Code-aided ML joint synchronization and channel estimation for downlink MC-CDMA

In this paper, we present a novel code-aided joint synchronization and channel estimation algorithm for downlink multicarrier code-division multiple access. The expectation-maximization algorithm is used to locate the maximum-likelihood estimate of the channel impulse response, propagation delay, and carrier frequency offset. The estimator accepts soft information from the decoder in the form of a posteriori probabilities of the coded symbols, and can be interpreted as performing joint estimation and data detection. The performance of the proposed algorithm is verified through computer simulations. Impressive performance gains are visible as compared with a conventional data-aided estimation scheme.