Channel knowledge map construction method based on expectation maximization algorithm

Abstract

The invention discloses a channel knowledge map construction method based on an expectation maximization algorithm. The method comprises the following steps: obtaining channel knowledge data of a local communication environment through any mode of offline ray tracing simulation, offline field measurement or online real-time measurement; carrying out statistical modeling on related channel knowledge according to expert knowledge, estimating K-class parameters of a mixed statistical model by using an EM algorithm, and constructing a channel knowledge map reflecting a local signal propagation environment; and when a user needs to communicate, obtaining real-time position information through GPS, Beidou, cellular positioning, laser radar and self-sensor positioning modes, and obtaining channel knowledge of a target position by using the previously constructed channel knowledge map and a mode based on inverse distance weighting. Therefore, the method is used for environment perception adaptive communication. According to the invention, the problems of low accuracy, large data storage capacity demand and high training complexity of a channel prediction method based on a pure model or pure data are solved, so that the cost for acquiring real-time channel state information is reduced.

Description

technical field [0001] The invention belongs to the technical field of the sixth generation communication, and in particular relates to a channel knowledge map construction method based on an expectation maximization algorithm. Background technique [0002] With the development of the sixth generation (6G) mobile communication technology research, the realization of ultra-wide coverage, ultra-large-scale links, ultra-high capacity, and extremely low-latency communication has become the focus of attention. Accurate prediction and estimation of wireless channels is the cornerstone of mobile communication network research, and is crucial to the design, analysis and optimization of wireless communication networks. For the 6G communication facing 2030, with the further increase of channel dimension and the huge overhead required for channel training, the development of next-generation communication technology is facing great challenges. However, due to the complexity of the actu...

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Problems solved by technology

[0005] The purpose of the present invention is to provide a channel knowledge map construction method based on the expectation maximization algorithm to solve the technical problem that there is an urgent need for a channel knowledge map construction method that can combine environmental awareness, low storage capacity overhead, accurate prediction, and wide applicability

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