5G wireless channel multipath clustering calculation method based on KNN and SVM algorithms

Abstract

The invention provides a 5G wireless channel multipath clustering calculation method based on a K-nearest neighbor (KNN) algorithm and a support vector machine (SVM) algorithm. The 5G wireless channelmultipath clustering calculation method comprises the following steps: extracting small-scale parameters in each snapshot of a channel by using a high-resolution channel parameter extraction algorithm; extracting a part of multi-path components (MPC) by using a random sampling algorithm, and clustering thepart of MPC to be used for pre-clustering; calculating a multi-dimensional relative distanceof the extracted MPCs by using the KNN algorithm and carrying out pre-clustering; performing pattern recognition on the pre-clustering label of the known MPC by utilizing the SVM algorithm to obtaina new clustering label; and performing pattern recognition on all MPCs by utilizing clustering labels generated by the SVM algorithm to obtain a final clustering result. According to the method, the wireless communication channel data can be clustered more accurately, so that a more accurate channel model is established, and the method has very important application value for wireless channel linkand system-level performance simulation evaluation and network design under a 5G background.

Description

technical field [0001] The invention belongs to the technical field of wireless channel modeling, and in particular relates to a 5G wireless channel multipath clustering calculation method based on KNN and SVM algorithms. Background technique [0002] An accurate channel model is the basis for the design and research of wireless communication systems. In the field of wireless communication system research, the wireless channel model based on the cluster model is one of the most commonly used channel models. In 5G mmWave communication, the application of higher frequency bands and larger antenna arrays enables observation of higher-resolution multi-path components (Multi-Path Component, MPC) in the delay domain and angle domain, so in The clustering problem in 5G wireless channel research is more important. The clustering of MPC helps to reduce the number of parameters in a Multiple-Input Multiple-Output (MIMO) channel model, and the cluster structure is more flexible in cha...

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Problems solved by technology

When performing clustering, the SVM algorithm does not need to manually specify the number of data in the cluster, but requires a certain amount of labeled data for training

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