Adaptive Data Session Re-establishment in Mobile Terminals
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
In communication systems, mobile terminals face challenges in re-establishing data sessions due to unstable radio links and unprepared base stations, leading to session drops, as they often attempt re-establishment with strong yet unprepared cells, resulting in non-continuous service.
Innovation Solution
The terminal operates in a learning phase to collect success statistics and transition to an adaptive phase, selecting re-establishment modes based on these statistics to choose the most suitable base station for re-establishment, reducing the likelihood of attempting re-establishment with unprepared cells.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If the terminal attempts re-establishment with the strongest neighbor base station, then the re-establishment speed is improved, but the reliability of re-establishment deteriorates because the target cell may not be prepared for re-establishment
Solution Approach 1:
The network performs preliminary preparation of target cells for re-establishment before the terminal actually needs to re-establish. The base station pre-identifies and prepares suitable neighbor cells, storing their information in advance so that when re-establishment is needed, the terminal can quickly connect to a pre-prepared cell rather than searching for an unprepared strong signal cell
Solution Approach 2:
The terminal provides feedback to the network about re-establishment outcomes and cell conditions. The network uses this feedback to continuously update and optimize which cells are marked as prepared for re-establishment, improving the accuracy of target cell selection over time and increasing re-establishment success rates
2Reliability
If the terminal collects and analyzes success statistics of multiple re-establishment modes, then the reliability of re-establishment is improved, but the complexity of the terminal increases due to learning and adaptive phases
Solution Approach 1:
The terminal implements dynamic operation modes that can switch between learning phase and adaptive phase. During learning phase, the terminal collects statistics about different re-establishment modes. During adaptive phase, it uses the learned information to select optimal modes. This dynamic adaptation allows the terminal to improve reliability while managing complexity through structured phase transitions rather than continuous complex decision-making
Solution Approach 2:
The terminal changes its operational parameters based on the phase it is in. In learning phase, it records success rates of various re-establishment modes with different criteria. In adaptive phase, it uses these recorded parameters to make informed decisions. This parameter-based approach simplifies the complexity by using predefined criteria and statistics rather than complex real-time analysis
Data Source
AI summary
A method includes, in a mobile communication terminal, holding a definition of multiple re-establishment modes, each re-establishment mode defining a respective criterion for selecting a base station with which to re-establish a failed data session. Success statistics of one or more of the re-establishment modes in a given geographical region are collected in the terminal. In response to a failure in a data session occurring while the terminal is in the given geographical region, a re-establishment mode is selected from among the multiple re-establishment modes based on the success statistics, and the data session is re-established using the selected re-establishment mode.