Camera-Guided Small-Cell Base Station Control for Dynamic Demand
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Solution Overview
Problem
The challenge in 5G/B5G/6G systems is the need for more base stations to achieve macrocell coverage, leading to increased power consumption and processing demands due to higher carrier frequencies and smaller coverage areas, with existing methods for controlling base station settings being inadequate.
Innovation Solution
A control system that utilizes cameras to detect and analyze objects in an image, extracting object information to predict communication demand, and adjusts base station settings such as turning RUs on/off, deleting or instantiating virtualized DUs, or scaling DUs based on predicted demand.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If more base stations are installed to achieve macrocell coverage in 5G/B5G/6G systems, then coverage area is improved, but power consumption increases
Solution Approach 1:
The base station operates in dynamic states (on-the-air/off-the-air) based on real-time communication demand. The control system continuously monitors object detection results and communication information to adjust the base station's operational state, transitioning between active and suspended modes to match actual usage requirements.
Solution Approach 2:
The system changes operational parameters (carrier frequency, RU on/off state, virtualized DU instantiation) based on detected communication demand. By adjusting these parameters dynamically rather than maintaining fixed settings, the base station can achieve macrocell coverage when needed while consuming less power during low-demand periods.
2Area of stationary object
If more base stations are installed to achieve macrocell coverage, then coverage area is improved, but processing amount increases
Solution Approach 1:
The system performs preliminary detection of objects and prediction of communication demand before actually activating base station resources. By anticipating communication needs based on object detection (such as detecting vehicles or pedestrians), the system can prepare appropriate settings in advance, avoiding reactive processing bursts and smoothing the computational load.
Solution Approach 2:
The base station autonomously adjusts its own operational state based on feedback from the control system. The determination unit uses object detection results and communication information to self-determine whether to activate or suspend the base station, reducing the need for external control processing and distributing the decision-making burden.
3Use of energy by stationary object
If base station settings are adjusted to reduce power consumption, then power usage is improved, but communication quality may deteriorate
Solution Approach 1:
The control system continuously monitors communication information (traffic volume, data type, connection status) and uses this feedback to adjust base station settings. This closed-loop control ensures that power-saving measures do not compromise communication quality, as the system can detect degradation and react by adjusting settings or activating additional resources when needed.
Solution Approach 2:
The base station operates in dynamic states (on-the-air/off-the-air) based on real-time communication demand. The control system continuously monitors object detection results and communication information to adjust the base station's operational state, transitioning between active and suspended modes to match actual usage requirements.
4Productivity
If virtualized DUs are instantiated to handle communication demand, then communication capacity is improved, but virtual resource consumption increases
Solution Approach 1:
Virtualized DUs are dynamically instantiated or deleted based on predicted communication demand. The system monitors object information and communication patterns, activating virtualized DU resources only when communication demand warrants it, and deactivating them when demand decreases, thus balancing service capacity with resource consumption.
Solution Approach 2:
The system performs preliminary detection of objects and prediction of communication demand before actually activating base station resources. By anticipating communication needs based on object detection (such as detecting vehicles or pedestrians), the system can prepare appropriate settings in advance, avoiding reactive processing bursts and smoothing the computational load.
Data Source
AI summary
An objective is to provide a control system, a control method, and a control program that can appropriately set a base station forming a small cell.A detection unit (811) detects a prescribed object in an image acquired by a camera. An extraction unit (812) extracts, from the image, object information relating to the detected object. A prediction unit (813) predicts, based on the object information, communication demand for a base station from a radio terminal that the detected object has. A determination unit (820) determines a setting of the base station based on the predicted communication demand. A control unit (830) controls the base station in accordance with the determined setting.


