Dynamic Cell Assignment for RRU Coordination Sets
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Solution Overview
Problem
Current methods lack an efficient way to dynamically coordinate cells among different baseband processing units (BBUs) to optimize network performance and efficiency in radio access networks, particularly due to limitations in processing capacity and time constraints, which restrict the number of cells that can be assigned to a coordination set (C-Set).
Innovation Solution
A method using a greedy algorithm with cell score variables and evaluation scores to dynamically assign cells to C-Sets, optimizing network performance by considering load, front-haul capacity, and site density, and applying policy and optimization weights to modify cell scores, allowing for variable numbers of cells and C-Sets.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If cells are dynamically coordinated among different BBUs to optimize network performance, then network performance and UE throughput are improved, but processing capacity requirements and computational complexity increase
Solution Approach 1:
The patent segments the cell assignment problem into two distinct phases: a greedy assignment phase that provides initial coordination, and a local search optimization phase that refines the assignment. This segmentation allows the system to handle large-scale networks by breaking down the complex optimization problem into manageable stages, improving network performance without overwhelming processing capacity
Solution Approach 2:
The patent applies partial action by implementing local search optimization only for cells that can potentially improve their assignment, rather than exhaustively optimizing all cells. This selective approach maintains network performance benefits while reducing overall computational complexity and processing requirements
2Productivity
If the number of cells assigned to a C-Set is increased to improve coordination benefits, then interference suppression and UE throughput increase, but time/delay constraints between BBUs are violated
Solution Approach 1:
The patent implements periodic action through iterative local search optimization that systematically evaluates and refines cell assignments in discrete steps. The algorithm periodically checks and adjusts cell-to-C-Set assignments based on current network conditions, achieving improved UE throughput while maintaining compliance with time/delay constraints through controlled iteration
Solution Approach 2:
The patent applies dynamics by making the C-Set assignment flexible and adaptive rather than fixed. The system dynamically adjusts cell assignments based on changing network conditions, load distributions, and coordination benefits, allowing the number of cells per C-Set to vary optimally without violating time constraints
3Measurement precision
If a brute force optimization method is used to assign cells to C-Sets, then optimal assignment is achieved, but computational complexity becomes infeasible for large networks
Solution Approach 1:
The patent segments the optimization process into a greedy initial assignment phase followed by a targeted local search phase. This segmentation avoids the computational infeasibility of brute force methods while still achieving near-optimal cell assignments for large-scale networks by focusing computational effort only where improvements are possible
Solution Approach 2:
The patent changes the approach from exhaustive search to heuristic-based assignment with local optimization. By transforming the problem from finding the absolute optimal solution to finding a sufficiently good solution through greedy algorithms and local search, the system achieves feasible computational complexity while maintaining practical assignment quality
Data Source
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AI summary
An apparatus and method to perform dynamic assignment of a cell associated with a remote radio unit (RRU) to a coordination set ("C-Set") associated with at least one BBU to optimize the overall performance of a network. The method, is based on a greedy algorithm and uses (1) score variables, (2) cell score function, and variations thereof and (3) the evaluation scores, and variations thereof to determine C-Set assignments for an overall improvement of network performance. Preferably, the cell score function determines the cell score of cells between each other, taking for example into account overlap between border of cells, or else interference.