An adaptive beamformer is a system that performs adaptive spatial signal processing with an array of transmitters or receivers. The signals are combined in a manner which increases the signal strength to/from a chosen direction. Abstract In recent years, adaptive beamformers have been researched more extens- ively, to be able to use it in the application of medical ultrasound imaging. The adaptive beamformers can provide a higher resolution and better con- trasts in the resulting images than non-adaptive, and most commonly used, delay-and-sum beamformer.
Subsequently, the thesis considers max-min fair transmit beamforming for single group multicast networks (which is NP-hard in general) and introduces a new class of adaptive beamforming algorithms that features guaranteed convergence and state-of-the-art performance at low complexity, when perfect CSI is available at the Tx.
Beamforming Overview Beamforming is the spatial equivalent of frequency filtering and can be grouped into two classes: data independent (conventional) and data-dependent (adaptive). All beamformers are designed to emphasize signals coming from some directions and suppress signals and noise arriving from other directions.