Title
A Low-Rank Approach For Interference Management In Dense Wireless Networks
Abstract
The curse of big data, propelled by the explosive growth of mobile devices, places overwhelming pressures on wireless communications. Network densification is a promising approach to improve the area spectral efficiency, but to acquire massive channel state information (CSI) for effective interference management becomes a formidable task. In this paper, we propose a novel interference management method which only requires the network connectivity information, i.e., the knowledge of the presence of strong links, and statistical information of the weak links To acquire such mixed network connectivity information incurs significant less overhead than complete CSI, and thus this method is scalable to large network sizes. To maximize the sum-rate with the mixed network connectivity information, we formulate a rank minimization problem to cancel strong interference and suppress weak interference, which is then solved by a Riemannian trust-region algorithm. Such algorithm is robust to initial points and has a fast convergence rate. Simulation result shows that our approach achieves a higher data rate than the state-of-the-art methods.
Year
Venue
Keywords
2016
2016 IEEE GLOBAL CONFERENCE ON SIGNAL AND INFORMATION PROCESSING (GLOBALSIP)
Topological interference management, capacity, sum-rate, interference leakage, Riemannian optimization
Field
DocType
ISSN
Wireless network,Wireless,Computer science,Computer network,Robustness (computer science),Interference (wave propagation),Spectral efficiency,Rate of convergence,Scalability,Channel state information,Distributed computing
Conference
2376-4066
Citations 
PageRank 
References 
0
0.34
0
Authors
5
Name
Order
Citations
PageRank
kai yang111630.39
Yuanming Shi265953.58
Jun Zhang33772190.36
Zhi Ding4492136.76
K. B. Letaief511078879.10