SINR-Based AP Selection for MU-MIMO Throughput
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Solution Overview
Problem
Existing AP selection algorithms in wireless networks, such as those based on Received Signal Strength Indicator (RSSI), often result in suboptimal throughput due to assigning clients with correlated or non-orthogonal channels to the same access point, leading to high inter-client interference and limited Multi-User Multiple Input Multiple Output (MU-MIMO) grouping opportunities, especially in enterprise and campus Wi-Fi networks.
Innovation Solution
The implementation of a method that estimates the signal-to-interference-plus noise ratio (SINR) value between wireless clients and access points using Channel State Information (CSI), allowing for the selection of access points based on channel bandwidth and SINR, to identify optimal MU-MIMO groups and enhance network throughput.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If RSSI-based AP selection algorithm is used, then client can be assigned to AP with strong signal, but inter-client interference increases and throughput decreases
Solution Approach 1:
The patent changes the selection parameter from RSSI (signal strength only) to SINR (signal quality considering interference and noise). This parameter change allows the system to select APs that provide both strong signals and low interference, resolving the contradiction between signal reliability and throughput productivity.
Solution Approach 2:
The patent introduces SINR as an intermediary metric that mediates between signal strength and interference levels. By using SINR as the intermediate selection criterion, the system can achieve both reliable connections and high throughput by filtering out clients that would cause or experience high interference.
2Productivity
If clients with correlated channels are assigned to same AP, then AP utilization increases, but MU-MIMO grouping opportunities are limited
Solution Approach 1:
The patent applies local quality by treating different client groups differently based on their channel characteristics. Clients with orthogonal channels are identified and grouped together for MU-MIMO, while clients with correlated channels are assigned to different APs. This localized differentiation resolves the contradiction between AP utilization and MU-MIMO capability.
Solution Approach 2:
The patent segments the client population into different groups based on channel orthogonality. By segmenting clients into MU-MIMO suitable groups and non-MU-MIMO groups, the system can optimize AP utilization for general clients while preserving MU-MIMO grouping opportunities for compatible clients.
3Adaptability or versatility
If legacy AP selection algorithm is used, then heterogeneous clients can be assigned to same AP, but MU-MIMO grouping opportunities are limited
Solution Approach 1:
The patent introduces dynamic client grouping based on real-time channel conditions and client capabilities. Instead of static assignment, the system dynamically identifies MU-MIMO suitable clients and groups them accordingly, while still allowing heterogeneous clients to be served by the same AP through non-MU-MIMO mechanisms. This dynamic approach resolves the contradiction between client compatibility and MU-MIMO throughput.
Data Source
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AI summary
In some examples, a method includes estimating a signal-to-interference-plus noise ratio (SINR) value between a wireless client and each Access Point (AP) of a plurality of APs based on Channel State Information (CSI) between the wireless client and each AP of the plurality of APs and selecting an AP of the plurality of APs to be associated with the wireless client based on a channel bandwidth of the wireless client and the estimated SINR value between the wireless client and each AP of the plurality of APs.