4.7 Article

Cluster Content Caching: An Energy-Efficient Approach to Improve Quality of Service in Cloud Radio Access Networks

Journal

IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS
Volume 34, Issue 5, Pages 1207-1221

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/JSAC.2016.2545384

Keywords

Content caching; energy efficiency; effective capacity; cloud-radio access networks; resource allocation

Funding

  1. National Natural Science Foundation of China [61501045, 61361166005]
  2. National 973 Program [2012CB316005]
  3. National High Technology Research and Development Program of China [2014AA01A701]
  4. State Major Science and Technology Special Projects [2016ZX03001020006]
  5. Fundamental Research Funds for the Central Universities
  6. U.K. EPSRC [EP/L025272/1]
  7. H2020MSCARISE [690750]
  8. U.S. National Science Foundation [ECCS1343210]
  9. Directorate For Engineering
  10. Div Of Electrical, Commun & Cyber Sys [1343210] Funding Source: National Science Foundation
  11. Engineering and Physical Sciences Research Council [EP/L025272/1] Funding Source: researchfish
  12. EPSRC [EP/L025272/1] Funding Source: UKRI

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In cloud radio access networks (C-RANs), a substantial amount of data must be exchanged in both backhaul and fronthaul links, which causes high power consumption and poor quality of service (QoS) experience for real-time services. To solve this problem, a cluster content caching structure is proposed in this paper, which takes full advantages of distributed caching and centralized signal processing. In particular, redundant traffic on the backhaul can be reduced because the cluster content cache provides a part of required content objects for remote radio heads (RRHs) connected to a common edge cloud. Tractable expressions for both effective capacity and energy efficiency performance are derived, which show that the proposed structure can improve QoS guarantees with a lower cost of local storage. Furthermore, to fully explore the potential of the proposed cluster content caching structure, the joint design of resource allocation and RRH association is optimized, and two distributed algorithms are accordingly proposed. Simulation results verify the accuracy of the analytical results and show the performance gains achieved by cluster content caching in C-RANs.

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