Huawei

About: Huawei is a company organization based out in Shenzhen, China. It is known for research contribution in the topics: Terminal (electronics) & Signal. 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..

Phased-array antenna aiming method and device and phased-array antenna

Abstract: A method and an apparatus for aligning a phased array antenna, and a phased array antenna are provided. A method for aligning a phased array antenna according to an embodiment of the present invention includes: receiving signals from respective antenna array subunits; performing phase shifting on the signals from the respective antenna array subunits, combining phase-shifted signals, where the signals are from the respective antenna array subunits, and obtaining a first signal, where a receiving beam corresponding to the first signal is a rotating receiving beam; rotating, by the rotating receiving beam, around a transmitting/receiving beam according to a preset angular frequency by using the transmitting/receiving beam as a rotation axis; calculating power values of respective first signals in a case that the rotating receiving beam rotates through different angles; and adjusting, according to the power values, a direction of the transmitting/receiving beam to align a phased array antenna.

CL-PRE: a certificateless proxy re-encryption scheme for secure data sharing with public cloud

Abstract: We propose CL-PRE, a certificateless proxy re-encryption scheme for secure data sharing with public cloud, which leverages maximal cloud resources to reduce the computing and communication cost for data owner. Towards running proxy in public cloud environment, we further propose multi-proxy CL-PRE and randomized CL-PRE, which enhance the security and robustness of CL-PRE. We implement all CL-PRE schemes and evaluate their security and performance.

TripPlanner: Personalized Trip Planning Leveraging Heterogeneous Crowdsourced Digital Footprints

Abstract: Planning an itinerary before traveling to a city is one of the most important travel preparation activities. In this paper, we propose a novel framework called TripPlanner , leveraging a combination of location-based social network (i.e., LBSN) and taxi GPS digital footprints to achieve personalized, interactive, and traffic-aware trip planning. First, we construct a dynamic point-of-interest network model by extracting relevant information from crowdsourced LBSN and taxi GPS traces. Then, we propose a two-phase approach for personalized trip planning. In the route search phase , TripPlanner works interactively with users to generate candidate routes with specified venues . In the route augmentation phase , TripPlanner applies heuristic algorithms to add user's preferred venues iteratively to the candidate routes, with the objective of maximizing the route score while satisfying both the venue visiting time and total travel time constraints. To validate the efficiency and effectiveness of the proposed approach, extensive empirical studies were performed on two real-world data sets from the city of San Francisco, which contain more than 391 900 passenger delivery trips generated by 536 taxis in a month and 110 214 check-ins left by 15 680 Foursquare users in six months.

Hierarchical Long Short-Term Concurrent Memory for Human Interaction Recognition

Abstract: In this work, we aim to address the problem of human interaction recognition in videos by exploring the long-term inter-related dynamics among multiple persons. Recently, Long Short-Term Memory (LSTM) has become a popular choice to model individual dynamic for single-person action recognition due to its ability to capture the temporal motion information in a range. However, most existing LSTM-based methods focus only on capturing the dynamics of human interaction by simply combining all dynamics of individuals or modeling them as a whole. Such methods neglect the inter-related dynamics of how human interactions change over time. To this end, we propose a novel Hierarchical Long Short-Term Concurrent Memory (H-LSTCM) to model the long-term inter-related dynamics among a group of persons for recognizing human interactions. Specifically, we first feed each person's static features into a Single-Person LSTM to model the single-person dynamic. Subsequently, at one time step, the outputs of all Single-Person LSTM units are fed into a novel Concurrent LSTM (Co-LSTM) unit, which mainly consists of multiple sub-memory units, a new cell gate, and a new co-memory cell. In the Co-LSTM unit, each sub-memory unit stores individual motion information, while this Co-LSTM unit selectively integrates and stores inter-related motion information between multiple interacting persons from multiple sub-memory units via the cell gate and co-memory cell, respectively. Extensive experiments on several public datasets validate the effectiveness of the proposed H-LSTCM by comparing against baseline and state-of-the-art methods.

A Survey on Handover Management: From LTE to NR

Abstract: To satisfy the high data demands in future cellular networks, an ultra-densification approach is introduced to shrink the coverage of base station (BS) and improve the frequency reuse. The gain in capacity is expected but at the expense of increased interference, frequent handovers (HOs), increased HO failure (HOF) rates, increased HO delays, increase in ping pong rate, high energy consumption, increased overheads due to frequent HO, high packet losses and bad user experience mostly in high-speed user equipment (UE) scenarios. This paper presents the general concepts of radio access mobility in cellular networks with possible challenges and current research focus. In this article, we provide an overview of HO management in long-term evolution (LTE) and 5G new radio (NR) to highlight the main differences in basic HO scenarios. A detailed literature survey on radio access mobility in LTE, heterogeneous networks (HetNets) and NR is provided. In addition, this paper suggests HO management challenges and enhancing techniques with a discussion on the key points that need to be considered in formulating an efficient HO scheme.