We describe a method for Maximum Likelihood (ML) parameter estimation corrupted by additive white Gaussian noise. The ML cost function is maximized over the constraint that the detected data vector lie on the sphere. The results are compared with MMSE and with [2]. Simulations results shows superior performance of our method comparing to both the methods.

This paper proposes a simple combining technique with arbitrary modulations for a cooperative relay scheme based on a Detect-and-Forward (DEF) relay protocol. Here we present Maximum Likelihood (ML) criterion detection at the destination which considers individual symbol error rate (SER) to facilitate the detection in noisy relay networks. In particular, our proposed algorithm is flexible to si...

In this paper we investigate the large-sample behavior of the maximum likelihood estimate (MLE) of the unknown parameter θ for processes following the model dξt = θf(t)ξt dt+ dBt where f : R → R is a continuous function with period, say P > 0, and which is observed through continuous time interval [0, T ] as T → ∞. Here the periodic function f(·) is assumed known. We establish the consistency o...

the performance of many traffic control strategies depends on how much the traffic flow models are accurately calibrated. one of the most applicable traffic flow model in traffic control and management is lwr or metanet model. practically, key parameters in lwr model, including free flow speed and critical density, are parameterized using flow and speed measurements gathered by inductive loop d...