Maximum-likelihood-based multipath channel estimation for code-division multiple-access systems

In this paper, the problem of estimating the channel parameters of a new us er in a multiuser code-division multiple-access (CDMA) communication system is addressed, It is assumed that the new user transmits training data over a slowly fading multipath channel, The proposed algorithm is based on maxi mum-likelihood estimation of the channel parameters. First, an asymptotic e xpression for the likelihood function of channel parameters is derived and a re-parametrization of this likelihood function is proposed. In this re-pa rametrization, the channel parameters are combined into a discrete time cha nnel filter of symbol period length. Then, expectation-maximization algorit hm and alternating projection algorithm-based techniques are considered to extract channel parameters from the estimated discrete channel filter, to m aximize the derived asymptotic likelihood function. The performance of the proposed algorithms is evaluated through simulation studies. In addition, t he proposed algorithms are compared to previously suggested subspace techni ques for multipath channel estimation.