Paper Info
Title
Coordinated Scheduling and Spectrum Sharing via Matrix Fractional Programming.
Abstract
Interference management is a fundamental issue in device-to-device (D2D) communications whenever the transmitter-and-receiver pairs are located geographically in close proximity and frequencies are fully reused, so active links may severely interfere with each other. This paper devises an optimization strategy named FPLinQ to coordinate the link scheduling decisions among the interfering links, along with power control and beamforming. The key enabler is a novel optimization method called matrix fractional programming (FP) that generalizes previous scalar and vector forms of FP in allowing multiple data streams per link. From a theoretical perspective, this paper provides a deeper understanding of FP by showing a connection to the minorization-maximization (MM) algorithm. From an application perspective, this paper shows that as compared to the existing methods for coordinating scheduling in the D2D network, such as FlashLinQ, ITLinQ, and ITLinQ+, the proposed FPLinQ approach is more general in allowing multiple antennas at both the transmitters and the receivers, and further in allowing arbitrary and multiple possible associations between the devices via matching. Numerical results show that FPLinQ significantly outperforms the previous state-of-the-art in a typical D2D communication environment.
Year
Venue
Field
2018
arXiv: Information Theory
Beamforming,Multiple data,Matrix (mathematics),Scheduling (computing),Computer science,Scalar (physics),Power control,Spectrum sharing,Fractional programming,Distributed computing
DocType
Volume
Citations 
Journal
abs/1808.05678
0
PageRank 
References 
Authors
0.34
22
4
Name
Order
Citations
PageRank
Kaiming Shen125114.76
Wei Yu232422.95
Licheng Zhao301.69
Daniel Pérez Palomar42146134.10