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..

Optimal feedback scheme and universal time scaling for Hamiltonian parameter estimation.

Abstract: Time is a valuable resource and it is expected that a longer time period should lead to better precision in Hamiltonian parameter estimation. However, recent studies in quantum metrology have shown that in certain cases more time may even lead to worse estimations, which puts this intuition into question. In this Letter we show that by including feedback controls this intuition can be restored. By deriving asymptotically optimal feedback controls we quantify the maximal improvement feedback controls can provide in Hamiltonian parameter estimation and show a universal time scaling for the precision limit under the optimal feedback scheme. Our study reveals an intriguing connection between noncommutativity in the dynamics and the gain of feedback controls in Hamiltonian parameter estimation.

Optical line terminal, passive optical network and radio frequency signal transmission method

Abstract: An optical line terminal, a passive optical network and a radio frequency signal transmission method in the communication technical field are provided. The passive optical network comprises: OLT, ODN and at least one ONU. The OLT comprises: at least one transmitting unit, which provides one dedicated downlink optical carrier and two dedicated uplink optical carriers for ONU, the downlink radio frequency signal which needs to be transmitted to ONU is modulated on the dedicated downlink optical carrier for the ONU, and after combining the modulated downlink optical carrier and the two dedicated uplink optical carriers, the downlink optical signals are outputted; the two dedicated optical carriers for ONU are configured to bear ONU uplink radio frequency signals; a multiplexing/demultiplexing unit which multiplexes through wavelength division the downlink optical signal outputted from each transmitting unit and transmit it to ONU via ODN, and demultiplexes through wavelength division the uplink optical wave of each ONU which has been multiplexed through wavelength division and is transmitted by ODN, and then output them; and at least one receiving unit which obtains the uplink signal from the demultiplexed uplink optical signal. The bandwidth of wireless access network is enhanced, and the design of ONU is simple.

Method and system for maintaining session continuity

Abstract: A method and a system for maintaining session continuity, in which the system includes: a Handover Source Function (HOSF), a Handover Destination Function (HODF), a Handover Anchor Function-Control Plane (HOAF-CP) and a Handover Anchor Function-User Plane (HOAF-UP). The method includes: a first user establishing a connection through the HOSF with the HOAF-CP and the HOAF-UP which correspond to a second user, so as to establishing a session with the second user; during session handover, the HODF that corresponds to the HOSF establishing another connection with the HOAF-CP and HOAF-UP though which the first user continues the session with the second user, so as to maintain the session continuity. When the access address or the access means of the terminal changes, or even the terminal changes during a session, embodiments of the present invention can logically replace the connection before the handover with a new connection to ensure the session continuity.

AET vs. AED: Unsupervised Representation Learning by Auto-Encoding Transformations rather than Data

Abstract: The success of deep neural networks often relies on a large amount of labeled examples, which can be difficult to obtain in many real scenarios. To address this challenge, unsupervised methods are strongly preferred for training neural networks without using any labeled data. In this paper, we present a novel paradigm of unsupervised representation learning by Auto-Encoding Transformation (AET) in contrast to the conventional Auto-Encoding Data (AED) approach. Given a randomly sampled transformation, AET seeks to predict it merely from the encoded features as accurately as possible at the output end. The idea is the following: as long as the unsupervised features successfully encode the essential information about the visual structures of original and transformed images, the transformation can be well predicted. We will show that this AET paradigm allows us to instantiate a large variety of transformations, from parameterized, to non-parameterized and GAN-induced ones. Our experiments show that AET greatly improves over existing unsupervised approaches, setting new state-of-the-art performances being greatly closer to the upper bounds by their fully supervised counterparts on CIFAR-10, ImageNet and Places datasets.

Mutual Coupling Reduction Using Meta-Structures for Wideband, Dual-Polarized, and High-Density Patch Arrays

Abstract: A mutual coupling reduction strategy that employs meta-structures is introduced for wideband, dual-polarized, high-density, planar, and patch antenna arrays The meta-structures consist of two types of resonators: grounded capacitively loaded loops (GCLLs) and $\pi$ -shaped elements By incorporating the meta-structures into the array configuration, the isolation levels between adjacent radiating elements in both the E- and H-planes orientations are improved by as much as 715 dB The surface current distribution behaviors of the array with only the GCLLs and with only the $\pi$ -shaped elements are investigated thoroughly to explain the mutual coupling reduction mechanisms A proof-of-concept array was constructed and tests were performed that validate the reported design principles and simulation results