Title page for ETD etd-10022008-063026


Type of Document Dissertation
Author He, Rong
URN etd-10022008-063026
Title AMPS co-channel interference rejection techniques and their impact on system capacity
Degree PhD
Department Electrical Engineering
Advisory Committee
Advisor Name Title
Reed, Jeffrey Hugh Committee Chair
Bostian, Charles W. Committee Member
Rappaport, Theodore S. Committee Member
Ribbens, Calvin J. Committee Member
Woerner, Brian D. Committee Member
Keywords
  • wireless communications
  • AMPS
  • adaptive filtering
  • cyclostationarity
  • cellular capacity
  • interference rejection
Date of Defense 1996-07-05
Availability restricted
Abstract
With the rapid and ubiquitous deployment of mobile communications in recent years, cochannel interference has become a critical problem because of its impact on system capacity and quality of service. The conventional approach to minimizing interference is through better cell planning and design. Digital Signal Processing COSP) based interference rejection techniques provide an alternative approach to minimize interference and improve system capacity.

Single channel adaptive interference rejection techniques have long been used for enhancing digitally modulated signals. However these techniques are not well suited for analog mobile phone system (AMPS) and narrowband AMPS (NAMPS) signals because of the large spectral overlap of the signals of interest with interfering signals and because of the lack of a well defined signal structure that can be used to separate the signals. Our research has created novel interference rejection techniques based on time-dependent filtering which exploit spectral correlation characteristics exhibited by AMPS and NAMPS signals. A mathematical analysis of the cyclostationary features of AMPS and NAMPS signals is presented to help explain and analyze these techniques. Their performance is investigated using both simulated and digitized data. The impact of these new techniques on AMPS system capacity is also studied. The adaptive algorithms and structures are refined to be robust in various channel environments and to be computationally efficient.

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