Wireless communication link estimation method facing high-speed railway linear community

Abstract

The invention discloses a wireless communication link estimation method facing a high-speed railway linear community, and belongs to the technical field of wireless mobile communication. The method comprises the following steps: 1) a set of classification standard aiming at a high-speed railway characteristic spreading environment is put forward; 2) modeling is performed on large-scale path loss and shadow fading under various scenes, and a set of standardized spreading model library facing a high-speed railway is established; and 3) a coverage prediction method facing the railway linear community is put forward. The coverage range of the high-speed railway community is more accurately predicted under the premise of being without preliminary measurement so that a network arrangement scheme of the high-speed railway is optimized, base station spacing distance among communities is reasonably arranged and thus investment in high-speed railway wireless communication infrastructure is greatly reduced.

Description

technical field [0001] The invention belongs to the technical field of wireless mobile communication, and in particular relates to a wireless communication link estimation method for linear cells of high-speed railways. Background technique [0002] In the high-speed railway mobile communication system, the setting and planning of cell base stations mainly depend on the attenuation of wireless signals in the characteristic railway environment. As the distance increases, the electromagnetic wave will suffer from the absorption loss of the electrolyte, the occlusion loss of the ground obstacle, and the coherence and cancellation of the signal caused by the back and scattered waves during the transmission of the electromagnetic wave in the free space. These effects greatly affect the strength of the radio channel at the receiver. If the wireless signal strength at the receiving end is lower than the threshold level of the system, there will be a call drop between the train and...

AI Technical Summary

Problems solved by technology

Among them, the Hata model can only predict three types of scenarios: urban, suburban, and rural, and cannot cover scenarios such as viaducts, road cuttings, rivers, and stations that are often involved in high-speed railway wireless communications.

When using the wireless link estimation based on the Hata model, its prediction effect often has a large error with the channel test in the railway characteristic environment

The traditional public network is mostly based on a cellular network structure, which assumes that the cell coverage area is a circular surface, while the cell in railway wireless communication is a linear cell, and the traditional cell coverage probability prediction method will This leads to the underestimation of the coverage probability, and it is impossible to reasonably predict the changes of the railway wireless link.

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