TY - GEN
T1 - Location-aware network operation for cloud radio access network
AU - Wang, Fanggang
AU - Ruan, Liangzhong
AU - Win, Moe Z.
N1 - KAUST Repository Item: Exported on 2020-10-01
Acknowledgements: 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.
This publication acknowledges KAUST support, but has no KAUST affiliated authors.
PY - 2017/6/20
Y1 - 2017/6/20
N2 - 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.
AB - 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.
UR - http://hdl.handle.net/10754/625804
UR - http://ieeexplore.ieee.org/document/7952850/
UR - http://www.scopus.com/inward/record.url?scp=85023750686&partnerID=8YFLogxK
U2 - 10.1109/icassp.2017.7952850
DO - 10.1109/icassp.2017.7952850
M3 - Conference contribution
SN - 9781509041176
SP - 3714
EP - 3718
BT - 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
PB - Institute of Electrical and Electronics Engineers (IEEE)
ER -