Method for lowest noise and signal threshold estimation method based on channel measurement and apparatus thereof

Abstract

The present invention discloses a method for estimating noise bottom and signal component threshold, and device thereof. The method according to the invention comprises the following steps: measuring the measuring point and the sub-measuring point thereof according to a preset measuring time interval to obtain the signal channel data of the measuring point and the sub-measuring point thereof; eliminating the largest and smallest signal channel data accounting a certain percentage in the signal channel data of the measuring pint and the sub-measuring point thereof; and estimating the noise bottom according to the residual signal channel data and estimating the threshold between the effective signal component and the noise component according to the noise bottom. The method according to the invention can make that the noise bottom and signal component obtained through calculation are more precise. The validity and reliability for subsequently extracting the characteristic parameter of the signal channel can be increased.

Description

technical field [0001] The invention relates to the field of wireless communication, in particular to a method and device for estimating noise floor and signal component threshold based on channel measurement. Background technique [0002] The development of mobile communication is changing with each passing day. From the first-generation cellular mobile communication system to the fourth-generation IMT-Advanced mobile communication system that has been extensively researched, the transmission rate and bandwidth of the system are constantly increasing. With the increase of bandwidth, the channel will show new characteristics in many aspects such as space-time correlation and frequency selectivity, which will bring new challenges to system design. Therefore, the study of wireless channel propagation characteristics is the premise and key to the study of future mobile communication technologies. [0003] It is the best way to understand the characteristics of the real channel...

AI Technical Summary

Problems solved by technology

This method will introduce a lot of noise when the signal-to-noise ratio is low, which will affect the accuracy of channel analysis; the latter is based on the noise floor and takes a constant upward as the threshold threshold. , will also introduce noise, which also affects the accuracy of channel analysis

[0006] The random change of channel noise will distort the received signal, and the space-time fading will make the extracted channel characteristic parameters fluctuate greatly

At present, the more commonly used method for measuring and extracting path loss and delay parameters is to conduct a measurement at the measurement point, which is easily affected by channel noise. Once there is impulse noise, it will have a great impact on the extraction of channel characteristic parameters. Even if multiple measurements are made to reduce the influence of noise, due to the influence of channel space fading, the extracted channel characteristic parameters will have large spatial fading and cannot reflect the real channel characteristics

For example, in the current method of extracting the Rice factor that is more commonly used, it is only extracted in time, and the influence of small-scale fading in space is not considered, which will make the extracted Rice factor more spatially volatile

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