Spectral and energy efficiency analysis for cognitive radio networks

Fourat Haider, Cheng Xiang Wang, Harald Haas, Erol Hepsaydir, Xiaohu Ge, Dongfeng Yuan

Research output: Contribution to journalArticle

50 Citations (Scopus)
104 Downloads (Pure)

Abstract

Cognitive radio (CR) is considered one of the prominent techniques for improving the utilization of the radio spectrum. A CR network (i.e., secondary network) opportunistically shares the radio resources with a licensed network (i.e., primary network). In this work, the spectral-energy efficiency trade-off for CR networks is analyzed at both link and system levels against varying signal-to-noise ratio (SNR) values. At the link level, we analyze the required energy to achieve a specific spectral efficiency for a CR channel under two different types of power constraint in different fading environments. In this aspect, besides the transmit power constraint, interference constraint at the primary receiver (PR) is also considered to protect the PR from a harmful interference. Whereas at the system level, we study the spectral and energy efficiency for a CR network that shares the spectrum with an indoor network. Adopting the extreme-value theory, we are able to derive the average spectral and energy efficiency of the CR network. It is shown that the spectral efficiency depends upon the number of the PRs, the interference threshold, and how far the secondary receivers (SRs) are located. We characterize the impact of the multi-user diversity gain of both kinds of users on the spectral and energy efficiency of the CR network. Our analysis also proves that the interference channels (i.e., channels between the secondary transmitter and PRs) have no impact on the minimum energy efficiency.

Original languageEnglish
Article number7029702
Pages (from-to)2969-2980
Number of pages12
JournalIEEE Transactions on Wireless Communications
Volume14
Issue number6
DOIs
Publication statusPublished - 2015

Keywords

  • Cognitive radio networks
  • energy efficiency
  • extreme-value theory
  • multi-user diversity gain
  • spectral efficiency

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Computer Science Applications
  • Applied Mathematics

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