Joint TDD Pattern Adaptation for Inter-Cell Interference Control
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Solution Overview
Problem
In dynamic TDD networks, the flexibility of TDD patterns leads to increased inter-cell interference, which threatens to increase latency and degrade throughput, particularly in mission-critical applications and industrial IoT where quality of service requirements are stringent.
Innovation Solution
Jointly adapt TDD patterns across cells based on combined performance metrics such as interference, throughput, and latency, using nested closed loops to decouple the timing of TDD pattern adaptation from communication device scheduling, thereby mitigating inter-cell interference while maintaining flexibility and autonomy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If dynamic TDD patterns are independently selected for use by different cells, then flexibility to handle varying traffic conditions is improved, but inter-cell interference increases
Solution Approach 1:
The patent implements a feedback mechanism where cells exchange TDD pattern information and performance metrics with neighboring cells. This feedback loop enables cells to adjust their TDD patterns based on real-time interference conditions and traffic demands, resolving the contradiction by allowing flexibility while mitigating interference through continuous monitoring and adaptation.
Solution Approach 2:
The patent introduces dynamic TDD pattern selection where cells can switch between different TDD patterns based on instantaneous traffic conditions. The system dynamically adjusts the uplink-downlink subframe configuration in each cell independently while considering neighboring cell conditions, enabling flexibility without fixed harmonization constraints.
2Object-affected harmful factors
If TDD patterns are jointly adapted across cells, then inter-cell interference is reduced, but system complexity increases
Solution Approach 1:
The patent segments the TDD pattern adaptation process into two distinct loops: an outer loop for TDD pattern adaptation and an inner loop for scheduling. This segmentation allows each loop to operate independently with its own timing and optimization criteria, reducing the complexity of jointly optimizing both functions simultaneously while still achieving interference reduction through coordinated pattern adaptation.
Solution Approach 2:
The patent introduces a hierarchical structure with nested loops, adding a temporal dimension to the optimization process. The outer loop operates at a coarser timescale for pattern adaptation, while the inner loop operates at a finer timescale for scheduling, effectively managing complexity through multi-scale optimization.
3Speed
If TDD patterns are frequently adapted, then responsiveness to traffic changes is improved, but signaling overhead increases
Solution Approach 1:
The patent implements dynamic adaptation timing where the frequency of TDD pattern changes is adjusted based on traffic conditions and interference levels. The system can respond quickly to significant changes while maintaining stability during normal conditions, optimizing the balance between responsiveness and signaling overhead through condition-based triggering.
Solution Approach 2:
The patent employs periodic evaluation of TDD pattern performance against predefined thresholds. Rather than continuous adaptation, the system periodically assesses whether traffic conditions have changed sufficiently to warrant pattern changes, reducing unnecessary signaling while maintaining responsiveness to meaningful variations.
Data Source
AI summary
Network equipment (20) in a communication network (10) jointly adapts time division duplexing, TDD, patterns of 2024/022598 respective cells (16) in the communication network (10), based on performance (40) of the TDD patterns (30) in combination. Based on the adapted TDD patterns (30), the network equipment (20) jointly schedules communication devices (11) served by the cells (16). In some embodiments, joint TDD pattern adaptation is performed in an outer closed loop whereas the joint scheduling is performed in an inner closed loop, e.g., that operates on a faster timescale than the outer closed loop.