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Delay-Aware Green Hybrid CRAN
KTH, School of Information and Communication Technology (ICT), Communication Systems, CoS.ORCID iD: 0000-0002-6614-5208
KTH, School of Information and Communication Technology (ICT), Communication Systems, CoS.ORCID iD: 0000-0003-4006-5848
2017 (English)In: 2017 15th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks, WiOpt 201727 June 2017, IEEE conference proceedings, 2017, 7959942Conference paper, Published paper (Refereed)
Abstract [en]

As a potential candidate architecture for 5G systems,cloud radio access network (CRAN) enhances the system’s capacityby centralizing the processing and coordination at the centralcloud. However, this centralization imposes stringent bandwidthand delay requirements on the fronthaul segment of the networkthat connects the centralized baseband processing units (BBUs)to the radio units (RUs). Hence, hybrid CRAN is proposed toalleviate the fronthaul bandwidth requirement. The concept ofhybrid CRAN supports the proposal of splitting/virtualizing theBBU functions processing between the central cloud (centraloffice that has large processing capacity and efficiency) and theedge cloud (an aggregation node which is closer to the user,but usually has less efficiency in processing). In our previouswork, we have studied the impact of different split points onthe system’s energy and fronthaul bandwidth consumption. Inthis study, we analyze the delay performance of the end user’srequest. We propose an end-to-end (from the central cloud tothe end user) delay model (per user’s request) for differentfunction split points. In this model, different delay requirementsenforce different function splits, hence affect the system’s energyconsumption. Therefore, we propose several research directionsto incorporate the proposed delay model in the problem ofminimizing energy and bandwidth consumption in the network.We found that the required function split decision, to achieveminimum delay, is significantly affected by the processing powerefficiency ratio between processing units of edge cloud and centralcloud. High processing efficiency ratio ( 1) leads to significantdelay improvement when processing more base band functionsat the edge cloud.

Place, publisher, year, edition, pages
IEEE conference proceedings, 2017. 7959942
National Category
Communication Systems
Identifiers
URN: urn:nbn:se:kth:diva-211446DOI: 10.23919/WIOPT.2017.7959942ISI: 000413806500081Scopus ID: 2-s2.0-85026252053ISBN: 9783901882906 (print)OAI: oai:DiVA.org:kth-211446DiVA: diva2:1129230
Conference
15th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks, WiOpt 2017, Paris, France, 15 May 2017 through 19 May 2017
Note

QC 20170803

Available from: 2017-08-01 Created: 2017-08-01 Last updated: 2017-11-20Bibliographically approved

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