Low-Complexity Scheduling and Power Adaptation for Coordinated Cloud-Radio Access Networks
KAUST DepartmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Electrical Engineering Program
Online Publication Date2017-07-17
Print Publication Date2017-10
Permanent link to this recordhttp://hdl.handle.net/10754/625223
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AbstractIn practical wireless systems, the successful implementation of resource allocation techniques strongly depends on the algorithmic complexity. Consider a cloud-radio access network (CRAN), where the central cloud is responsible for scheduling devices to the frames’ radio resources blocks (RRBs) of the single-antenna base-stations (BSs), adjusting the transmit power levels, and for synchronizing the transmit frames across the connected BSs. Previous studies show that the jointly coordinated scheduling and power control problem in the considered CRAN can be solved using an approach that scales exponentially with the number of BSs, devices, and RRBs, which makes the practical implementation infeasible for reasonably sized networks. This paper instead proposes a low-complexity solution to the problem, under the constraints that each device cannot be served by more than one BS but can be served by multiple RRBs within each BS frame, and under the practical assumption that the channel is constant during the duration of each frame. The paper utilizes graph-theoretical based techniques and shows that constructing a single power control graph is sufficient to obtain the optimal solution with a complexity that is independent of the number of RRBs. Simulation results reveal the optimality of the proposed solution for slow-varying channels, and show that the solution performs near-optimal for highly correlated channels.
CitationDouik A, Dahrouj H, Al-Naffouri TY, Alouini M-S (2017) Low-Complexity Scheduling and Power Adaptation for Coordinated Cloud-Radio Access Networks. IEEE Communications Letters: 1–1. Available: http://dx.doi.org/10.1109/LCOMM.2017.2728009.
SponsorsHayssam 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
JournalIEEE Communications Letters