Identification of Impulsive Interference Channels
Abstract
In this work, the problem of optimum and near-optimum identification of the parameters of the Middleton Class A impulsive interference model is considered. In particular, under the assumption of the availability of a set of independent samples from the Class A envelope distribution, the problems of basic batch estimation of the Class A parameters, recursive identification of the parameters, and efficient estimation of the parameters for small sample sizes, are investigated. Within the context of basic batch estimation, several estimators of the parameters are proposed and their asymptotic performances explored. From this analysis, estimates based on the method of moments are seen to be consistent and computationally desirable but highly inefficient, whereas more efficient likelihood-based estimators are seen to be computationally unwieldy. However, an estimator that initiates likelihood iteration with the method-of-moments estimates is seen to overcome these difficulties in its asymptotic performance. Unfortunately, simulation of this third estimator for moderate sample sizes reveals poor performance under these conditions. To overcome this lack of moderate-sample-size efficiency, a similar estimator that initiates likelihood iteration with physically motivated (but nonoptimal) estimates is also proposed. Simulation of this latter estimator for moderate sample sizes indicates that near-optimal performance is obtained by this technique. Within the context of recursive estimation, a recursive decision- directed estimator for on-line identification of the parameters of the Class A model is proposed.
Document Details
- Document Type
- Technical Report
- Publication Date
- Jul 01, 1989
- Accession Number
- ADA213154
Entities
People
- Serena M. Zabin
Organizations
- University of Illinois Urbana–Champaign