Beijing University of Posts and Telecommunications

About: Beijing University of Posts and Telecommunications is a education organization based out in Beijing, Beijing, China. It is known for research contribution in the topics: MIMO & Quality of service. The organization has 39576 authors who have published 41525 publications receiving 403759 citations. The organization is also known as: BUPT.

Enhanced power allocation scheme in ultra-dense small cell network

Abstract: A feasible design of ultra-dense Small cell network involves an effective solution to the interference coordination especially in cell edge. In this paper, we propose a channel state and interference aware power allocation scheme (PAG) as an enhanced solution to improve the system performance, especially for the cell-edge users. Cournot model in Non-cooperative game is employed for power adjustment in Small cell clusters to increase cell-edge users' throughput by considering the power limitation and interference coordination. Additionally, we take iterative Water Filling scheme as a comparison to clarify that the PAG scheme has struck a favorable balance between system efficiency and fairness. Simulation results show that the proposed scheme contributes to the enhancement of edge users' throughput and cells' coverage. Moreover, the scheme is observed to show a stronger adaptability in denser Small cell networks.

Intelligent Cooperative Edge Computing in Internet of Things

Abstract: The fusion of edge computing and artificial intelligence (AI) technology is a key enabler for the smart Internet of Things (IoT). However, these two emerging paradigms face many issues for their integration, such as data storage structure, model generation algorithms, and cloud-edge collaboration mechanisms. Moreover, edge computing is not ready for supporting AI and can be enabled to support AI via some basic network functions related to Quality of Experience (QoE), such as passive computation offloading and content caching. In this article, we present an intelligent cooperative edge (ICE) computing in IoT networks to achieve a complementary integration of AI and edge computing. The AI-related modules of edge computing are redesigned for distributing AI’s core functions from the cloud to the edge. IoT-generated data are differentiated as user-private data preserved locally in IoT devices, edge-private data isolated on the edge and public data uploaded to the cloud. Therefore, a cloud-scale machine learning model can be generated, followed by privacy-preserving transfer learning running on each edge, which also has data updated more frequently that enables the model’s incremental learning. The model distribution is accomplished through lightweight deployment pipelines consisting of cloud compression and edge reconstruction. Conversely, some key issues of edge computing, such as the computation offloading and content caching, achieve a better solution using the localized AI. We perform the prototype-based evaluation, which indicates that the ICE computing architecture enables a benign combination of AI and edge computing.

Lax pair, conservation laws, Darboux transformation and localized waves of a variable-coefficient coupled Hirota system in an inhomogeneous optical fiber

Abstract: Optical fiber communication plays an important role in the modern communication. In this paper, we investigate a variable-coefficient coupled Hirota system which describes the vector optical pulses in an inhomogeneous optical fiber. With respect to the complex wave envelopes, we construct a Lax pair and a Darboux transformation, both different from the existing ones. Infinitely-many conservation laws are derived based on our Lax pair. We obtain the one/two-fold bright-bright soliton solutions, one/two-fold bright-dark soliton solutions and one/two-fold breather solutions via our Darboux transformation. When α ( t ) , β ( t ) and δ ( t ) are the trigonometric functions, we present the bright-bright soliton, bright-dark soliton and breather which are all periodic along the propagation direction, where α ( t ) , β ( t ) and δ ( t ) represent the group velocity dispersion, third-order dispersion and nonlinear terms of the self-phase modulation and cross-phase modulation. Interactions between the two bright-bright soliton, two bright-dark solitons and two breathers are presented. Bound state of the two bright-bright solitons is formed. Widths and velocities of the two bright-bright solitons do not change but their amplitudes change after their interaction via the asymptotic analysis. Periods of the bright-dark solitons decrease when the periods of the trigonometric α ( t ) , β ( t ) and δ ( t ) decrease.

A Mobility Analytical Framework for Big Mobile Data in Densely Populated Area

Abstract: Due to the pervasiveness of mobile devices, a vast amount of geolocated data is generated, which allows us to gain deep insight into human behavior. Among other data sources, the analysis of data traffic from mobile Internet enables the study of mobile subscribers' movements over long time periods at large scales, which is paramount to research over a wide range of disciplines, e.g., sociology, transportation, epidemiology, networking, etc. However, to efficiently analyze the massive data traffic from the view of user mobility, several technical challenges have to be tackled before releasing the full potential of such data sources, including data collection, trajectory construction, data noise removing, data storage, and methods for analyzing user mobility. This paper introduces a mobility analytical framework for big mobile data, based on real data traffic collected from second-, third- and fourth-generation networks, which covered nearly 7 million people. To construct a user's history trajectories, we apply different rules to extract users' locations from different data sources and reduce oscillations between the cell towers. The comparison of mobility characteristics between our mobile data and other existing data sources shows the large potential of mobile Internet data traffic to study human mobility. In addition, our experiments discover the changing of city hotspots, the movement patterns during peak hours, and people with similar history trajectories, which uncover the common rules that exist among huge populations in a city.

3-D Indoor Positioning for Millimeter-Wave Massive MIMO Systems

Abstract: In this paper, a novel three-dimensional (3-D) indoor positioning scheme is proposed for millimeter-wave (mmWave) massive multiple-input multiple-output (MIMO) systems. Its operation is based upon a hybrid received signal strength and angle of arrival (RSS-AoA) positioning scheme, which employs only a single access point equipped with a large-scale uniform cylindrical array. To reduce the high computational complexity imposed by the large number of antennas used in mmWave massive MIMO (M3-MIMO) systems, we firstly propose a novel channel compression method. By proper quantization and selection of the received mmWave signals, which exhibit quasioptical and sparse multipath characteristics, the channel compression method reduces the dimension of the received signal space while maintaining the accuracy of the position estimation. Then, we propose a beamspace transformation approach to transform signal vectors in the element space to the beamspace, and thus the computational complexity of the angle estimation is significantly reduced. Finally, a novel hybrid RSS-AoA positioning scheme is designed for the computations of the 3-D coordinates of the target mobile terminal. Simulation results have shown that the proposed indoor positioning scheme is capable of achieving high accuracy as well as significantly lower computational complexity as compared to other previously known indoor positioning techniques.