In this paper, two different filter structures for smart antennas based on a convex combination of independent transversal adaptive sub-filters are analyzed. The first structure combines the least-mean-squares (lms) a...
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ISBN:
(纸本)9781509037940
In this paper, two different filter structures for smart antennas based on a convex combination of independent transversal adaptive sub-filters are analyzed. The first structure combines the least-mean-squares (lms) and the augmented complex least-mean-squares (AClms) algorithms, whereas the second one uses the recursive least-squares (RLS) and the complex dual least-mean-squares (cdu-lms) algorithms. The individual sub-filters are independently adapted using their own error signals, while the whole smart system is adapted by means of a convex stochastic gradient algorithm that generates an third independent error signal. The number of iterations required to reach convergence and the effects of the control parameter tau on the learning curve of the whole structure are studied. According to the simulation, these hybrid smart structures turned out to be more robust than a smart antenna that uses an unique adaptive filter. In general, both hybrid smart beamformers show to have a better filtering capacity than the standard lms and RLS smart antenna systems. General equations for the overall output and the radiation pattern have been developed for both variations.
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