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A novel adaptive filter for interference suppression

  • School of Electronics and Information Engineering, Harbin Institute of Technology

Research output: Contribution to conferencePaperpeer-review

Abstract

In wireless communication systems of consumer electronics, it is very important to suppress the interference and extract the target effectively without any phase-amplitude shift. A number of signal processing optimal algorithms developed, we apply the smart antenna to adaptive filtering. But the performances of adaptive filtering differ from each other corresponding to different algorithms. The linear constraint minimum variance (LCMV) criteria shall be applicable to the case of lower array signal noise ratio (ASNR), while the interference suppression criteria shall be applicable to the opposite case. We can get the best performance in any cases using the maximum signal-to-interference-plus-noise ratio (MSINR) criteria, but sometimes it has application limitations. To solve this problem, an alterable parameter adaptive filter is proposed, which minimizes the output noise power under a premise, that is, there exists no shift from the target and the interference can be suppressed to a certain extent. The methods of the alterable parameter estimation are discussed, and performance analyses and simulation results are given as well. It can be concluded from the results that a nearly ideal output signal-to-interference-plus-noise ratio (SINR) of the novel adaptive filter can be expected, keeping the original phase and amplitude of the target.

Original languageEnglish
Pages57-62
Number of pages6
DOIs
StatePublished - 2013
Externally publishedYes
Event2013 IEEE International Conference on Consumer Electronics - China Workshop, ICCE-China 2013 - Shenzhen, China
Duration: 11 Apr 201313 Apr 2013

Conference

Conference2013 IEEE International Conference on Consumer Electronics - China Workshop, ICCE-China 2013
Country/TerritoryChina
CityShenzhen
Period11/04/1313/04/13

Keywords

  • adaptive filter
  • interference suppression
  • signal processing

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