Estimation and Equalization of Communications Channels Using Wavelet Transforms

Estimation and Equalization of Communications Channels Using Wavelet Transforms

Author: Canute Vaz

Publisher:

Published: 2010

Total Pages: 245

ISBN-13:

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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.


Estimation and Adaptive Equalization of Communications Channels

Estimation and Adaptive Equalization of Communications Channels

Author: Karthik Sridhar Dharmarajan

Publisher:

Published: 2015

Total Pages: 74

ISBN-13:

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The focus of this research is to determine the channel impulse response of a communications link and then equalize the channel to mitigate the e ffects of fading on the received signal. Traditionally, channel identifi cation is achieved using a deconvolution process implemented in the time-domain. An alternative method is to perform deconvolution, for the purpose of estimating communications channel structures, in the wavelet transform domain. This approach is attractive for use in agile transceivers that utilize the wavelet domain for functions such as automatic modulation recognition. An equivalent method for deconvolving discrete time-domain signals within the Discrete Wavelet Transform (DWT) framework is explained. This method of deconvolution can be applied at any level of DWT resolution from which the complete channel impulse response can be estimated. Computer simulations have been conducted to characterize the performance of the channel estimation algorithm using the Mean Square Error (MSE) criterion. The simulation experiments are performed for two di fferent channel models characterized by a Power Delay Profi le (PDP), i.e., the Gaussian PDP and the Exponential PDP. Channel conditions of slow and fast fading are considered. In addition, the faded channel output signals are corrupted by AWGN having ratios of bit energy-to-noise spectral density, Eb/N0, in the range from 0 to 30 dB. It has been found that, for both channel models, the best channel impulse response estimate is obtained from the DWT detail coe fficients at the 1st level of resolution resulting in computational effi ciency. A novel method, based on the classic LMS algorithm, has been developed for adaptive equalization of channels in the wavelet domain. Computer simulation experiments for channel equalization show that the DWT-LMS algorithm, using a Haar wavelet, performs better than the LMS algorithm for the Gaussian PDP channel in terms of the achievable bit error probabilities.


RLE Progress Report

RLE Progress Report

Author: Massachusetts Institute of Technology. Research Laboratory of Electronics

Publisher:

Published: 1997

Total Pages: 518

ISBN-13:

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Fundamentals of Wireless Communication

Fundamentals of Wireless Communication

Author: David Tse

Publisher: Cambridge University Press

Published: 2005-05-26

Total Pages: 598

ISBN-13: 9780521845274

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This textbook takes a unified view of the fundamentals of wireless communication and explains cutting-edge concepts in a simple and intuitive way. An abundant supply of exercises make it ideal for graduate courses in electrical and computer engineering and it will also be of great interest to practising engineers.