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检索条件"机构=Laboratory of Networks System Architecture and Convergence"

共 340 条记录，以下是291-300 订阅

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Orthogonal Polarizations Based Channel Estimation for Dual-polarized Massive MIMO Under Pilot Contamination

Orthogonal Polarizations Based Channel Estimation for Dual-p...

引用

IEEE International Conference on Communications in China Workshops (ICCC)

作者： Li Han Fangfang Liu Chunyan Feng Shulun Zhao Beijing Laboratory of Advanced Information Networks Beijing Key Laboratory of Network System Architecture and Convergence Beijing University of Posts and Telecommunications Beijing China

ISBN: (纸本)9781538670125;9781538670118

Pilot contamination limits the accuracy of channel state information (CSI). In this paper, we propose an orthogonal polarizations based channel estimation algorithm in multi-cell multi-user dual-polarized massive multiple-input multiple-output (MIMO) system. The algorithm exploits orthogonal polarizations effectively reduce the mean square error (MSE) under pilot contamination. Meanwhile, for the high complexity of the minimum mean square error (MMSE) channel estimation, the algorithm uses unbiased estimation for the combination term of interference caused by pilot contamination and the noise. Then we deduce and evaluate the approximate MSE analytical expression of the proposed channel estimation. Finally, the simulation results show that the proposed algorithm is simpler than the MMSE estimation, and more practical than least squares (LS) channel estimation.

关键词： Channel estimation Contamination Antennas Estimation MIMO communication Covariance matrices Partial transmit sequences

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Fast Software-based Table-less Algorithm for CRC Generation

Fast Software-based Table-less Algorithm for CRC Generation

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International Symposium on Wireless Personal Multimedia Communications (WPMC)

作者： Mucong Chi Dazhong He Jun Liu Beijing Laboratory of Advanced Information Networks and Beijing Key Laboratory of Network System Architecture and Convergence Beijing University of Posts and Telecommunications Beijing China

ISBN: (纸本)9781538657584;9781538657577

This paper proposes a software-based CRC algorithm, which can be applied to CRCs with check values of different lengths. The proposed algorithm can be implemented by shift and XOR operations, and no look-up tables are needed. Therefore, it is suitable for processors with limited memory resources. Compared with table-based CRC algorithms, the proposed algorithm takes more instructions; however, the memory accesses are reduced significantly. As a result, for CRCs with specific generator polynomials, the implementation of the proposed algorithm achieves a high throughput. In the best cases, the proposed algorithm is 29% faster than the Sarwate algorithm for 16-bit CRC generation, and 45% faster than the Slicing-by-4 algorithm for 32-bit CRC generation. Furthermore, for 64-bit CRC generation, the proposed algorithm quadruples the throughput of the Slicing-by-4 algorithm at best.

关键词： Generators Throughput Wireless communication Program processors Software algorithms Multimedia communication Table lookup

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SOCIAL-GUIDED REPRESENTATION LEARNING FOR IMAGES VIA DEEP HETEROGENEOUS HYPERGRAPH EMBEDDING

SOCIAL-GUIDED REPRESENTATION LEARNING FOR IMAGES VIA DEEP HE...

引用

IEEE International Conference on Multimedia and Expo

作者： Yunfei Chu Chunyan Feng Caili Guo Beijing Laboratory of Advanced Information Networks Beijing China Beijing Key Laboratory of Network System Architecture and Convergence Beijing University of Posts and Telecommunications China

Representation learning for images is widely recognized as critical to the performance of end tasks such as image classification and cross-modal retrieval. However, most existing methods extract features only from visual content, far from adequate in interpreting semantics latent in images. For social images, there also exists rich social context information, e.g. owners, tags and groups, which provides cues for interpreting semantics. In this paper, we propose a representation learning framework via deep heterogeneous hypergraph embedding (DHHE), considering both visual content and social contexts. In particular, images and their contexts are first represented as a heterogeneous hypergraph, which is then embedded into a low-dimensional space. To incorporate visual information and generalize for unseen images, we learn the mapping from visual content to the semantic space. We conduct experiments with the tasks of classification, cross-modal retrieval and recommendation, which demonstrates the effectiveness of our approach and the merits of social guidance.

