption. Simulations with real data of city cellular traffic from the OMNILab at Shanghai Jiao Tong University show that the proposed algorithm can reduce the weighted sum of the energy and time consumption of all users by up to 16.1% compared to a conventional centralized method. Copyright © 2020, The Authors. All rights reserved.

关键词： Support vector machines

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Power efficient visible light communication (VLC) with unmanned aerial vehicles (UAVs)

arXiv

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arXiv 2019年

作者： Yang, Yang Chen, Mingzhe Guo, Caili Feng, Chunyan Saad, Walid Beijing Key Laboratory of Network System Architecture and Convergence School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing100876 China Virginia Polytechnic Institute and State University Blacksburg United States

A novel approach that combines visible light communication (VLC) with unmanned aerial vehicles (UAVs) to simultaneously provide flexible communication and illumination is proposed. To minimize the power consumption, the locations of UAVs and the cell associations are optimized under illumination and communication constraints. An efficient sub-optimal solution that divides the original problem into two sub-problems is proposed. The first sub-problem is modeled as a classical smallest enclosing disk problem to obtain the optimal locations of UAVs, given the cell association. Then, assuming fixed UAV locations, the second sub-problem is modeled as a min-size clustering problem to obtain the optimized cell association. In addition, the obtained UAV locations and cell associations are iteratively optimized multiple times to reduce the power consumption. Numerical results show that the proposed approach can reduce the total transmit power consumption by at least 53.8% compared to two baseline algorithms with fixed UAV locations. Copyright © 2019, The Authors. All rights reserved.

关键词： Unmanned aerial vehicles (UAV)

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Analysis of Memory Capacity for Deep Echo State networks

arXiv

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arXiv 2019年

作者： Liu, Xuanlin Chen, Mingzhe Yin, Changchuan Saad, Walid Beijing Key Laboratory of Network System Architecture and Convergence Beijing University of Posts and Telecommunications Beijing China Wireless@VT Bradley Department of Electrical and Computer Engineering Virginia Tech BlacksburgVA United States

—In this paper, the echo state network (ESN) memory capacity, which represents the amount of input data an ESN can store, is analyzed for a new type of deep ESNs. In particular, two deep ESN architectures are studied. First, a parallel deep ESN is proposed in which multiple reservoirs are connected in parallel allowing them to average outputs of multiple ESNs, thus decreasing the prediction error. Then, a series architecture ESN is proposed in which ESN reservoirs are placed in cascade that the output of each ESN is the input of the next ESN in the series. This series ESN architecture can capture more features between the input sequence and the output sequence thus improving the overall prediction accuracy. Fundamental analysis shows that the memory capacity of parallel ESNs is equivalent to that of a traditional shallow ESN, while the memory capacity of series ESNs is smaller than that of a traditional shallow ESN. In terms of normalized root mean square error, simulation results show that the parallel deep ESN achieves 38.5% reduction compared to the traditional shallow ESN while the series deep ESN achieves 16.8% reduction. Copyright © 2019, The Authors. All rights reserved.

关键词： network architecture

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Ultra-broadband Polarization Rotator Design in Terahertz Region

Ultra-broadband Polarization Rotator Design in Terahertz Reg...

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International Conference on Wireless Communications and Signal Processing (WCSP)

作者： Weijun Hong Xinlong Li Jianfeng Zhu Shufang Li Tingxiao Cai Huanhuan Lin Hongjie Liu Yanqing Wei Beijing Key Laboratory of Network System Architecture and Convergence Beijing University of Posts and Telecommunications Beijing China Beijing Laboratory of Advanced Information Network Beijing University of Posts and Telecommunications Beijing China China Electronics Standardization Institute Beijing China Borsche Technologies Limited Company Beijing China Renmin University of China Beijing China

A three layered metamaterial functions as polarization rotator with extremely broad bandwidth and high conversion ratio is proposed and investigated in this paper. The designed structure is composed of two electric dipole resonant polarization selectors on the top and bottom sides and a cross-shaped polarization converter in the middle filled with two dielectric layers of silica as spacers. The proposed structure forms a cascaded Fabry-Perot-like resonance cavity, leading to the enhancement of polarization conversion between two orthogonal linearly polarized waves. The designed structure is optimized to achieve an extremely broad bandwidth, sharp rejection stop-band, and maximum conversion ratio of 99.9% at the resonant frequency.

关键词： Metamaterials Cavity resonators Polarization Bandwidth Substrates Telecommunications Dielectrics

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