Blind Maximum Likelihood Jade in Multipath Environement Using Importance Sampling

In this paper, we tackle the problem of joint angles and time delays estimation (JADE) in a non-data aided (NDA) scenario where the transmitted signal is unknown at the receiver. We do so by applying the maximum likelihood (ML) in order to obtain the best performance achievable. The importance sampling (IS) technique is used to reduce the multidimensionality of the maximization problem without recurring to an iterative option. Computer simulations show that the new ML IS solution approaches the DA techniques and the Cramér-Rao lower bound (CRLB) at medium and high SNR levels.