• DocumentCode
    653141
  • Title

    GA-Based Green SFN Planning for DTMB

  • Author

    Li Caiwei ; Zhang Xiaolin

  • Author_Institution
    Sch. of Electron. & Inf. Eng., Beihang Univ., Beijing, China
  • fYear
    2013
  • fDate
    20-23 Aug. 2013
  • Firstpage
    51
  • Lastpage
    58
  • Abstract
    This paper proposed an approach based on genetic algorithm (GA) to deploy green single frequency network (SFN) for digital terrestrial television multimedia broadcasting (DTMB). The network optimization goal is to achieve energy efficiency, low cost, low carbon and low exposure to radiation, which caters to the sustainable development strategy. The method is applied over a real area of China, which is described by a digital terrain model (DTM) with the resolution of 20m. In order to show the validity of green deployment, optimization results of three other planning strategies are also presented. Comparisons between optimization results of the four planning strategies show that green deployment strategy can achieve energy consumption savings and low exposure to radiation. Energy consumption savings lead to CO2 reductions and cost savings.
  • Keywords
    digital multimedia broadcasting; genetic algorithms; optimisation; sustainable development; telecommunication network planning; television broadcasting; television networks; CO2 reduction; China; DTMB; GA; SFN; cost saving; digital terrestrial television multimedia broadcasting; energy consumption; energy efficiency; genetic algorithm; green single frequency network planning; network optimization goal; sustainable development strategy; Conferences; Internet; Social network services; DTMB; GA; SFN; green network planning;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Green Computing and Communications (GreenCom), 2013 IEEE and Internet of Things (iThings/CPSCom), IEEE International Conference on and IEEE Cyber, Physical and Social Computing
  • Conference_Location
    Beijing
  • Type

    conf

  • DOI
    10.1109/GreenCom-iThings-CPSCom.2013.34
  • Filename
    6682048