Telecommunication Service Node Closest User Terminal Search Method
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Solution Overview
Problem
Existing telecommunication network systems incur high costs and consume network capacity by transmitting numerous requests and messages to determine the closest user terminals to a point of interest, as they require location data from all potentially relevant users, leading to excessive resource usage.
Innovation Solution
A method that sets a search range with an upper limit and iteratively queries cells with the lowest minimum distance to a point of interest, adjusting the range based on found user terminals' distances, thereby reducing the number of user data requests and excluding cells further away, optimizing power and network resource usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If location data is requested from all potentially relevant users to determine the closest user terminal, then the accuracy of finding the closest user is improved, but the network resource usage and power consumption increase significantly
Solution Approach 1:
The network area is segmented into multiple cells, each with a calculated distance range to the point of interest. The system queries cells in order of increasing minimum distance, dividing the search space into manageable segments and stopping when the nth closest user is found, avoiding unnecessary queries in distant cells.
Solution Approach 2:
The system performs preliminary calculations of distance ranges for all cells before querying user locations. By pre-determining which cells could potentially contain the closest users and ordering them by proximity, the system avoids unnecessary location requests and reduces network overhead.
2Loss of information
If location data is requested from all potentially relevant users, then complete information is obtained, but the number of requests and messages transmitted in the network increases
Solution Approach 1:
The system performs partial action by querying only the necessary number of cells to find the nth closest user. Once n users are found, the search stops, even if other cells remain unqueryed. This partial approach maintains information completeness for the required result while reducing network traffic.
Solution Approach 2:
The system extracts only the essential information needed to solve the problem - location data from cells that could contain the closest users. By excluding data from distant cells that cannot contribute to finding the nearest users, the system reduces network messages while maintaining result accuracy.
3Reliability
If the search range is set without an upper limit, then all possible user terminals are considered, but the time and resources required to complete the search increase
Solution Approach 1:
The system performs preliminary ordering of cells by their minimum distance to the point of interest before conducting the actual user search. This pre-sorted arrangement enables the algorithm to systematically query cells from closest to farthest, ensuring that the nth closest user is found efficiently without unnecessary searches in distant cells.
Solution Approach 2:
The search range upper limit is dynamically adjusted during the search process. As users are found in closer cells, the effective search boundary moves outward only as needed. This dynamic adjustment allows the system to complete the search faster by adapting the search scope to the actual distribution of users.
Data Source
AI summary
Service node for a telecommunication network (15) and method for determining a group of n user terminals (21) which are closest to a point of interest (22). First, a search range with an upper limit (24) is set. Then in an iterative manner, a current search cell of the set of cells (1-10) is determined and the search cell is queried for user data. The user terminals (21) are added to a set of found user terminals, and if the set of found user terminals comprises n or more user terminals (21), the upper limit (24) of the search range is adjusted to the nth lowest distance. This is repeated until no further possible cell (1-10) can be determined. The set of criteria can be set and matched with obtained user data to find a closest user terminal (21) having a specific role.