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15 - Generalized Low-Rank Optimization for Ultra-dense Fog-RANs

from Part III - Resource Allocation and Network Management

Published online by Cambridge University Press:  12 October 2020

Haijun Zhang
Affiliation:
University of Science and Technology Beijing
Jemin Lee
Affiliation:
Daegu Gyeongbuk Institute of Science and Technology, Korea
Tony Q. S. Quek
Affiliation:
Singapore University of Technology and Design
Chih-Lin I
Affiliation:
China Mobile Research Institute
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Summary

As mobile data traffic keeps growing and mobile applications pose increasingly stringent and diverse requirements, wireless networks are facing unprecedented pressures. Network infrastructure densification presents promises to further evolve wireless networks and maintain their competitiveness. Deploying more radio access points equipped with storage and computation capabilities can increase network capacity, improve network energy efficiency, provide low-latency services and access for massive devices. The benefits of network densification can be exploited using the emerging fog radio access network (Fog-RAN) architecture by pushing computation and storage resources to network edges. However, it comes with formidable technical challenges. Innovative methodologies are needed to operate such networks with various resources. This chapter develops a generalized low-rank optimization model for performance enhancements in ultra-dense Fog-RANs, supported by various motivating design objectives including mobile edge caching and topological interference alignment. A special attention is paid on algorithmic approaches for nonconvex low-rank optimization problems via Riemannian optimization.

Type
Chapter
Information
Ultra-dense Networks
Principles and Applications
, pp. 277 - 300
Publisher: Cambridge University Press
Print publication year: 2020

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