A Small Range Ergodic Beamforming Method Based on Binocular Vision Positioning

The increasing construction of 5G dense network creates the conditions for the application of Massive MIMO system. However, with the continuous expansion of business requirements, users put forward higher requirements for the number of antennas in MIMO system. With the increase of the number of antennas, the cost of traditional MIMO beamforming algorithm for channel detection and feedback will increase rapidly, which consumes more wire-less resources and greatly increases the computational burden of the system. The use of computer vision aids provides convenience for the beamforming method to track the target accurately under LOS condition. Combined with image tracking algorithm, the position of the target in each image frame can be calculated so that the angle information of LOS path and the best beam-forming scheme can be determined directly, which can reduce the cost and calculation of the system through wireless resource measurement and feed-back. As a result, the operation speed and accuracy of the system are improved. In this paper, a beamforming method based on binocular positioning is studied. Compared with the traditional method, this method can reduce the number of codeword searches and improve the channel capacity in high-density 5G network.