© 2016 IEEE. 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 τ 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.
|Original language||English (US)|
|State||Published - 23 Jan 2017|
|Event||2016 IEEE International Autumn Meeting on Power, Electronics and Computing, ROPEC 2016 - Ixtapa, Mexico|
Duration: 9 Nov 2016 → 11 Nov 2016
|Conference||2016 IEEE International Autumn Meeting on Power, Electronics and Computing, ROPEC 2016|
|Abbreviated title||ROPEC 2016|
|Period||9/11/16 → 11/11/16|