Practical implementation of time covariance based spectrum sensing methods using WARP

Kuo Hao Lee, Abhijeet Mate, I. Tai Lu

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

Abstract

Cognitive radio is a promising technology to deal with the spectrum scarcity problem. One important application of cognitive radio is spectrum reuse. To reuse a licensed spectrum, secondary users (unlicensed users) must ensure the frequency bands are free and no primary users (licensed users) exist. Thus, accurate spectrum sensing is a fundamental requirement of cognitive radio for avoiding signal collision and several methods have been proposed. In this paper, we examine the performance of three spectrum sensing methods with Wireless Open Access Research Platform (WARP) which is developed by RICE University. Considered first is the conventional energy detection (ED) method which requires perfect knowledge of noise power and is very sensitive to noise uncertainty. Many approaches have been proposed to mitigate the noise uncertainty problem. We mainly focus on two methods based on the time covariance matrix of the received signal, called covariance method (COV) and maximum to minimum eigenvalue (MME) method. COV method utilizes ratios of time correlations with different time separations. MME method computes maximum and minimum eignvalues from the sample covariance matrix. Both COV and MME methods are insensitive to noise uncertainty and do not need any prior knowledge of signal properties of licensed users. Furthermore, these two methods are not affected theoretically by noise uncertainty. To examine the three above mentioned spectrum sensing methods in low SNR environment, we implement them by adjusting the setting in physical and network layer protocols of WARP. As predicted from theory, experimental and numerical results show that COV and MME outperform ED in large margins.

Original languageEnglish (US)
Title of host publication2011 IEEE Long Island Systems, Applications and Technology Conference, LISAT 2011
DOIs
StatePublished - 2011
Event2011 IEEE Long Island Systems, Applications and Technology Conference, LISAT 2011 - Farmingdale, NY, United States
Duration: May 6 2011May 6 2011

Publication series

Name2011 IEEE Long Island Systems, Applications and Technology Conference, LISAT 2011

Other

Other2011 IEEE Long Island Systems, Applications and Technology Conference, LISAT 2011
CountryUnited States
CityFarmingdale, NY
Period5/6/115/6/11

Keywords

  • Cognitive Radio
  • Covariance Method
  • Energy Detection
  • Maximum to Minimum Eigenvalue Method
  • Spectrum Sensing
  • WARP

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Computer Science Applications
  • Control and Systems Engineering
  • Communication

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