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.

Millimeter-Wave NOMA Transmission in Cellular M2M Communications for Internet of Things

Abstract: Massive connectivity and low latency are two important challenges for the Internet of Things (IoT) to achieve the quality of service provisions required by the numerous devices it is designed to service. Motivated by these challenges, in this paper we introduce a new millimeter-wave nonorthogonal multiple access (mmWave-NOMA) transmission scheme designed for cellular machine-to-machine (M2M) communication systems for IoT applications. It consists of one base station (BS) and numerous multiple machine type communication (MTC) devices operating in a cellular communication environment. We consider its down-link performance and assume that multiple MTC devices share the same communication resources offered by the proposed mmWave-NOMA transmission scheme, which can support massive connectivity. For this system, a novel MTC pairing scheme is introduced the design of which is based upon the distance between the BS and the MTC devices aiming at reducing the system overall overhead for massive connectivity and latency. In particular, we consider three different MTC device pairing schemes, namely: 1) random near and the random far MTC devices; 2) nearest near and the nearest far MTC devices (NNNF); and 3) nearest near and the farthest far MTC device. For all three pairing schemes, their performance is analyzed by deriving closed-form expressions of the outage probability and the sum rate. Furthermore, performance comparison studies of the three MTC device pairing schemes have been carried out. The validity of the analytical approach has been verified by means of extensive computer simulations. The obtained performance evaluation results have demonstrated that the proposed cellular M2M communication system employing the mmWave-NOMA transmission scheme improves outage probability as compared to equivalent systems using mmWave with orthogonal multiple access schemes.

Generation and control of multiple solitons under the influence of parameters

Abstract: In this paper, the analytic three-soliton solution for a high-order nonlinear Schrodinger equation is obtained by the Hirota’s bilinear method. The transmission characteristics of three solitons are discussed. By selecting relevant parameters, soliton interactions are presented, and the method of generating new solitons is suggested. The influences of corresponding parameters on soliton transmission and interactions are analyzed. Results of this paper are helpful for enriching the soliton theory and studying the signal routing system.

Deep Attentive Tracking via Reciprocative Learning

Abstract: Visual attention, derived from cognitive neuroscience, facilitates human perception on the most pertinent subset of the sensory data. Recently, significant efforts have been made to exploit attention schemes to advance computer vision systems. For visual tracking, it is often challenging to track target objects undergoing large appearance changes. Attention maps facilitate visual tracking by selectively paying attention to temporal robust features. Existing tracking-by-detection approaches mainly use additional attention modules to generate feature weights as the classifiers are not equipped with such mechanisms. In this paper, we propose a reciprocative learning algorithm to exploit visual attention for training deep classifiers. The proposed algorithm consists of feed-forward and backward operations to generate attention maps, which serve as regularization terms coupled with the original classification loss function for training. The deep classifier learns to attend to the regions of target objects robust to appearance changes. Extensive experiments on large-scale benchmark datasets show that the proposed attentive tracking method performs favorably against the state-of-the-art approaches.

Cloud model for service selection

Abstract: Cloud computing is Internet-based computing where computing resources are offered over the Internet as scalable, on-demand services. Web services are widely employed for building distributed cloud applications. Performance of web services may fluctuate due to the dynamic Internet environment, which makes the Quality-of-Service (QoS) inherently uncertain. With the increase of Web services in the Internet, selecting the optimal service from a set of functionally equivalent candidates becomes an important research problem. In this paper, we propose an efficient and effective QoS-aware service selection approach. Our approach first employs cloud model to compute the QoS uncertainty for pruning redundant services while extracting reliable services. Then, mixed integer programming is used to select optimal services. The experimental results show that our approach can provide reliable and efficient optimal service selection for users.

Mobile cloud computing as future for mobile applications - Implementation methods and challenging issues

Abstract: In recent years cloud computing has gained a momentum and is transforming the internet computing infrastructure. Also the mobile applications and mobile devices are developing rapidly. Cloud computing is anticipated to bring an innovation in mobile computing, where the mobile devices can use clouds for data processing, storage and other intensive operations. Already there are some mobile cloud applications for example Google's Map, Gmail for iPhone and Cisco's WebEx on iPad, however these applications are using the Software as a Service model. In this paper we introduce state-of-the-art Mobile Cloud Computing and its implementation methods. We also investigate some critical issues to be solved and point-out further future research directions.