Distributed transmit beamforming via feedback-based inter-cluster synchronization

This paper focuses on the problem of achieving optimal transmit beamforming for a collection of wireless sensors. The objective is to design distributed algorithms running on each sensor (each carrying an antenna) such that the signals from all sensors combine constructively at the receiver end and thus, the received power is increased. Towards this goal, we propose two algorithms that are applicable to two types of sensor setups: Taking Turn Distributed Beamforming (TT-DB) for sensors with partial global knowledge and Random Grouping Distributed Beamforming (RG-DB) for sensors with no global knowledge. Both algorithms are iterative whereby each sensor adjusts its phase offset without directly communicating with each other. In each iteration, either one sensor or a subset of sensors are selected and then transmit the signals that are carefully crafted based on the SNR feedback from the receiver end. We have proved that guided by either algorithm, the signals from all sensor nodes converge to perfect phase coherence asymptotically, and our simulation results have shown that the convergence steps of both algorithms are linear with respect to the number of sensor nodes in the group.