Performance-improving techniques for wireless systems Public Deposited


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  • In this thesis, maximum likelihood Doppler frequency estimation and phase noise suppression algorithms for Orthogonal Frequency Division Multiplexing (OFDM) systems are presented. A novel handover decision algorithm for wireless systems, called predictive base station switching (PBSS), is also introduced. The maximum Doppler Frequency is the ratio of the speed of the mobile user and the carrier frequency. The Doppler frequency information of each mobile can be exploited to minimize the number of handover scenarios and to improve channel estimation. The estimation of this quantity in time-varying multipath channels is performed in this thesis by a frequency-domain approach that utilizes pilot subcarriers, which are commonly implemented in most practical OFDM systems. In the proposed estimator, the effect of the intercarrier interference (ICI) caused by the time-varying fading is taken into consideration with a proper model for accurate results. The Cramer-Rao bounds are also derived and simulation results are provided to quantify the performance of the algorithm. This thesis also presents a maximum likelihood approach exploiting the OFDM pilot subcarriers to suppress phase noise due to imperfect local oscillators. This algorithm does not require perfect channel equalization and is applicable for the two common types of oscillators: phase-locked and free-running oscillators. Furthermore, doubly-selective fading is considered rather than assuming time-invariant and/or flat fading channels. Finally, a new handover decision algorithm, PBSS, is presented. PBSS is designed for broadband wireless access (BWA) systems (where users can travel at vehicular speeds) that typically have small cell sizes due to high-data-rate transmission. High-mobility users of BWA systems usually need to perform frequent handovers, which degrades the overall network performance. PBSS uses mobile speed and direction information to reduce the number of handovers without degrading the received signal level. Simulation results show that PBSS performs better than algorithms solely based on information of signal strength and distance and has a comparable outage probability, even when the users move randomly or accurate direction and speed information is unavailable.
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