TY - GEN
T1 - Joint Scheduling and Beamforming via Cloud-Radio Access Networks Coordination
AU - Douik, Ahmed
AU - Dahrouj, Hayssam
AU - Al-Naffouri, Tareq Y.
AU - Alouini, Mohamed-Slim
N1 - KAUST Repository Item: Exported on 2020-10-01
Acknowledgements: Hayssam Dahrouj would like to thank Effat University in Jeddah, Saudi Arabia, for funding the research reported in this paper through the Research and Consultancy Institute.
PY - 2019/4/15
Y1 - 2019/4/15
N2 - Cloud radio access network (CRAN) emerges as a promising architecture for large-scale interference management. This paper addresses the benefit of one particular type of coordinated resource allocation in CRANs through the combined effect of joint scheduling and beamforming. Consider the downlink of a CRAN where the cloud is connected to several remote radio heads (RRHs), each equipped with multiple antennas. The transmit frame of every RRH is formed by several radio resource blocks (RRBs), each capable of serving multiple single-antenna users via spatial multiplexing using beamforming. The paper focuses on the problem of maximizing the network-wide weighted sum-rate by jointly determining the set of scheduled users at each RRB, and their corresponding beamforming vectors. The main contribution of the paper is to solve such a mixed discrete-continuous optimization problem using a graph-theoretical based approach. The paper introduces the joint scheduling and beamforming graph, wherein each independent set accounts for a feasible schedule and feasible beamforming vectors. Afterward, the joint scheduling and beamforming problem is shown to be equivalent to a maximum independent set problem in the proposed graph. Simulation results suggest that the proposed joint solution provides appreciable performance improvements as compared to the classical iterative approach.
AB - Cloud radio access network (CRAN) emerges as a promising architecture for large-scale interference management. This paper addresses the benefit of one particular type of coordinated resource allocation in CRANs through the combined effect of joint scheduling and beamforming. Consider the downlink of a CRAN where the cloud is connected to several remote radio heads (RRHs), each equipped with multiple antennas. The transmit frame of every RRH is formed by several radio resource blocks (RRBs), each capable of serving multiple single-antenna users via spatial multiplexing using beamforming. The paper focuses on the problem of maximizing the network-wide weighted sum-rate by jointly determining the set of scheduled users at each RRB, and their corresponding beamforming vectors. The main contribution of the paper is to solve such a mixed discrete-continuous optimization problem using a graph-theoretical based approach. The paper introduces the joint scheduling and beamforming graph, wherein each independent set accounts for a feasible schedule and feasible beamforming vectors. Afterward, the joint scheduling and beamforming problem is shown to be equivalent to a maximum independent set problem in the proposed graph. Simulation results suggest that the proposed joint solution provides appreciable performance improvements as compared to the classical iterative approach.
UR - http://hdl.handle.net/10754/631981
UR - https://ieeexplore.ieee.org/document/8690904
UR - http://www.scopus.com/inward/record.url?scp=85064950821&partnerID=8YFLogxK
U2 - 10.1109/vtcfall.2018.8690904
DO - 10.1109/vtcfall.2018.8690904
M3 - Conference contribution
SN - 9781538663585
BT - 2018 IEEE 88th Vehicular Technology Conference (VTC-Fall)
PB - Institute of Electrical and Electronics Engineers (IEEE)
ER -