Institution
Huawei
Company•Shenzhen, China•
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..
Papers published on a yearly basis
Papers
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29 Oct 2007TL;DR: In this paper, a method, a system and an authentication server for realizing a secure assignment of a DHCP address are disclosed, which includes: sending a DHCP Discovery message via an access network; obtaining the identification information of the DHCP client and performing an authenticating to the client based on identification information; and only assigning the address to the registry after the client has passed the authentication.
Abstract: A method, a system and an authentication server for realizing a secure assignment of a DHCP address are disclosed. The method includes: sending a DHCP Discovery message via an access network; obtaining the identification information of the DHCP client and performing an authenticating to the DHCP client based on the identification information; and only assigning the address to the DHCP client has passed the authentication. Therefore, in the present invention, access authentication may be performed on a subscriber according to location information, and IP address is only assigned to the valid subscriber and terminal. Therefore, the security of the address assignment in DHCP mode may be enhanced greatly. Moreover, in the present invention, addresses may be managed by an AAA server unitedly, or the addresses may be assigned after being authenticated by the AAA server successfully.
97 citations
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08 Dec 2016TL;DR: In this article, a per-service handover for a user equipment between hypercells is described, where the user equipment is transferred from a source cell to a target cell in respect of one of uplink and downlink communications.
Abstract: Systems and methods of performing handover for a user equipment between hyper cells are provided. Handover is done on a per service basis. In some cases, a handover of one service from a source cell to target cell is performed while continuing to use the source cell, the target cell, or another cell for another service. In some cases the handover for a user equipment is from a source cell to a target cell in respect of one of uplink and downlink communications, and the user equipment continues to use the source cell for the other of uplink and downlink communications.
97 citations
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TL;DR: Deep Reinforcement Learning is leveraged to extract knowledge from experience by interacting with the network and enable dynamic adjustment of the resources allocated to various slices in order to maximise the resource utilisation while guaranteeing the Quality-of-Service (QoS).
97 citations
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TL;DR: In this paper, different non-data-aided (blind) CD estimation methods for single-carrier transmission under implementation constraint conditions such as bandwidth limitation and sampling rate are presented.
Abstract: Polarization-diverse coherent demodulation allows to compensate large values of accumulated linear distortion by digital signal processing. In particular, in uncompensated links without optical dispersion compensation, the parameter of the residual chromatic dispersion (CD) is vital to set the according digital filtering function. We present different non-data-aided (blind) CD estimation methods for single-carrier transmission under implementation constraint conditions such as bandwidth limitation and sampling rate. The estimation performance for various modulation formats is compared with respect to precision and robustness for a wide range of combined channel impairments.
97 citations
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TL;DR: This work develops an efficient continuous evolutionary approach for searching neural networks that provides a series of networks with the number of parameters ranging from 3.7M to 5.1M under mobile settings and surpasses those produced by the state-of-the-art methods on the benchmark ImageNet dataset.
Abstract: Searching techniques in most of existing neural architecture search (NAS) algorithms are mainly dominated by differentiable methods for the efficiency reason. In contrast, we develop an efficient continuous evolutionary approach for searching neural networks. Architectures in the population that share parameters within one SuperNet in the latest generation will be tuned over the training dataset with a few epochs. The searching in the next evolution generation will directly inherit both the SuperNet and the population, which accelerates the optimal network generation. The non-dominated sorting strategy is further applied to preserve only results on the Pareto front for accurately updating the SuperNet. Several neural networks with different model sizes and performances will be produced after the continuous search with only 0.4 GPU days. As a result, our framework provides a series of networks with the number of parameters ranging from 3.7M to 5.1M under mobile settings. These networks surpass those produced by the state-of-the-art methods on the benchmark ImageNet dataset.
97 citations
Authors
Showing all 41483 results
Name | H-index | Papers | Citations |
---|---|---|---|
Yu Huang | 136 | 1492 | 89209 |
Xiaoou Tang | 132 | 553 | 94555 |
Xiaogang Wang | 128 | 452 | 73740 |
Shaobin Wang | 126 | 872 | 52463 |
Qiang Yang | 112 | 1117 | 71540 |
Wei Lu | 111 | 1973 | 61911 |
Xuemin Shen | 106 | 1221 | 44959 |
Li Chen | 105 | 1732 | 55996 |
Lajos Hanzo | 101 | 2040 | 54380 |
Luca Benini | 101 | 1453 | 47862 |
Lei Liu | 98 | 2041 | 51163 |
Tao Wang | 97 | 2720 | 55280 |
Mohamed-Slim Alouini | 96 | 1788 | 62290 |
Qi Tian | 96 | 1030 | 41010 |
Merouane Debbah | 96 | 652 | 41140 |