3DMIMO channel modeling method

Abstract

The invention relates to a 3D MIMO channel modeling method. The method includes the following steps that: (1) simulated scenes and network layout are determined, large-scale parameters are calculated according to the scenes and calculated correlations; (2) small-scale parameters are generated sequentially based on the large-scale parameters, a probability density function and the scenes; (3) a channel coefficient is calculated; (4) the small-scale parameters are updated according to a calculation result, and a drift model is built; and (5) time evolution is carried out according to the drift model, and then, modeling is carried out. According to the 3D MIMO channel modeling method of the invention, short-term time evolution of the channel coefficient is realized through updating time delay, a departure angle, an arrival angle, polarization, shadow fading and a K factor; smooth transition between adjacent channel segments is supported; a visual-range scene and a non-visual-range scene are simulated jointly by a common framework structure, and therefore, the complexity of a model can be reduced, and multi-unit scenes can be configured freely; and an algorithm of position graph generation is expanded, and diagonal angle movement directions are considered, and smoother output is created.

Description

technical field [0001] The invention belongs to the field of wireless communication, and in particular relates to a method for modeling 3DMIMO channels. Background technique [0002] The core advantage of MIMO technology lies in the effective use of space resources. The multipath effect, which was originally a shortcoming in wireless communication, has become a favorable factor for improving capacity in MIMO systems. The isolation between multiple antennas in the MIMO channel makes the large capacity of the system possible. If the channel correlation is low, the MIMO channel can be divided into multiple parallel sub-channels, and each sub-channel is equivalent to a traditional single-input single-channel Out of the wireless communication channel. For a completely uncorrelated MIMO channel, the multiple of its capacity improvement is the number of antennas. It can be seen that the capacity gain largely depends on whether the transmission environment has rich multipath facto...

AI Technical Summary

Problems solved by technology

The propagation of electromagnetic waves is affected by many factors such as antenna parameters, carrier frequency, user and base station locations, moving speed, and scatterer distribution, which makes wireless channels very unpredictable, thus increasing the complexity of channel modeling degree and difficulty

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