Campus Units

Electrical and Computer Engineering

Document Type

Article

Publication Version

Accepted Manuscript

Publication Date

8-2005

Journal or Book Title

IEEE Transactions on Signal Processing

Volume

53

Issue

8

First Page

2942

Last Page

2948

DOI

10.1109/TSP.2005.850380

Abstract

We present a sequential Bayesian method for dynamic estimation and prediction of local mean (shadow) powers from instantaneous signal powers in composite fading-shadowing wireless communication channels. We adopt a Nakagami-m fading model for the instantaneous signal powers and a first-order autoregressive [AR(1)] model for the shadow process in decibels. The proposed dynamic method approximates predictive shadow-power densities using a Gaussian distribution. We also derive Crame/spl acute/r-Rao bounds (CRBs) for stationary lognormal shadow powers and develop methods for estimating the AR model parameters. Numerical simulations demonstrate the performance of the proposed methods.

Comments

This is a manuscript of an article from IEEE Transactions on Signal Processing 53 (2005): 2942, doi:10.1109/TSP.2005.850380. Posted with permission.

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

Language

en

File Format

application/pdf

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