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User equipment

About: User equipment is a research topic. Over the lifetime, 23201 publications have been published within this topic receiving 186786 citations. The topic is also known as: user equipment & UE.


Papers
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Journal ArticleDOI
TL;DR: This paper describes major use cases and reference scenarios where the mobile edge computing (MEC) is applicable and surveys existing concepts integrating MEC functionalities to the mobile networks and discusses current advancement in standardization of the MEC.
Abstract: Technological evolution of mobile user equipment (UEs), such as smartphones or laptops, goes hand-in-hand with evolution of new mobile applications. However, running computationally demanding applications at the UEs is constrained by limited battery capacity and energy consumption of the UEs. A suitable solution extending the battery life-time of the UEs is to offload the applications demanding huge processing to a conventional centralized cloud. Nevertheless, this option introduces significant execution delay consisting of delivery of the offloaded applications to the cloud and back plus time of the computation at the cloud. Such a delay is inconvenient and makes the offloading unsuitable for real-time applications. To cope with the delay problem, a new emerging concept, known as mobile edge computing (MEC), has been introduced. The MEC brings computation and storage resources to the edge of mobile network enabling it to run the highly demanding applications at the UE while meeting strict delay requirements. The MEC computing resources can be exploited also by operators and third parties for specific purposes. In this paper, we first describe major use cases and reference scenarios where the MEC is applicable. After that we survey existing concepts integrating MEC functionalities to the mobile networks and discuss current advancement in standardization of the MEC. The core of this survey is, then, focused on user-oriented use case in the MEC, i.e., computation offloading. In this regard, we divide the research on computation offloading to three key areas: 1) decision on computation offloading; 2) allocation of computing resource within the MEC; and 3) mobility management. Finally, we highlight lessons learned in area of the MEC and we discuss open research challenges yet to be addressed in order to fully enjoy potentials offered by the MEC.

1,829 citations

Patent
29 Dec 2005
TL;DR: In this article, a user may configure the delivery of the selected television program and associated data and interactive applications to different user equipment devices in a home network, which may have different capabilities.
Abstract: When selecting a television program for recording, a user may configure the delivery of the selected television program and associated data and interactive applications to different user equipment devices in a home network, which may have different capabilities. Because the user equipment devices in the home network may have different capabilities, the user may wish to deliver different types and amount of content, different amounts of data, and different versions of interactive applications to the user equipment devices in the home network.

757 citations

Proceedings ArticleDOI
08 Jun 2015
TL;DR: In this article, the authors proposed a novel association algorithm and proved its superiority w.r.t. prior art by means of simulations that are based on Vodafone's small cell trial network and employing a high resolution pathloss prediction and realistic user distributions.
Abstract: Until the 4th Generation (4G) cellular 3GPP systems, a user equipment's (UE) cell association has been based on the downlink received power from the strongest base station. Recent work has shown that - with an increasing degree of heterogeneity in emerging 5G systems - such an approach is dramatically suboptimal, advocating for an independent association of the downlink and uplink where the downlink is served by the macro cell and the uplink by the nearest small cell. In this paper, we advance prior art by explicitly considering the cell-load as well as the available backhaul capacity during the association process. We introduce a novel association algorithm and prove its superiority w.r.t. prior art by means of simulations that are based on Vodafone's small cell trial network and employing a high resolution pathloss prediction and realistic user distributions. We also study the effect that different power control settings have on the performance of our algorithm.

756 citations

Patent
22 May 1981
TL;DR: In this paper, an acquisition-aiding signal generated by an earth-based control station (12) is relayed to user terminals via a geostationary satellite (10) to simplify user equipment.
Abstract: In a global positioning system (GPS), such as the NAVSTAR/GPS system, wherein the position coordinates of user terminals (14) are obtained by processing multiple signals transmitted by a constellation of orbiting satellites (16), an acquisition-aiding signal generated by an earth-based control station (12) is relayed to user terminals via a geostationary satellite (10) to simplify user equipment. The aiding signal is FSK modulated on a reference channel slightly offset from the standard GPS channel. The aiding signal identifies satellites in view having best geometry and includes Doppler prediction data as well as GPS satellite coordinates and identification data associated with user terminals within an area being served by the control station (12) and relay satellite (10). The aiding signal significantly reduces user equipment by simplifying spread spectrum signal demodulation and reducing data processing functions previously carried out at the user terminals (14).

561 citations

Proceedings ArticleDOI
29 Nov 2010
TL;DR: This paper forms the problem of radio resource allocation to the D2D communications as a mixed integer nonlinear programming (MINLP) and proposes an alternative greedy heuristic algorithm that can lessen interference to the primary cellular network utilizing channel gain information.
Abstract: Device-to-device (D2D) communication as an underlaying cellular network empowers user-driven rich multimedia applications and also has proven to be network efficient offloading eNodeB traffic. However, D2D transmitters may cause significant amount of interference to the primary cellular network when radio resources are shared between them. During the downlink (DL) phase, primary cell UE (user equipment) may suffer from interference by the D2D transmitter. On the other hand, the immobile eNodeB is the victim of interference by the D2D transmitter during the uplink (UL) phase when radio resources are allocated randomly. Such interference can be avoided otherwise diminish if radio resource allocated intelligently with the coordination from the eNodeB. In this paper, we formulate the problem of radio resource allocation to the D2D communications as a mixed integer nonlinear programming (MINLP). Such an optimization problem is notoriously hard to solve within fast scheduling period of the Long Term Evolution (LTE) network. We therefore propose an alternative greedy heuristic algorithm that can lessen interference to the primary cellular network utilizing channel gain information. We also perform extensive simulation to prove the efficacy of the proposed algorithm.

551 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
2023123
2022236
2021752
20201,797
20191,953
20182,012