Article
Maximum likelihood estimation of statistical properties of composite gamma-lognormal fading channels
IEEE Transactions on Signal Processing
Document Type
Article
Disciplines
Publication Version
Accepted Manuscript
Publication Date
10-1-2004
DOI
10.1109/TSP.2004.834265
Abstract
We propose maximum likelihood (ML) methods for estimating the parameters of composite gamma-lognormal fading channels. Newton-Raphson and expectation-maximization (EM) algorithms are developed to compute the ML estimates of the mean and variance of the shadowing component, and the Nakagami-m parameter of the fading component. We also derive Crame/spl acute/r-Rao bounds (CRBs) for the unknown parameters. Numerical simulations demonstrate the performance of the proposed method.
Rights
Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Copyright Owner
IEEE
Copyright Date
2004
Language
en
File Format
application/pdf
Citation Information
Aleksandar Dogandžić and Jinghua Jin. "Maximum likelihood estimation of statistical properties of composite gamma-lognormal fading channels" IEEE Transactions on Signal Processing Vol. 52 Iss. 10 (2004) p. 2940 - 2945 Available at: http://works.bepress.com/aleksandar_dogandzic/50/
This is a manuscript of an article from IEEE Transactions on Signal Processing 52 (2004): 2940, doi:10.1109/TSP.2004.834265. Posted with permission.