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

The problem of estimating the channel parameters of a new user 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 maximum-likelihood estimation of the channel parameters. First, an asymptotic expression for the likelihood function of channel parameters is derived and a re-parametrization of this likelihood function is proposed. In this re-parametrization, the channel parameters are combined into a discrete time channel filter of symbol period length. Then, expectation-maximization algorithm and alternating projection algorithm-based techniques are considered to extract channel parameters from the estimated discrete channel filter, to maximize the derived asymptotic likelihood function. The performance of the proposed algorithms is evaluated through simulation studies. In addition, the proposed algorithms are compared to previously suggested subspace techniques for multipath channel estimation.