Belief propagation with Gaussian priors for pilot-assisted communication over fading ISI channels
IEEE Transactions on Wireless Communications
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This paper analyzes the asymptotic performance of maximum likelihood (ML) channel estimation algorithms in wideband code division multiple access (WCDMA) scenarios. We concentrate on systems with periodic spreading sequences (period larger than or equal to the symbol span) where the transmitted signal contains a code division multiplexed pilot for channel estimation. First, the asymptotic covariances of the training-only, semi-blind conditional maximum likelihood (CML) and semi-blind Gaussian maximum likelihood (GML) channel estimators are derived. Then, these formulas are further simplified assuming randomized spreading and training sequences under the approximation of high spreading, factors and high number of codes. The results provide a useful tool to describe the performance of the channel estimators as a function of basic system parameters such as number of codes, spreading factors, or traffic to training power ratio