Huawei

About: Huawei is a company organization based out in Shenzhen, China. It is known for research contribution in the topics: Terminal (electronics) & Node (networking). The organization has 41417 authors who have published 44698 publications receiving 343496 citations. The organization is also known as: Huawei Technologies & Huawei Technologies Co., Ltd..

Large-scale Interactive Recommendation with Tree-structured Policy Gradient

Abstract: Reinforcement learning (RL) has recently been introduced to interactive recommender systems (IRS) because of its nature of learning from dynamic interactions and planning for long-run performance. As IRS is always with thousands of items to recommend (i.e., thousands of actions), most existing RL-based methods, however, fail to handle such a large discrete action space problem and thus become inefficient. The existing work that tries to deal with the large discrete action space problem by utilizing the deep deterministic policy gradient framework suffers from the inconsistency between the continuous action representation (the output of the actor network) and the real discrete action. To avoid such inconsistency and achieve high efficiency and recommendation effectiveness, in this paper, we propose a Tree-structured Policy Gradient Recommendation (TPGR) framework, where a balanced hierarchical clustering tree is built over the items and picking an item is formulated as seeking a path from the root to a certain leaf of the tree. Extensive experiments on carefully-designed environments based on two real-world datasets demonstrate that our model provides superior recommendation performance and significant efficiency improvement over state-of-the-art methods.

Joint Device Positioning and Clock Synchronization in 5G Ultra-Dense Networks

Abstract: In this article, we address the prospects and key enabling technologies for highly efficient and accurate device positioning and tracking in 5G radio access networks. Building on the premises of ultra-dense networks as well as on the adoption of multicarrier waveforms and antenna arrays in the access nodes (ANs), we first formulate extended Kalman filter (EKF)-based solutions for computationally efficient joint estimation and tracking of the time of arrival (ToA) and direction of arrival (DoA) of the user nodes (UNs) using uplink reference signals. Then, a second EKF stage is proposed in order to fuse the individual DoA/ToA estimates from one or several ANs into a UN position estimate. Since all the processing takes place at the network side, the computing complexity and energy consumption at the UN side are kept to a minimum. The cascaded EKFs proposed in this article also take into account the unavoidable relative clock offsets between UNs and ANs, such that reliable clock synchronization of the access-link is obtained as a valuable by-product. The proposed cascaded EKF scheme is then revised and extended to more general and challenging scenarios where not only the UNs have clock offsets against the network time, but also the ANs themselves are not mutually synchronized in time. Finally, comprehensive performance evaluations of the proposed solutions on a realistic 5G network setup, building on the METIS project based outdoor Madrid map model together with complete ray tracing based propagation modeling, are provided. The obtained results clearly demonstrate that by using the developed methods, sub-meter scale positioning and tracking accuracy of moving devices is indeed technically feasible in future 5G radio access networks operating at sub-6GHz frequencies, despite the realistic assumptions related to clock offsets and potentially even under unsynchronized network elements.

Software-defined control of the virtualized mobile packet core

Abstract: Mobile packet core networks are undergoing major changes to meet the requirements of the future data tsunami, enhance network flexibility, and reduce both CAPEX and OPEX. In this regard, SDN and NFV technologies have gained great momentum among the teleos, with the promise of interoperability, programmability, and on-demand dynamic provisioning. In this article, we present work being developed in the Mobile Packet Core project within the ONF Wireless & Mobile Working Group regarding SDN architecture for the Mobile Packet Core. In addition, we propose an SDN-based MPC in the NFV context in order to facilitate dynamic provisioning of MPC network functions. Finally, a potential control architecture considering both SDN and NFV is proposed.

Method and apparatus for providing presence information

Abstract: The present invention discloses a method for providing presence information, a watcher, a presence server, a presence system and a presentity. It enables the provisioning of history and future presence information, while the prior arts can provide only presence information corresponding to the current time. The method provided by the present invention includes: setting time elements of presence information; recording relevant time information of presence information in the time elements; providing the watcher with presence information together with relevant time information.

Efficient Spatio-Temporal Recurrent Neural Network for Video Deblurring

Abstract: Real-time video deblurring still remains a challenging task due to the complexity of spatially and temporally varying blur itself and the requirement of low computational cost. To improve the network efficiency, we adopt residual dense blocks into RNN cells, so as to efficiently extract the spatial features of the current frame. Furthermore, a global spatio-temporal attention module is proposed to fuse the effective hierarchical features from past and future frames to help better deblur the current frame. For evaluation, we also collect a novel dataset with paired blurry/sharp video clips by using a co-axis beam splitter system. Through experiments on synthetic and realistic datasets, we show that our proposed method can achieve better deblurring performance both quantitatively and qualitatively with less computational cost against state-of-the-art video deblurring methods.