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High resolution reduced complexity synchronization in spread spectrum systems

The estimation of several unknown channel amplitudes and taps in a multipath environment is an important problem when designing receivers both for communication and navigation purposes. A popular approach for these estimation problems are methods solving the maximum likelihood (ML) problem for each dimension separately like the expectation maximization (EM) approach and the more sophisticated space alternating generalized expectation maximization (SAGE) algorithm. However, both methods require a high computational complexity when used in spread spectrum systems due to long spreading sequences. Therefore, we apply methods for decreasing the computational complexity before executing the iterative estimation algorithms. The respective performance is assessed by means of computer simulations for a UMTS scenario which show a negligible degradation in estimation accuracy despite a substantial complexity reduction.