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UBC Theses and Dissertations

Parameter Estimation for Wireless Fading and Turbulence Channels Wang, Ning


In this thesis, we mainly investigate the parameter estimation problem for fading and atmospheric turbulence channel models for wireless communications. A generalized method of moments (GMM) estimation scheme is introduced to the estimation of Nakagami fading parameter. Our simulation results and asymptotic performance analysis reveal that this GMM framework achieves the best performance among all method of moments estimators based on the same moment conditions. Further improved performance can be achieved using additional moment conditions in the GMM. In the study of the maximum-likelihood (ML) based Nakagami m parameter estimators, we observe that a parameter \Delta, which is defined as the logarithmic ratio of the arithmetic mean to the geometric mean of the Nakagami-m fading power, can be used to assess the estimation performance of ML-based estimators analytically. For small sample size, the probability density function (PDF) of is derived by the moment generating function (MGF) method. For large sample size scenarios, we use a moment matching method to approximate the PDF of \Delta by a two-parameter Gamma PDF. This approximation is validated by the Kolmogorov-Smirnov (K-S) test as well as simulation results. When studying the Gamma-Gamma turbulence model for free-space optical (FSO) communication, an estimation scheme for the shape parameters of the Gamma-Gamma distribution is introduced based on the concept of fractional moments and convex optimization. A modified estimation scheme, which exploits the relationship between the Gamma-Gamma shape parameters in FSO communication, is also proposed. Simulation results show that this modified scheme can achieve satisfactory estimation performance over a wide range of turbulence conditions.

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