A weight optimization method for massive MIMO single cell

Abstract

The invention discloses a method for optimizing the weight of a Massive MIMO single cell, comprising the steps of: S1 acquiring data; S2 confirming the cell to be optimized: confirming the cell to be optimized according to the operator's KPI data and business requirements; S3 strengthening the learning output to adjust the weight : Combining the indicators of the KPI data of the community and the location distribution of the sampling points of the user, the candidate weight action combination is given, and the beam weight scheme is selected to carry out intensive learning and adjustment of the candidate weight, and output the adjusted weight; S4 Execution on the live network: The beam weight scheme selected in step S3 is implemented in the live network, and the data after feedback is collected; S5 determines whether to continue optimization: according to the collected feedback data, it is determined whether the optimization is completed, and if the optimization is completed, the optimization process of the cell is ended ; If not completed, then return to step S3, and loop steps S3~S5, until the optimization is completed, and save the Q-table of the community.

Description

Technical field [0001] The present invention relates to a wireless communication network technologies, and particularly to a single-cell weights Massive MIMO optimization method. Background technique [0002] With the introduction of a millimeter wave 5G, to address the limitations of the millimeter wave transmission distance is limited by the proposed use of Massive MIMO antenna technology, and to compensate for the problem of limited transmission distance 5G. 5G 2019, the first year of construction, a lot of Massive MIMO network, to solve the transmission distance is limited outside support for its ultra-high access rate is becoming increasingly apparent advantages, operators began using support ultra-high access rate of Massive MIMO in 4G network, to relieve hot spots and the growing traffic demand. [0003] With 5G promote the progress of construction, extensive use of 5G Massive MIMO base station network gradually, while 4GMassive MIMO base station also increased rapidly, re...

AI Technical Summary

Problems solved by technology

[0003] With the progress of 5G construction, a large number of 5G base stations using Massive MIMO are gradually entering the network. At the same time, 4G Massive MIMO base stations are also increasing rapidly, resulting in more complex 3 / 4 / 5G wireless environments and posing great challenges to RF (Radio Frequency) optimization.

[0004] Traditional RF adjustment is dominated by the manual experience of engineers, and it is impossible to quantitatively analyze and determine the optimal adjustment plan. There are problems such as low efficiency of repeated adjustments, insufficient consideration of regional impacts, poor comprehensiveness, single analysis data source, and difficulty in guaranteeing optimization results, etc.

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