Mobile velocity estimation using a timefrequency approach
Azemi, Ghasem (2003) Mobile velocity estimation using a timefrequency approach. PhD thesis, Queensland University of Technology.

Ghasem Azemi Thesis (PDF 4MB) 
Abstract
This thesis deals with the problem of estimating the velocity of a mobile station (MS)in a mobile communication system using the instantaneous frequency (IF) of the received signal at the MS antenna. This estimate is essential for satisfactory handover performance, effective dynamic channel assignment, and optimisation of adaptive multiple access wireless receivers. Conventional methods for estimating the MS velocity are based either on the statistics of the envelope or quadrature components of the received signal. In chapter 4 of the thesis, we show that their performance deteriorates in the presence of shadowing. Other velocity estimators have also been proposed which require prior estimation of the channel or the average received power. These are generally difficult to obtain due to the nonstationary nature of the received signal. An appropriate window which depends on the unknown MS velocity must first be applied in order to accurately estimate the required quantities. Using the statistics of the IF of the received signal at the MS antenna given in chapter 3, new velocity estimators are proposed in chapter 4 of this thesis. The proposed estimators are based on the moments, zerocrossing rate, and covariance of the received IF. Since the IF of the received signal is not affected by any amplitude distortion, the proposed IFbased estimators are robust to shadowing and propagation pathloss. The estimators for the MS velocity in a macro and microcellular system are presented separately. A macrocell system can be considered as a special case of a microcell in which there is no lineofsight component at the receiver antenna. It follows that those estimators which are derived for microcells can be used in a macrocell as well. In chapter 4, we analyse the performance of the proposed velocity estimators in the presence of additive noise, nonisotropic scattering, and shadowing. We also prove analytically that the proposed velocity estimators outperform the existing methods in the presence of shadowing and additive noise. The proposed IFbased estimators need prior estimation of both the IF of the received signal and Ricean Kfactor. The IF estimation in a typical wireless environment, can be considered as a special case of a general problem of IF estimation in the presence of multiplicative and additive noise. In chapter 5, we show that current timefrequency approaches to this problem which are based on the peak of a timefrequency distribution (TFD) of the signal, fail because of the special shape of the power spectral density of the multiplicative noise in a wireless environment. To overcome this drawback, the use of the firstorder moment of a TFD is studied in chapter 5. Theoretical analysis and simulations show that the IF estimator based on the firstorder moment of a TFD exhibits negligible bias when the signaltoadditive noise ratio is more than 10 dB. The Ricean Kfactor is not only necessary for velocity estimation in microcells, but also is a measure of the severity of fading and a good indicator of the channel quality. Two new methods for estimating the Ricean Kfactor based on the first two moments of the envelope of the received signal, are proposed in chapter 6. Performance analysis presented in chapter 6, prove that the proposed K estimators are robust to nonisotropic scattering. Theoretical analysis and simulations which are presented in chapters 4 and 7 of this thesis, prove that the proposed velocity and K estimators outperform existing estimators in the presence of shadowing and additive noise.
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ID Code:  15807 

Item Type:  QUT Thesis (PhD) 
Supervisor:  Boashash, Boualem & Senadji, Bouchra 
Keywords:  velocity estimation, mobile communication systems, wireless communication systems, instantaneous frequency, timefrequency signal processing, microcellular systems, multitier systems, Rice factor, Ricean Kfactor, multiplicative noise, handover, handoff, firstorder moment, bias, variance, estimation, CramerRao bounds 
Department:  Built Environment and Engineering 
Institution:  Queensland University of Technology 
Copyright Owner:  Copyright Ghasem Azemi 
Deposited On:  03 Dec 2008 03:49 
Last Modified:  28 Oct 2011 19:39 
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