Beam resource allocation methods, devices, network equipment, and readable storage media

CN117500049BActive Publication Date: 2026-05-26BEIJING UNIV OF POSTS & TELECOMM
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
BEIJING UNIV OF POSTS & TELECOMM
Filing Date
2023-10-20
Publication Date
2026-05-26

AI Technical Summary

Technical Problem

In the context of connected autonomous vehicles, existing technologies often fail to meet the diverse business needs of users due to the limitations of traditional single-network architectures. This leads to issues such as inter-beam interference when the number of vehicle users is small and the inability to guarantee service effectiveness when the number of users is large. In particular, the impact of multi-beam interference on business requirements and overall network performance is not considered in millimeter-wave resource allocation.

Method used

By determining whether the vehicle belongs to a low-vehicle or high-vehicle vehicle network scenario, a beam resource allocation method is adopted, including clustering, beam resource allocation and interference analysis. The extended Kalman filter algorithm and non-orthogonal multiple access (NOMA) technology are used to optimize beam resource allocation to reduce interference and improve network performance.

Benefits of technology

It effectively solves the problems of user-differentiated service needs and beam interference under traditional network architecture, ensures the effectiveness of services in multi-user scenarios, improves the transmission rate and perception mutual information of communication services, reduces perception blind spots, and improves the overall network performance.

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Abstract

This application provides a beam resource allocation method, apparatus, network device, and readable storage medium. The method includes: determining the vehicle-to-everything (V2X) scenario to which a vehicle belongs; the V2X scenario includes a few-vehicle scenario and a many-vehicle scenario; wherein, a scenario where the beams supported by the base station satisfy one-to-one vehicle service is the few-vehicle scenario; and a scenario where the beams supported by the base station do not satisfy one-to-one vehicle service is the many-vehicle scenario; and allocating beam resources to the vehicle according to the V2X scenario. The solution of this application can flexibly allocate beam resources to vehicles according to few-vehicle and many-vehicle scenarios, avoiding the problem of traditional single-network architectures failing to meet the diverse service needs of users. It can also solve the problem of inter-beam interference caused by beam power leakage when the number of users is small, and ensure the effectiveness of multi-user service when the number of users is large.
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