Loop learning algorithm for distributed beamforming based on one bit feedback

摘要

Distributed beamforming is an attractive topic in wireless communication networks. This paper focuses on improving both the convergence speed and the precision level for distributed transmitting beamforming based one bit feedback scheme. A loop learning algorithm is proposed where three states are contained: random perturbation state, reinforcement learning state, optimization decision state. A loop starts with random perturbation state, and then proceeds to the next state according to the information of previous states. Each transmitter adjusts its phase by repeating the loop, so that the carrier phase alignment can be achieved at the receiver when multiple transmitters cooperatively send a common message signal. The proposed algorithm has advantages over other one bit feedback algorithms for convergence performance. The effectiveness of the algorithm are verified by the provided simulation results.