Extended study towards performance improvement of Cloud-RAN

Maha Fathy, Bassem Mokhtar, Mohamed A. Abdou, M. R.M. Rizk

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

Cloud Radio Access Network (Cloud-RAN) has recently been proposed as a promising network architecture to maintain both profitability and quality of service of the ever-growing existing networks. This paper provides an extended optimization study of improving the performance of Cloud-RAN targeting minimized consumed power for the network. The minimization problem can be formulated as a Joint RRH selection and power minimization beamforming problem. We adapt a proposed greedy selection algorithm to decrease the number of active Remote Radio Heads (RRHs) and to optimize the transmitted power from RRHs to end users maintaining heterogeneous users' QoS requirements. A heuristics-driven approach has been proposed and applied to the optimization problem to further reach better optimum solutions of power consumption and to reduce the problem complexity. Simulation results coupled with a statistical analysis show that more reduction in both power consumption and complexity have been reached.

Original languageEnglish
Title of host publication2017 13th International Wireless Communications and Mobile Computing Conference, IWCMC 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1061-1066
Number of pages6
ISBN (Electronic)9781509043729
DOIs
Publication statusPublished - Jul 19 2017
Externally publishedYes
Event13th IEEE International Wireless Communications and Mobile Computing Conference, IWCMC 2017 - Valencia, Spain
Duration: Jun 26 2017Jun 30 2017

Publication series

Name2017 13th International Wireless Communications and Mobile Computing Conference, IWCMC 2017

Other

Other13th IEEE International Wireless Communications and Mobile Computing Conference, IWCMC 2017
Country/TerritorySpain
CityValencia
Period6/26/176/30/17

Keywords

  • Beamforming
  • Cloud-RAN
  • Greedy Selection
  • Performance Optimization
  • Power Minimization

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Hardware and Architecture
  • Signal Processing

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