KSII Transactions on Internet and Information Systems (TIIS)

Korean Society for Internet Information (한국인터넷정보학회)
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User-Oriented Energy- and Spectral-Efficiency Tradeoff for Wireless Networks

  • Zhang, Yueying (Wireless Signal Process& Network Lab, Key Lab of Universal Wireless Communications, Ministry of Education, Beijing University of Posts & Telecommunications) ;
  • Long, Hang (Wireless Signal Process& Network Lab, Key Lab of Universal Wireless Communications, Ministry of Education, Beijing University of Posts & Telecommunications) ;
  • Peng, Yuexing (Wireless Signal Process& Network Lab, Key Lab of Universal Wireless Communications, Ministry of Education, Beijing University of Posts & Telecommunications) ;
  • Zheng, Kan (Wireless Signal Process& Network Lab, Key Lab of Universal Wireless Communications, Ministry of Education, Beijing University of Posts & Telecommunications) ;
  • Wang, Wenbo (Wireless Signal Process& Network Lab, Key Lab of Universal Wireless Communications, Ministry of Education, Beijing University of Posts & Telecommunications)
  • Received : 2012.11.03
  • Accepted : 2013.02.17
  • Published : 2013.02.28
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Abstract

Conventional optimization designs of wireless networks mainly focus on spectral efficiency (SE) as a performance metric. However, as diverse media services are emerging, a green wireless network, which not only meets the quality of experience (QoE) requirements for users and also improves energy efficiency (EE), is the most appropriate solution. In this paper, we firstly propose the unit QoE per Watt, which is termed QoE efficiency (QEE), as a user-oriented metric to evaluate EE for wireless networks. We then analyze which is the kind of wireless resource given priority to use under different scenarios to obtain an acceptable QEE. Particularly, power, delay and data-rate related to QoE are separately addressed for several typical services, such as file download, video stream and web browsing services. Next, the fundamental tradeoffs are investigated between QEE and SE for wireless networks. Our analytical results are helpful for network design and optimization to strike a good balance between the users perceived QoE and energy consumption.

Keywords

References

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