Parameter Estimation for Middleton Class A Interference Processes

The problem of estimating the parameters of the Middleton Class A interference model is considered. On the assumption of the availability of a set of independent samples from a Class A envelope distribution, the asymptotic performance of several estimation procedures is 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 practical sample sizes reveals poor performance under these conditions. To overcome this lack of small-sample efficiency, a similar estimator that initiates likelihood iteration with physically motivated (but nonoptimal) estimates is also proposed. Simulation of this latter estimator for practical sample sizes indicates that near-optimal performance is attained by this technique.