Network Access Map Reduces UE Search Space
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Solution Overview
Problem
Current wireless network discovery and connection establishment methods are inefficient and power-consuming, especially in dense heterogeneous networks and multi-interface/multi-carrier band environments, due to blind physical layer searches, which struggle to detect small cells and manage network load effectively.
Innovation Solution
A location-based network discovery and connection establishment method that uses network access MAP information, transmitted to user equipment (UE), to reduce the search space and speed up network discovery by determining a specific search area based on the UE's geographic location, allowing for efficient downlink and uplink connection establishment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If blind physical layer search and measurement is used for network discovery, then network discovery can be performed without location information, but time consumption and battery power consumption increase significantly
Solution Approach 1:
The network pre-calculates and stores optimal search spaces for different geographic locations before the UE needs to discover networks. When UE provides its location, the corresponding pre-computed search space parameters are immediately retrieved and applied, eliminating the need for time-consuming blind searches at runtime.
Solution Approach 2:
Location information acts as an intermediary that bridges the UE and the network. By providing location as intermediate data, the system can determine appropriate search spaces without requiring the UE to perform exhaustive blind searches, thus reducing time consumption while maintaining network discovery capability.
2Ease of operation
If blind physical layer search and measurement is used for network discovery, then network discovery can be performed without location information, but battery power consumption increases significantly
Solution Approach 1:
The network pre-calculates and stores optimal search spaces for different geographic locations before the UE needs to discover networks. When UE provides its location, the corresponding pre-computed search space parameters are immediately retrieved and applied, eliminating the need for time-consuming blind searches at runtime.
Solution Approach 2:
Location information acts as an intermediary that bridges the UE and the network. By providing location as intermediate data, the system can determine appropriate search spaces without requiring the UE to perform exhaustive blind searches, thus reducing time consumption while maintaining network discovery capability.
3Ease of manufacture
If only PHY measurements are used for network discovery in dense heterogeneous networks, then the approach is simple to implement, but detection of small cells becomes difficult due to strong macro signals
Solution Approach 1:
The search space parameters are customized according to local geographic conditions and network deployment characteristics. For each location, the system determines appropriate frequency ranges, power levels, and measurement parameters that are optimized for that specific area, enabling small cells to be detected even in the presence of strong macro signals.
Solution Approach 2:
The system dynamically adjusts search space parameters such as frequency ranges, power thresholds, and measurement timing based on location information. This allows the UE to search in appropriate frequency bands and with appropriate sensitivity levels for detecting small cells in dense heterogeneous networks without being overwhelmed by macro cell signals.
4Adaptability or versatility
If only PHY measurements are used for network discovery in multi-interface/multi-carrier band networks, then the approach maintains compatibility with existing systems, but the search space becomes much larger making discovery difficult
Solution Approach 1:
The search space parameters are customized according to local geographic conditions and network deployment characteristics. For each location, the system determines appropriate frequency ranges, power levels, and measurement parameters that are optimized for that specific area, enabling small cells to be detected even in the presence of strong macro signals.
Solution Approach 2:
The system dynamically adjusts search space parameters such as frequency ranges, power thresholds, and measurement timing based on location information. This allows the UE to search in appropriate frequency bands and with appropriate sensitivity levels for detecting small cells in dense heterogeneous networks without being overwhelmed by macro cell signals.
Data Source
AI summary
Embodiments are provided for a location-based network discovery and connection establishment, which take advantage of location/positioning technology of user equipment (UE) and resolve issues above of the blind search approaches. The location-based network discovery and connection establishment schemes use UE location information and a network access MAP to speed up network discovery, and remove the need for continuous search and measurement by the UE. The schemes also reduce the search space. A wireless network access map (MAP) is provided to the UE. The UE uses the MAP information with UE current location information to reduce the search space and speed up network discovery and radio connection establishment with the network. Network operators can use this network access MAP to control the network access and manage the network load distribution. The network access MAP can be customized for each UE.