Distributed Resource Management in Heterogeneous Wireless Networks
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Solution Overview
Problem
Current resource management systems in heterogeneous wireless networks with high backhaul latency struggle to optimize activation fractions of transmission points effectively, leading to inefficiencies in user association and spectral efficiency.
Innovation Solution
A distributed resource management method that operates on two time-scales, using a Greedy Stage and Local Search Stage to determine user association and activation fractions, considering average single-user rates and fairness factors, and incorporating an auxiliary function method for efficient activation fraction optimization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If coordinated resource management is performed at fine slot-level granularity, then resource allocation efficiency is improved, but backhaul latency causes coordination failures
Solution Approach 1:
The patent segments resource management into two distinct time scales: coarse time-scale for coordinated management among TPs and fine time-scale for independent TP decisions. This segmentation allows coordination at a manageable granularity level while maintaining overall system efficiency, resolving the contradiction between fine-grained allocation and backhaul latency constraints.
Solution Approach 2:
The patent performs preliminary user association decisions at the coarse time-scale before fine-grained resource allocation. By pre-determining which users are served by which TPs at the frame level, the system eliminates the need for complex real-time coordination at slot-level, thereby maintaining coordination reliability despite backhaul latency while still achieving efficient resource allocation.
2Reliability
If semi-static resource management is used to handle backhaul latency, then coordination reliability is improved, but resource allocation flexibility deteriorates
Solution Approach 1:
The patent introduces dynamics by allowing TP activation fractions to be adjusted at the coarse time-scale based on system conditions, while fine time-scale resource allocation adapts independently at each TP. This dynamic two-scale approach maintains coordination reliability through structured coarse-level management while preserving flexibility through independent fine-level adaptations.
Solution Approach 2:
The patent implements periodic coordination at the coarse frame level, where TP activation fractions and user associations are updated regularly. This periodic coordinated management ensures reliability by maintaining synchronized decision-making at appropriate intervals, while allowing continuous independent adaptation at the fine time-scale between coordination cycles.
3Adaptability or versatility
If distributed implementation is used for resource management, then system scalability is improved, but implementation complexity increases
Solution Approach 1:
The patent segments the complex distributed resource management problem into two simpler sub-problems: coarse time-scale user association and TP activation fraction determination, and fine time-scale independent resource allocation. This segmentation reduces implementation complexity by breaking down the distributed coordination challenge while maintaining scalability through the modular two-scale architecture.
Solution Approach 2:
The patent performs preliminary user association and TP activation decisions centrally or semi-centrally at the coarse time-scale, which simplifies the subsequent fine time-scale distributed implementation. By pre-determining user-TP associations and activation fractions, the system reduces the complexity of distributed resource allocation while maintaining scalability across multiple TPs.
Data Source
AI summary
A system and method for resource management in a heterogeneous wireless network that is performed via distributed implementation wherein the resources of the mobile communications system are managed on a coarse time-scale and a fine time-scale. The coarse time-scale management comprises a first stage of determining the user association for each of the TPs followed by a second stage of determining activation fractions for all TPs. The determining of the user association is performed by utilizing a GLS procedure having a Greedy Stage and a Local Search Stage. In the Greedy Stage, new user, TP pairs are analyzed and the pair with the greatest improvement in system utility is selected. In the Local Search Stage, potential swaps are analyzed and a pair offering the greatest improvement that exceeds a threshold is selected. The determining of activation fractions for all TPs is performed by utilizing an auxiliary function method.