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.

Anomalous Hall effect in a ferromagnetic Fe 3 Sn 2 single crystal with a geometrically frustrated Fe bilayer kagome lattice

Abstract: The anomalous Hall effect (AHE) is investigated for a ferromagnetic ${\mathrm{Fe}}_{3}{\mathrm{Sn}}_{2}$ single crystal with a geometrically frustrated kagome bilayer of Fe. The scaling behavior between anomalous Hall resistivity ${\ensuremath{\rho}}_{xy}^{A}$ and longitudinal resistivity ${\ensuremath{\rho}}_{xx}$ is quadratic and further analysis implies that the AHE in the ${\mathrm{Fe}}_{3}{\mathrm{Sn}}_{2}$ single crystal should be dominated by the intrinsic Karplus-Luttinger mechanism rather than extrinsic skew-scattering or side-jump mechanisms. Moreover, there is a sudden jump of anomalous Hall conductivity ${\ensuremath{\sigma}}_{xy}^{A}$ appearing at about 100 K where the spin-reorientation transition from the $c$ axis to the $ab$ plane is completed. This change of ${\ensuremath{\sigma}}_{xy}^{A}$ might be related to the evolution of the Fermi surface induced by the spin-reorientation transition.

Learning-Based Energy-Efficient Data Collection by Unmanned Vehicles in Smart Cities

Abstract: Mobile crowdsourcing (MCS) is now an important source of information for smart cities, especially with the help of unmanned aerial vehicles (UAVs) and driverless cars. They are equipped with different kinds of high-precision sensors, and can be scheduled/controlled completely during data collection, which will make MCS system more robust. However, they are limited to energy constraint, especially for long-term, long-distance sensing tasks, and cities are almost too crowded to set stationary charging station. Towards this end, in this paper we propose to leverage emerging deep reinforcement learning (DRL) techniques for enabling model-free unmanned vehicles control, and present a novel and highly effective control framework, called “DRL-RVC.” It utilizes the powerful convolutional neural network for feature extraction of the necessary information (including sample distribution, traffic flow, etc.), then makes decisions under the guidance of the deep Q network. That is, UAVs will cruise in the city without control and collect most required data in the sensing region, while mobile unmanned charging station will reach the charging point in the shortest possible time. Finally, we validate and evaluate the proposed framework via extensive simulations based on a real dataset in Rome. Extensive simulation results well justify the effectiveness and robustness of our approach.

Practical quantum private query with better performance in resisting joint-measurement attack

Abstract: As a kind of practical protocol, quantum-key-distribution (QKD)-based quantum private queries (QPQs) have drawn lots of attention. However, joint-measurement (JM) attack poses a noticeable threat to the database security in such protocols. That is, by JM attack a malicious user can illegally elicit many more items from the database than the average amount an honest one can obtain. Taking Jacobi et al.'s protocol as an example, by JM attack a malicious user can obtain as many as 500 bits, instead of the expected 2.44 bits, from a ${10}^{4}$-bit database in one query. It is a noticeable security flaw in theory, and would also arise in application with the development of quantum memories. To solve this problem, we propose a QPQ protocol based on a two-way QKD scheme, which behaves much better in resisting JM attack. Concretely, the user Alice cannot get more database items by conducting JM attack on the qubits because she has to send them back to Bob (the database holder) before knowing which of them should be jointly measured. Furthermore, JM attack by both Alice and Bob would be detected with certain probability, which is quite different from previous protocols. Moreover, our protocol retains the good characters of QKD-based QPQs, e.g., it is loss tolerant and robust against quantum memory attack.

Computation Offloading With Data Caching Enhancement for Mobile Edge Computing

Abstract: Computation offloading is a proven successful paradigm for enabling resource-intensive applications on mobile devices. Moreover, in view of emerging mobile collaborative application, the offloaded tasks can be duplicated when multiple users are in the same proximity. This motivates us to design a collaborative offloading scheme and cache the popular computation results that are likely to be reused by other mobile users. In this paper, we consider the scenario where multiple mobile users offload duplicated computation tasks to the network edge, and share the computation results among them. Our goal is to develop the optimal fine-grained collaborative offloading strategies with caching enhancements to minimize the overall execution delay at the mobile terminal side. To this end, we propose an optimal offloading with caching-enhancement scheme (OOCS) for femto-cloud scenario and mobile edge computing scenario, respectively. Simulation results show that compared to six alternative solutions in literature, our single-user OOCS can reduce execution delay up to $42.83$ % and $33.28$ % for single-user femto-cloud and single-user mobile edge computing, respectively. Our multi-user OOCS can further reduce $11.71$ % delay compared to single-user OOCS through users’ cooperation.