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You searched for +publisher:"Rutgers University" +contributor:("Vaz, Canute"). Showing records 1 – 2 of 2 total matches.

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Rutgers University

1. Vaz, Canute. Estimation and equalization of communications channels using wavelet transforms:.

Degree: PhD, Electrical and Computer Engineering, 2010, Rutgers University

This 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.

Advisors/Committee Members: Vaz, Canute (author), Daut, David (chair), McAfee, Sigrid (internal member), Orfanidis, Sophocles (internal member), Sannuti, Peddapullaiah (internal member), Chant, Robert, (outside member).

Subjects/Keywords: Signal processing; Wavelets (Mathematics)

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Vaz, C. (2010). Estimation and equalization of communications channels using wavelet transforms:. (Doctoral Dissertation). Rutgers University. Retrieved from http://hdl.rutgers.edu/1782.2/rucore10001600001.ETD.000052157

Chicago Manual of Style (16th Edition):

Vaz, Canute. “Estimation and equalization of communications channels using wavelet transforms:.” 2010. Doctoral Dissertation, Rutgers University. Accessed November 13, 2019. http://hdl.rutgers.edu/1782.2/rucore10001600001.ETD.000052157.

MLA Handbook (7th Edition):

Vaz, Canute. “Estimation and equalization of communications channels using wavelet transforms:.” 2010. Web. 13 Nov 2019.

Vancouver:

Vaz C. Estimation and equalization of communications channels using wavelet transforms:. [Internet] [Doctoral dissertation]. Rutgers University; 2010. [cited 2019 Nov 13]. Available from: http://hdl.rutgers.edu/1782.2/rucore10001600001.ETD.000052157.

Council of Science Editors:

Vaz C. Estimation and equalization of communications channels using wavelet transforms:. [Doctoral Dissertation]. Rutgers University; 2010. Available from: http://hdl.rutgers.edu/1782.2/rucore10001600001.ETD.000052157


Rutgers University

2. Ge, Yao, 1983-. Wavelet-based software-defined radio receiver design.

Degree: PhD, Electrical and Computer Engineering, 2016, Rutgers University

Software-defined radios (SDRs), have become very important in both commercial as well as military applications that demand high Quality of Service (QoS) in hostile physical and spectral conditions. Simultaneously, interoperability with legacy communications equipment is also a critical requirement for widespread adoption. An ideal SDR supports multi-standard, multimode and multiband wireless communications. Such a system is reconfigurable in the sense that transmitted signals at different carrier frequencies and/or different modulation schemes can be reliably identified and appropriately demodulated in real-time. In this dissertation, such a radio system is developed using a wavelet transform-based transceiver platform, composed of four main wavelet-domain processors: Channel Estimator, Channel Equalizer, Automatic Modulation Recognition (AMR) and Demodulator. The AMR method is blind identification of the modulation scheme used to format digital data embedded in a signal. It is investigated using the Discrete Wavelet Transform (DWT) in conjunction with techniques typically used in signal processing field of pattern recognition. In particular, the concept of wavelet-domain template matching is used to achieve modulation identification prior to signal demodulation. The digital modulation schemes considered in this work include families of ASK, FSK, PSK and QAM. The test signals used in this study have been subjected to Additive White Gaussian Noise (AWGN) resulting in Signal-to-Noise Ratios (SNRs) in the range of -5 dB to 10 dB. Monte Carlo simulations using the wavelet-based AMR algorithms show correct classification rates that are better than most of existing methods that use other techniques For wavelet-based demodulation original signal information can be directly obtained in the wavelet-domain without an inverse transform of a signal to its original time-domain form, and that has been proven analytically herein. Extensive Monte Carlo simulations have shown that the Bit Error Rates (BERs) obtained from wavelet-based demodulation are very comparable with the optimal case of matched filter-based demodulation. The results of this work show the ability of wavelet transforms to enable the automatic recognition and subsequent demodulation of communications signals in a single processing sequence by solely using the computationally-friendly mathematics of the Discrete Wavelet Transform.

Advisors/Committee Members: Gajic, Zoran (chair), Daut, David G. (co-chair), Jha, Shantenu (internal member), Marsic, Ivan (internal member), Vaz, Canute (outside member).

Subjects/Keywords: Digital communications; Software radio

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Ge, Yao, 1. (2016). Wavelet-based software-defined radio receiver design. (Doctoral Dissertation). Rutgers University. Retrieved from https://rucore.libraries.rutgers.edu/rutgers-lib/51294/

Chicago Manual of Style (16th Edition):

Ge, Yao, 1983-. “Wavelet-based software-defined radio receiver design.” 2016. Doctoral Dissertation, Rutgers University. Accessed November 13, 2019. https://rucore.libraries.rutgers.edu/rutgers-lib/51294/.

MLA Handbook (7th Edition):

Ge, Yao, 1983-. “Wavelet-based software-defined radio receiver design.” 2016. Web. 13 Nov 2019.

Vancouver:

Ge, Yao 1. Wavelet-based software-defined radio receiver design. [Internet] [Doctoral dissertation]. Rutgers University; 2016. [cited 2019 Nov 13]. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/51294/.

Council of Science Editors:

Ge, Yao 1. Wavelet-based software-defined radio receiver design. [Doctoral Dissertation]. Rutgers University; 2016. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/51294/

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