User Scheduling and Simulated Beam Selection Optimization Method Based on Machine Learning

An analog beam and machine learning technology, applied in the field of wireless communication, can solve the problems of large scheduling scale, NP difficulty, and high computational complexity, and achieve the effects of high compatibility, improved classification accuracy, and high prediction accuracy.
CN113746510BActive Publication Date: 2022-05-24南方电网互联网服务有限公司
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
南方电网互联网服务有限公司
Publication Date
2022-05-24

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Abstract

The invention discloses a user scheduling and simulation beam selection optimization method based on machine learning. The method includes the following steps: obtaining each user channel feature vector; simulation beam matching: sequentially inputting each user channel feature vector to the beam prediction model Determine the analog beam, use multiple beam classifiers to divide the downlink channel between the base station and the selected user into multiple different beam classes, use the hyperplane to predict the channel class and select the best analog beam for each user; after After matching the analog beams, it is judged whether all users in the user set have been matched. When all users are matched, channel scheduling is performed according to the analog beam scheduling set, where the analog beam scheduling set is the analog beam set corresponding to the output user set. The invention reduces the computing power required by the applicable large-scale system, has high compatibility, reduces the cost of communication system construction, and reduces the time delay of user matching channels in the case of multiple users.
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Description

technical field

[0001] The present invention relates to the technical field of wireless communication, in particular to a method for optimizing user scheduling and analog beam selection based on machine learning. Background technique

[0002] Millimeter-wave (mmWave) communication technology and massive multiple-input multiple-output (MIMO) systems are key technologies in fifth-generation (5G) mobile communication systems to cope with the explosive growth of data services. For massive MIMO-mmWave systems, the traditional all-digital beamforming method is almost inapplicable in practice, because in all-digital beamforming, each antenna is equipped with a radio frequency (RF) chain, and each RF chain occupies a Dedicated baseband processor, so all-digital beamforming makes the system complexity and power consumption unbearable when the number of antennas is large. Hybrid beamforming, which divides beamforming into a low-dimensional digital part and an RF analog part, is a low...

Claims

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