关键词： Representation learning Deep learning Hypergraph embedding Social media

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Polarization Modulation based Phase Noise Cancellation for Massive MIMO-OFDM systems

Polarization Modulation based Phase Noise Cancellation for M...

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International Symposium on Personal, Indoor, and Mobile Radio Communications

作者： Yao Nie Chunyan Feng Fangfang Liu Caili Guo Huan Wu Beijing Key Laboratory of Network System Architecture and Convergence Beijing Laboratory of Advanced Information Networks Beijing University of Posts and Telecommunications Beijing China 100876

ISBN: (纸本)9781538660102

In massive multiple-input multiple-output (MIMO) uplink systems, phase noise introduced by oscillators can cause severe performance loss. It leads to common phase error and inter-carrier interference in massive MIMO-OFDM uplink. To solve the issue, a novel phase noise cancellation scheme based on polarization modulation is proposed. We first introduce the polarization modulation (PM) exploited in massive MIMO-OFDM uplink. Then, by exploiting zero-forcing detection, we analyze ICI and the distribution of the transformed noise. Furthermore, we demonstrate that phase noise can be asymptotically cancelled and only the transformed additive white Gaussian noise exists as the number of antennas at the base station is very lager. Moreover, we derive the instantaneous signal-to-noise ratio (SNR) on each subcarrier and analyze the ergodic capacity. The simulation results show that the proposed scheme can effectively mitigate phase noise and achieve a higher ergodic capacity.

关键词： MIMO MIMO-OFDM SNR

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Adaptive resource allocation scheme for wireless cellular networks 2

Adaptive resource allocation scheme for wireless cellular ne...

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2nd IEEE International Conference on Energy Internet, ICEI 2018

作者： Wang, Yue Miao, Jiansong Liang, Xinyu Wang, Jianmin Yue Wang Beijing Key Laboratory of Network System Architecture and Convergence Beijing University of Posts and Telecommunications Beijing China Beijing Laboratory of Advanced Information Networks Beijing University of Posts and Telecommunications Beijing China Beijing University of Posts and Telecommunications Beijing China 6th Research Institute of China Electronics Corporation Beijing China

ISBN: (纸本)9781538641316

As spectrum scarcity and inter cell interference (ICI) are both limiting factors in wireless cellular system, ICI coordination (ICIC) techniques play an important role in improving system performance. Soft Frequency Reuse (SFR) is an effective way to manage the spectrum and reduce ICI in cellular system. It carries out resource allocation prior to system deployment, and dynamic schemes allocate resource regardless of the actual network traffic and interference distribution, both of which limit the potential system performance. Energy Internet's deployment is becoming more and more intensive. It is important to increase system throughput and reduce data error rate. In this paper, an adaptive resource allocation scheme (ARAS) is proposed which first dynamically optimizes resource allocation according to interference distribution and traffic load. In ARAS, the interference thresholds and the roles of victim and aggressor require to be specific. For each victim user, their dominant interferer (DI) applies the Different Evolution (DE) to find the optimal transmission power reduction, aiming at improving victim users' performance and guaranteeing data requirement. To improve system performance, extra resources are allocated to balance ICIC and system capacity. Simulation results show that the ARAS achieves better SINR and throughput compared with existing ICIC schemes. © 2018 IEEE.

关键词： Resource allocation

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Low-Rank and Joint-Sparse Signal Recovery for Spatially and Temporally Correlated Data Using Sparse Bayesian Learning

Low-Rank and Joint-Sparse Signal Recovery for Spatially and ...

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IEEE International Conference on Acoustics, Speech and Signal Processing

作者： Yanbin Zhang Yangqing Li Changchuan Yin Kesen He Beijing Laboratory of Advanced Information Networks Beijing Key Laboratory of Network System Architecture and Convergence Beijing University of Posts and Telecommunications Beijing 100876 P. R. China

ISBN: (纸本)9781538646595

In order to meet the demands of data-intensive continuous monitoring in wireless body area network, we address a structured sparse signal recovery method to exploit both spatial and temporal correlations in data using compressive sensing (CS). Using a simultaneously low-rank and joint-sparse (L&S) signal model, we employ a Bayesian learning treatment by incorporating an L&S-inducing prior over the data and the appropriate hyperpriors over all hyperparameters, resulting in effective reconstruction of the L&S data. Simulation results suggest that the proposed L&S-bSBL is superior to the state-of-the-art recovery methods in terms of computation burden and runtime cost.

