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Title: Dynamic directional channel model for indoor wireless communications
Author: Chong, Chia-Chin
Awarding Body: University of Edinburgh
Current Institution: University of Edinburgh
Date of Award: 2003
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The frequency-domain space alternating generalised expectation-maximisation (FD-SAGE) algorithm is proposed and used in conjunction with the serial interference cancellation (SIC) technique for joint detection and estimation of multipath channel parameters. The SIC technique demonstrates more stable performance than the parallel interference cancellation (PIC) technique used in the time-domain SAGE algorithm especially in a multipath rich environment. The performance of the FD-SAGE algorithm is demonstrated by using real indoor channel measurement data and its functionality is verified through comparison with unitary estimation of signal parameter via rotational invariance technique (ESPRIT) algorithm. The first channel model is derived from data collected during a static measurement campaign. This model incorporates both the clustering of MPCs and the correlation between the spatial and temporal domains. The clustering effect relies on two classes of parameters (intercluster and intracluster parameters) and two classes of power density spectra (PDS) (intercluster and intracluster PDS) which characterise the cluster and MPC, respectively. All parameters are described by empirical probability density (pdfs) derived from the measured data and the correlation properties are incorporated in two joint pdfs for cluster and MPC positions. Data analysis shows that the intercluster and intracluster PDS exhibit exponential and Laplacian functions in the delay and angular domains, respectively. The second channel model is derived based on data collected during a dynamic measurement campaign. This model incorporates both the spatial-temporal properties as well as the dynamic evolution of paths due to motion of the MT. An M-step, 4-state Markov channel model (MCM) is proposed in order to account for the correlation between the number of births and deaths and multiple births and deaths that can occur at any time instant. The power and spatio-temporal variation of paths within their lifespan are modelled by a low-pass-filter and a Gaussian distributed spatio-temporal vector, respectively. Due to the distinction in the birth-death statistics and the spatio-temporal dispersion and correlation properties for line-of-sight (LOS) and non-LOS (NLOS) scenarios, the model can be generalised, and parameterised by two sets of Markov parameters for these two scenarios.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available