Location-aware network operation for cloud radio access network

Handle URI:
http://hdl.handle.net/10754/625804
Title:
Location-aware network operation for cloud radio access network
Authors:
Wang, Fanggang; Ruan, Liangzhong; Win, Moe Z.
Abstract:
One of the major challenges in effectively operating a cloud radio access network (C-RAN) is the excessive overhead signaling and computation load that scale rapidly with the size of the network. In this paper, the exploitation of location information of the mobile devices is proposed to address this challenge. We consider an approach in which location-assisted channel state information (CSI) acquisition methods are introduced to complement conventional pilot-based CSI acquisition methods and avoid excessive overhead signaling. A low-complexity algorithm is designed to maximize the sum rate. An adaptive algorithm is also proposed to address the uncertainty issue in CSI acquisition. Both theoretical and numerical analyses show that location information provides a new dimension to improve throughput for next-generation massive cooperative networks.
Citation:
Wang F, Ruan L, Win MZ (2017) Location-aware network operation for cloud radio access network. 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). Available: http://dx.doi.org/10.1109/icassp.2017.7952850.
Publisher:
IEEE
Journal:
2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
Issue Date:
20-Jun-2017
DOI:
10.1109/icassp.2017.7952850
Type:
Conference Paper
Sponsors:
This work was supported in part by the National Natural Science Foundation under Grant 61571034 and under Grant U1334202, the State Key Laboratory of Rail Traffic Control and Safety under Grant RCS2016ZT013, the Fundamental Research Funds for the Central Universities under Grant 2015JBM112, Office of Naval Research Grant No. N00014-16-1-2141, and the Sensor Research Initiative through the Office of Sponsored Research at the King Abdullah University of Science and Technology, Saudi Arabia.
Appears in Collections:
Publications Acknowledging KAUST Support

Full metadata record

DC FieldValue Language
dc.contributor.authorWang, Fanggangen
dc.contributor.authorRuan, Liangzhongen
dc.contributor.authorWin, Moe Z.en
dc.date.accessioned2017-10-04T14:59:17Z-
dc.date.available2017-10-04T14:59:17Z-
dc.date.issued2017-06-20en
dc.identifier.citationWang F, Ruan L, Win MZ (2017) Location-aware network operation for cloud radio access network. 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). Available: http://dx.doi.org/10.1109/icassp.2017.7952850.en
dc.identifier.doi10.1109/icassp.2017.7952850en
dc.identifier.urihttp://hdl.handle.net/10754/625804-
dc.description.abstractOne of the major challenges in effectively operating a cloud radio access network (C-RAN) is the excessive overhead signaling and computation load that scale rapidly with the size of the network. In this paper, the exploitation of location information of the mobile devices is proposed to address this challenge. We consider an approach in which location-assisted channel state information (CSI) acquisition methods are introduced to complement conventional pilot-based CSI acquisition methods and avoid excessive overhead signaling. A low-complexity algorithm is designed to maximize the sum rate. An adaptive algorithm is also proposed to address the uncertainty issue in CSI acquisition. Both theoretical and numerical analyses show that location information provides a new dimension to improve throughput for next-generation massive cooperative networks.en
dc.description.sponsorshipThis work was supported in part by the National Natural Science Foundation under Grant 61571034 and under Grant U1334202, the State Key Laboratory of Rail Traffic Control and Safety under Grant RCS2016ZT013, the Fundamental Research Funds for the Central Universities under Grant 2015JBM112, Office of Naval Research Grant No. N00014-16-1-2141, and the Sensor Research Initiative through the Office of Sponsored Research at the King Abdullah University of Science and Technology, Saudi Arabia.en
dc.publisherIEEEen
dc.titleLocation-aware network operation for cloud radio access networken
dc.typeConference Paperen
dc.identifier.journal2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)en
dc.contributor.institutionLaboratory for Information and Decision Systems, Massachusetts Institute of Technology, United States of Americaen
dc.contributor.institutionState Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Chinaen
All Items in KAUST are protected by copyright, with all rights reserved, unless otherwise indicated.