关键词： Wireless Body Area Network Bayesian Learning Compressive Sensing Low-rank and Joint-sparse Bayesian learning Compressed sensing body area networks signals

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Impedance Measurement of RFID Tag Antenna Based on Different Methods 5

Impedance Measurement of RFID Tag Antenna Based on Different...

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The 5th International Symposium on Electromagnetic Compatibility

作者： Chenwei Cai Weijun Hong Li Deng Shufang Li Beijing Laboratory of Advanced Information Networks Beijing University of Posts and Telecommunications Beijing Key Laboratory of Network System Architecture and Convergence Beijing University of Posts and Telecommunications

ISBN: (纸本)9781509051861;9781509051854

RFTD tag antennas use balanced feeding structure,which causes great challenge on antenna impedance measurement Methods for balanced antenna impedance measurement can be divided into three categories:Balun method,imaging theory and S-parameter *** types methods are analyzed and compared in this *** and experiments are implemented to support the *** the comparisons,great agreements in impedance value and variation tendency are observed between the simulation and experiment Moreover,strengths and weaknesses of the three methods also are analyzed in this paper.

关键词： impedance measurement Balun imaging theory SParameter

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Modelling and Forecasting of Commodity Trading Price

Modelling and Forecasting of Commodity Trading Price

引用

2018 2nd International Conference on Data Mining,Communications and Information Technology (DMCIT 2018)

作者： Jun Liu Yuan Tian Qing Yan Center for Data Science BUPT School of Information and Communication Engineering BUPT Beijing Laboratory of Advanced Information Networks BUPT Beijing Key Laboratory of Network System Architecture and Convergence BUPT

This paper proposes and improves a model for China's cotton reserves trading market,generates a more accurate price level table in contrast to the widely used China Cotton Association(CCA)'s table,and predicts the future trading price with this *** used is all 29895 trade records of cotton reserves from May,2016 to Sept,*** this paper,we firstly give a briefly introduction to the data as well as basic knowledge of cotton,especially the CCA's price level table as the target to improve *** then present a multiple linear regression with dummy variable model,which can reduce the error on predicting the trading price of current month,but still remains some problems such as the result shows a batch of cotton with better quality may get a lower *** we finally advance the model with multidimensional isotonic regression and more factors taken into *** last model could be used to predict the trade price of both current month and next month with approximately 4% mean absolute percentage error(MAPE).

关键词： CCA Modelling and Forecasting of Commodity Trading Price

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An Energy-Efficient User Association Scheme Based on Robust Optimization in Ultra-Dense networks

An Energy-Efficient User Association Scheme Based on Robust ...

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IEEE International Conference on Communications in China Workshops (ICCC)

作者： Chenming Ma Fangfang Liu Zhimin Zeng Shulun Zhao Beijing Key Laboratory of Advanced Information Networks Beijing Key Laboratory of Network System Architecture and Convergence School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing China

ISBN: (纸本)9781538670125;9781538670118

In ultra-dense networks, due to the diversity of content requested by users, the traffic demand of each user is actually uncertain. User association schemes based on exact traffic demand seem to be outdated. With economic and operational considerations and environmental issues, energy efficiency has now become a key pillar of communication network design. Therefore, we propose an energy-efficient user association scheme based on robust optimization, which improves the stability of association and the energy efficiency of the system. First, a robust optimization model for user association scheme is designed in ultra-dense network deployments. In this model, we construct an uncertainty set of bandwidth to describe the uncertainty of the user traffic demand. Then we solve the association matrix through an iterative user association algorithm to maximize system energy efficiency. The simulation results show that the proposed user association scheme has better energy efficiency performance than the signal to interference plus noise ratio (SINR)-based user association scheme.

关键词： Base stations Optimization Mathematical model Uncertainty Bandwidth Power demand Ultra-dense networks

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Location-Aware Hypergraph Coloring Based Spectrum Allocation for D2D Communication

Location-Aware Hypergraph Coloring Based Spectrum Allocation...

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International Symposium on Wireless Communication systems (ISWCS)

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

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.

关键词： Device-to-device communication Interference Resource management Cellular networks Receivers Transmitters Channel allocation

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