GPS-Assisted Wireless Handover via Predictive Resource Allocation
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Solution Overview
Problem
Current wireless communication networks face challenges in seamless handovers and resource allocation due to the lack of integration with GPS navigation systems, leading to inefficiencies in quality of service (QoS) maintenance and power consumption.
Innovation Solution
The integration of GPS data into wireless network management systems and client devices to assist in handover decisions and resource allocation, using planned routes to enhance scheduling and selection of infrastructure stations, and leveraging expected QoS as a metric for route optimization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If GPS data is integrated into wireless network management systems to assist handover decisions, then handover efficiency and QoS maintenance improve, but device complexity and power consumption increase
Solution Approach 1:
The system divides handover management into two segments: GPS-based predictive handover initiation and traditional signal-quality-based handover execution. The GPS module independently determines when handover should be initiated based on location data and pre-configured cell geography, while the traditional wireless communication system continues to handle the actual handover execution based on signal quality measurements. This segmentation allows GPS to provide advance notice of upcoming handovers without completely replacing the existing handover decision-making architecture.
Solution Approach 2:
The system performs preliminary actions by using GPS location data to predict future handover events before they occur. The network system receives GPS coordinates, determines the mobile device's current and future locations, and proactively prepares for handover by identifying target cells in advance. This preliminary action allows the system to pre-configure handover parameters and allocate resources before the actual handover is needed, improving efficiency without adding complex real-time decision-making requirements.
2Use of energy by moving object
If GPS-based predictive handover is implemented, then power consumption is reduced by optimizing scanning operations, but device complexity increases
Solution Approach 1:
The system implements periodic scanning only during specific intervals when GPS-predicted handover events are anticipated. Instead of continuous scanning, the mobile device performs scanning operations periodically at locations where GPS data indicates a handover is likely to occur. This periodic action based on GPS-triggered events significantly reduces the overall scanning frequency and associated power consumption compared to traditional continuous or frequent periodic scanning approaches.
Solution Approach 2:
The mobile device's GPS module independently determines when handover events should be triggered based on its own location data and pre-configured cell geography information stored locally. The device uses its own GPS coordinates to autonomously identify when it is approaching cell boundaries or entering new coverage areas, eliminating the need for continuous network-assisted location tracking and reducing the computational burden on both the device and network infrastructure.
Data Source
Figure 1A~1B
Figure 2~3A
Figure 3B~4
AI summary
Embodiments disclosed herein include methods, apparatus, and system architectures for using GPS within wireless networks to assist with wireless network management including handovers and data transfers, along with navigation decisions within heterogeneous networks.