Smart Antenna Selection Method and Access Point

Abstract

The invention provides a method for selecting an intelligent antenna and an access point. The method for selecting the intelligent antenna comprises the steps that (1) the AP determines a first station from stations, the value of the communication quality of the first STA is smaller than a preset quality threshold value, and the flow requirement of the first STA is higher than a preset flow requirement; (2) the AP sends an active training message to the first STA in the directions of antennas of an antenna array in a training period of the first STA, and obtains a training result which corresponds to the active training message; (3) the AP selects an optimal antenna from the antenna array according to the training result; (4) the AP uses the optimal antenna to send a user message to the first STA. According to the method for selecting the intelligent antenna, due to the facts that the AP sends the active training message to the first STA which is poor in communication quality but has a certain need for flow, and increases user flow by sending the active training message, the AP helps the first STA to select the optimal antenna as soon as possible.

Description

technical field [0001] The invention relates to communication technology, in particular to a method for selecting an intelligent antenna and an access point. Background technique [0002] Traditional antennas have the disadvantages of large coverage angles but small coverage areas. With the emergence of smart antennas, different antenna array combinations can be dynamically selected, which can not only achieve full coverage of all angles, but also obtain greater coverage at each angle. scope. When the access point (AccessPoint, referred to as AP) needs to select the most suitable antenna array for the station (STATION, referred to as STA), the AP can send messages to the antenna array in different directions, and then select the optimal antenna array through a series of judgment strategies. Antenna array to ensure the transmission quality as much as possible. [0003] In the prior art, the selection of the antenna array depends on the normal user traffic, and the training ...

AI Technical Summary

Problems solved by technology

However, the existing technology cannot distinguish whether the user's traffic is small because the user's own traffic demand is small, or the rate is low due to the harsh environment, which causes the traffic per unit time to be small.

For STAs with low rate due to the harsh environment and small traffic per unit time, it is impossible to select the optimal antenna array for a long time

At the same time, due to the shared nature of the wireless network, in the integrated network, if there are individual STAs with poor initial communication quality, it will inevitably affect the normal communication of other STAs. During the smart antenna training process, even if individual STAs with better communication quality The STA quickly selects the optimal antenna array. If some STAs are unable to select the optimal antenna array for a long time due to the poor communication environment of some STAs, the communication quality of the entire network will be severely affected in terms of air interface utilization. Large impact, and the training time is long, the accuracy of the training may also decrease due to factors such as changes in the STA position

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