WLAN Access Point Grouping for MU-MIMO Throughput
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Solution Overview
Problem
Conventional wireless local area networks (WLANs) fail to maximize data throughput in Multi-User Multiple-Input-Multiple-Output (MIMO) transmission by only considering channel state information when grouping client stations, leading to suboptimal performance due to uniform channel correlation thresholds that do not account for varying distances from the access point.
Innovation Solution
The method involves calculating channel correlations and determining distances between the access point and client stations, adjusting channel correlation thresholds based on distance, and selecting a subset of client stations for spatial stream allocation to maximize throughput, using sounding packets for feedback and signal-to-noise ratio to estimate distances and channel quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a uniform channel correlation threshold is used for grouping client stations, then the grouping process is simple, but data throughput is not maximized
Solution Approach 1:
The patent applies local quality by using different channel correlation thresholds for different distance ranges. Instead of a uniform threshold, the system determines thresholds based on the distance between the access point and each client station, allowing closer stations to have higher correlation thresholds while distant stations have lower thresholds. This localized adaptation maximizes throughput for each station's specific conditions.
Solution Approach 2:
The patent implements dynamics by making the channel correlation threshold variable rather than fixed. The threshold is dynamically adjusted based on the measured distance between the access point and each client station. This dynamic threshold adaptation allows the system to optimize grouping decisions in real-time based on actual channel conditions and station positions.
2Productivity
If only channel state information is used for grouping, then the system is simple to implement, but data throughput is not maximized
Solution Approach 1:
The patent applies parameter changes by expanding the grouping criteria from solely channel state information to include distance-based threshold adjustments. The system changes the parameter used for correlation assessment from a fixed value to a variable threshold that depends on station distance. This parameter modification enables better throughput optimization while maintaining practical implementation complexity.
3Productivity
If closer client stations are grouped together, then spatial stream allocation is efficient, but channel correlation requirements must be relaxed
Solution Approach 1:
The patent applies local quality by implementing distance-specific channel correlation thresholds. For closer stations, the system uses higher correlation thresholds, while distant stations use lower thresholds. This localized quality adjustment allows efficient spatial stream allocation for nearby stations without unnecessarily rejecting valid groupings, thereby maintaining both efficiency and reliability.
Data Source
AI summary
A method for grouping a plurality of client stations in a wireless local area network is disclosed herein. An access point (AP) determines the channel correlation and a distance to the AP for each of the client stations. The AP selects a smaller subset of client stations that meet a threshold requirement determined based on the respective distances between the client stations and the AP.