Adaptive Beamforming Based on Subspace Theory in Cognitive Networks

In this paper, a two-terminal cognitive network coexists in underlay way with a primary network, which is comprised of two primary radios who takes turn to send signals to each other in time division duplex (TDD) mode. In order to alleviate the interference to receivers in primary network, adaptive beamforming algorithm is proposed based on subspace theory, which can adaptively adjust the direction of beam to maximize the capacity of cognitive link. If the channel between cognitive transmitter and primary receiver is completely known to cognitive transmitter, cognitive transmission produces completely no interference to primary receiver. If this assumption can´t be guaranteed, this will inevitably introduce interference to primary receiver. However, we can keep the interference at primary receiver below the predefined interference temperature. Finally, simulation is conducted and justifies its feasibility.