Beamforming Techniques Analysis In3D Mimo

3D multiple input multiple output (MIMO) has become a hot spot in standardization study. While beamforming technique is core part of3D MIMO techniques, it has attracted more and more interesting with its dy-namic downtilt adjustment, improved system capacity and interference elimination. In this paper, we study beamforming techniques from differ-ent aspects, analyzing the elevation impact on channel, array and algo-rithm. The work can be categorized as three parts:First, we research minimum variance distortionless response(MVDR) in the3D scene. MVDR is a kind of classical algorithm, which obtains shaped weights by setting linear constraints in the direction of the desired signal and minimizing the output power. Analysis showed that MVDR’s performance declined sharp in the3D scene, because of the disturbance of noise eigenvalues in small sample length. Analysis also showed that an increase in the number of array elements have amplification of the dis-turbance. Therefore, we propose an improved method based on eigenva-lues, which can solute the problem in a better way. We proved the feasi-bility of the beam decomposition method from the horizontal and vertical dimensions in theoretical dimension, and laid the foundation for subse-quent research.Second, assessment about Eigenvalue Based Beamforming (EBB) algorithm based on the3D channel. Radio channel, as the cornerstone of communication technology research,is of great significance. EBB algo-rithm is the shaping algorithm that combined with channel most closely. In this paper, we illustrate the difference between3D and traditional2D channel model with the actual measurement results, and provide the basic steps of generating a3D channel mode. The correctness of3D channel model generation is simply verified by simulation. We evaluated the per-formance of EBB algorithm in the3D channel, which showed that EBB has a better performance in the3D channel than the2D channel.Third, a novel transmission scheme is proposed in this paper. The scheme combines beamforming, diversity and multiplexing. In order to distinguish the different spatial sub-stream, the transmit end constructs an uncorrelated equivalent channel by beamforming weights, and the re-ceiving end generates orthogonal beamforming using the network Butler. The original data stream is recovered finally by the matching algorithms which arranges the detect sequential reasonably. The program showed a better performance in the simulation. And the spatial filtering effect of the receiving end is very enlightening for the expansion to3D scene.These are the main content of the work and innovation of this article. Since the direction of the research is in the initial stages, these results may provide reference and basis in the following study of3D beamform-ing.