Antenna monomer space coverage scheduling method and system based on compound eye bionic structure

By dividing the antenna radiation space into sub-sectors and configuring biomimetic sub-coverage units, and using a communication neural network for dynamic scheduling, the problem of insufficient resource allocation in existing antenna scheduling methods is solved, and efficient and flexible communication resource management is achieved.

CN122054343APending Publication Date: 2026-05-15ZHUHAI QIANHONG ZHIJIN TECH CO LTD
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Patent Information

Application Number
CN202610280841.5
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2026-03-09
Publication Date
2026-05-15

AI Technical Summary

Technical Problem

Existing antenna scheduling methods lack dynamic response to real-time communication needs and interference, resulting in the inability to optimize resource allocation in a timely manner and affecting overall communication quality.

Method used

The antenna radiation space is divided into N spatial sub-sectors, and N bionic sub-coverage units are configured. Distributed communication scene perception is performed through a communication neural network. Dual-dimensional quantization and dynamic weighted priority calculation are carried out to generate antenna control commands, thereby realizing adaptive collaborative scheduling and closed-loop update.

Benefits of technology

It enables refined radiation pattern control for each region, improves the efficiency of space resource utilization and the flexibility of communication resources, ensures adaptation to different communication needs in dynamic environments, and enhances the system's response speed and communication quality.

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Abstract

The invention provides an antenna monomer space coverage scheduling method and system based on a compound eye bionic structure, and relates to the technical field of antenna engineering, and the method comprises the steps: dividing an antenna radiation space into N space sub-sectors, and configuring N bionic sub-coverage units; carrying out distributed communication scene perception to obtain N pieces of communication scene information; performing two-dimensional quantization to obtain N space demand intensity values and N interference risk level values; performing dynamic weighting priority calculation to obtain a scheduling priority sequence; carrying out self-adaptive cooperative scheduling, and generating N antenna control instructions; and after issuing, sensing feedback based on the communication scene, and executing sub-sector-level closed-loop updating. According to the method and the device, the technical problems that in antenna scheduling in the prior art, a scheduling strategy is often carried out based on a fixed rule or a preset parameter, dynamic response to real-time communication requirements and interference conditions is lacked, resources cannot be optimally allocated in time, and the overall communication quality is influenced are solved.
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