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TitleEstimation and equalization of communications channels using wavelet transforms
NameVaz, Canute (author), Daut, David (chair), McAfee, Sigrid (internal member), Orfanidis, Sophocles (internal member), Sannuti, Peddapullaiah (internal member), Chant, Robert (outside member), Rutgers University, Graduate School - New Brunswick,
Degree Date2010-01
Date Created2010
SubjectElectrical and Computer Engineering,
Signal processing,
Wavelets (Mathematics)
DescriptionThis dissertation features the development of signal processing strategies for the estimation of the impulse responses of channels and the equalization of the effects of channels on communications signals propagating through them using the Discrete Wavelet Transform (DWT). The two strategies are developed as part of a wavelet-based signal processing platform, which can be used to enable reconfigurable radio transceivers.
In broad terms, the approach that is taken is to recast standard discrete time-domain signal processing procedures into a DWT-based framework. To facilitate this, three equivalent techniques of DWT-based convolution are devised. The techniques are described analytically using a systems-theoretic approach. The convolution techniques use both standard subband coding as well as polyphase filter implementations.
Consequent to the development of DWT-based convolution is a DWT-based deconvolution procedure that is derived analytically. The deconvolution procedure is then applied to the problem of the estimation of several time-invariant multipath communications channels. Conditions of slow and fast fading are considered, and faded test signals are also subjected to Additive White Gaussian Noise (AWGN) that result in ratios of bit-energy-to-noise-power-density, Eb/N0, in the range of 0 to 60 dB. Monte Carlo simulations of the estimation of the channel impulse responses yield Mean-Square Error (MSE) results with excellent statistical agreement even for coarse levels of DWT resolution when compared with standard discrete time-domain deconvolution.
Using DWT-based convolution the linear equalization techniques of Zero Forcing Equalization (ZFE) and Minimum Mean-Squared Error (MMSE) equalization, are formulated and implemented in the wavelet-domain. Monte Carlo simulations of the equalization of a fast fading channel with Eb/N0 in the range from 0 dB to 60 dB show that the performance of both linear equalizers in the time and wavelet-domains is essentially identical.
Allied with the primary objective of the dissertation, both DWT-based channel estimation and equalization are included in communications systems. In Monte Carlo simulations of these systems, signals that are digitally modulated with the Binary Amplitude Shift Keying (BASK), Binary Frequency Shift Keying (BFSK) and 16-Quadrature Amplitude Modulation (16-QAM) schemes are propagated through a fast fading channel. The faded signals are subjected to AWGN resulting in Eb/N0 in the range from 0 dB to 20 dB. The performance of these hybrid time- and DWT-based communications systems is evaluated with Symbol Error Rate (SER) curves that show no decrease in performance when compared with discrete time-domain system methods.
In broad terms, the approach that is taken is to recast standard discrete time-domain signal processing procedures into a DWT-based framework. To facilitate this, three equivalent techniques of DWT-based convolution are devised. The techniques are described analytically using a systems-theoretic approach. The convolution techniques use both standard subband coding as well as polyphase filter implementations.
Consequent to the development of DWT-based convolution is a DWT-based deconvolution procedure that is derived analytically. The deconvolution procedure is then applied to the problem of the estimation of several time-invariant multipath communications channels. Conditions of slow and fast fading are considered, and faded test signals are also subjected to Additive White Gaussian Noise (AWGN) that result in ratios of bit-energy-to-noise-power-density, Eb/N0, in the range of 0 to 60 dB. Monte Carlo simulations of the estimation of the channel impulse responses yield Mean-Square Error (MSE) results with excellent statistical agreement even for coarse levels of DWT resolution when compared with standard discrete time-domain deconvolution.
Using DWT-based convolution the linear equalization techniques of Zero Forcing Equalization (ZFE) and Minimum Mean-Squared Error (MMSE) equalization, are formulated and implemented in the wavelet-domain. Monte Carlo simulations of the equalization of a fast fading channel with Eb/N0 in the range from 0 dB to 60 dB show that the performance of both linear equalizers in the time and wavelet-domains is essentially identical.
Allied with the primary objective of the dissertation, both DWT-based channel estimation and equalization are included in communications systems. In Monte Carlo simulations of these systems, signals that are digitally modulated with the Binary Amplitude Shift Keying (BASK), Binary Frequency Shift Keying (BFSK) and 16-Quadrature Amplitude Modulation (16-QAM) schemes are propagated through a fast fading channel. The faded signals are subjected to AWGN resulting in Eb/N0 in the range from 0 dB to 20 dB. The performance of these hybrid time- and DWT-based communications systems is evaluated with Symbol Error Rate (SER) curves that show no decrease in performance when compared with discrete time-domain system methods.
NotePh.D.
NoteIncludes bibliographical references (p. 218-230)
Noteby Canute Vaz
Genretheses
Persistent URLhttp://hdl.rutgers.edu/1782.2/rucore10001600001.ETD.000052157
Languageeng
CollectionGraduate School - New Brunswick Electronic Theses and Dissertations
Organization NameRutgers, The State University of New Jersey
RightsThe author owns the copyright to this work.