MIMO Active Set Management via Scheduler-Based Grouping
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Solution Overview
Problem
Wireless communication systems, particularly multiple-input multiple-output (MIMO) networks, face challenges in managing active sets to optimize resource allocation and minimize interference and capacity issues, leading to complexity and latency in scheduling.
Innovation Solution
A scheduler in the network system determines the number of available MIMO dimensions and interference levels within active sets, calculating metrics to combine underperforming active sets with higher-performing ones, ensuring each active set meets threshold values for dimensions and interference, thereby optimizing resource allocation and reducing complexity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If active sets are managed separately for each node, then device complexity is reduced, but network throughput and reliability deteriorate due to insufficient resource allocation and interference management
Solution Approach 1:
The patent combines multiple active sets from different nodes into a unified active set managed by a central scheduler. This merging allows coordinated resource allocation across nodes, improving network reliability and throughput while maintaining manageable complexity through centralized control.
Solution Approach 2:
The unified active set structure enables the scheduler to perform multiple functions simultaneously: resource allocation, interference management, and coordination across multiple nodes. This multi-functionality improves network performance without proportionally increasing complexity.
2Productivity
If more nodes are combined in active sets, then network throughput is improved, but interference levels increase beyond acceptable thresholds
Solution Approach 1:
The scheduler dynamically adjusts transmission parameters such as power levels and resource allocation for each node within the unified active set. By changing these parameters, the system can combine more nodes to improve throughput while controlling interference through optimized transmission settings.
Solution Approach 2:
The system implements feedback mechanisms where the scheduler monitors interference levels and performance metrics from combined active sets. Based on this feedback, the scheduler dynamically adjusts node combinations and transmission parameters to maintain optimal throughput while keeping interference below thresholds.
3Productivity
If active sets are frequently reconfigured to optimize performance, then network efficiency is improved, but scheduling latency increases due to repeated evaluations
Solution Approach 1:
The scheduler performs active set reconfigurations at periodic intervals rather than continuously. This periodic evaluation maintains network efficiency by optimizing performance periodically while reducing scheduling latency by avoiding constant reconfigurations and evaluations.
Solution Approach 2:
The system performs preliminary evaluations of potential active set combinations before actual reconfiguration. This preliminary assessment allows the scheduler to prepare optimal configurations in advance, reducing the time required for actual reconfiguration and minimizing scheduling latency.
Data Source
AI summary
Aspects of the disclosure relate to an active set management scheme implemented by a scheduler in a multiple-input multiple-output (MIMO) network that minimizes capacity and interference issues. For example, the scheduler can initially group each base station into a separate active set. The scheduler can then analyze each active set to determine whether the active set is a good or bad based on the level of interference in and the number of MIMO transmit dimensions available in the respective active set. If the scheduler determines that an active set is a bad, the scheduler can determine a set of metrics that each represent a capacity and link quality that would result if the bad active set is combined with another active set. Based on the set of metrics, the scheduler can combine the bad active set with another active set, and repeat this process until no bad active sets remain.