An efficient propagation delay estimator for DS-CDMA signals

In this paper, we present an efficient algorithm for estimating the propagation delay of a known training sequence in an asynchronous direct-sequence code division multiple access (DS-CDMA) system. The algorithm is a large sample maximum likelihood (LSML) estimator that is derived by modeling the known training sequence as the desired signal and all other signals including the interfering signals and thermal noise as unknown colored Gaussian noise that are uncorrelated with the desired signal. LSML is asymptotically statistically efficient as the length of the training sequence goes to infinity. We shall show that LSML is robust against the near-far problem. The performance of the LSML estimator is compared with that of the MUSIC estimator via numerical examples and is shown to be better than that of the latter method in the sense of having lower root-mean-squared errors, lower computational complexity, and tolerating more users.