Assisted MU-MIMO Grouping via Client Sensor Data
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Solution Overview
Problem
Conventional MU-MIMO systems face inefficiencies due to large discrepancies in data usage, latency, and bandwidth consumption among clients with similar RF characteristics, and frequent regrouping challenges posed by mobile devices, which affect data distribution and spectral efficiency.
Innovation Solution
The implementation of an assisted MU-MIMO wireless communication system that uses complementary data, such as device mobility, type, and application data usage, in addition to RF characteristics, to group clients more efficiently, allowing clients to share protocol data and adjust their grouping membership, and enabling the access point to create a RF map for reevaluation of groupings.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If clients are grouped based solely on RF characteristics in conventional MU-MIMO systems, then beamforming can be established for data transmission, but large discrepancies in data usage, latency, and bandwidth consumption among clients with similar RF characteristics cause inefficiencies
Solution Approach 1:
The patent applies local quality by transitioning from uniform grouping based solely on RF characteristics to differentiated grouping that considers individual client attributes such as device type, mobility status, and application data usage patterns. This allows the system to tailor beamforming strategies and resource allocation to the specific needs of each client or client group, resolving the inefficiency where clients with similar RF characteristics but different usage patterns were treated identically.
Solution Approach 2:
The patent implements dynamics by enabling frequent regrouping of clients based on real-time changes in client attributes (device type, mobility, data usage). Unlike conventional static grouping based only on RF characteristics, this dynamic approach allows the access point to adapt client groupings as clients move or change their data usage patterns, thereby maintaining optimal spectral efficiency and data distribution efficiency throughout the communication session.
2Reliability
If client grouping is based on RF characteristics only, then beamforming groups can be formed, but mobile devices cause frequent regrouping challenges that affect data distribution
Solution Approach 1:
The patent applies preliminary action by proactively identifying and categorizing client attributes (device type, mobility status, data usage patterns) before forming beamforming groups. The access point collects this attribute information in advance and uses it to predict which clients are likely to remain stable in their groupings versus those that may require frequent regrouping. This preliminary classification enables the system to prepare appropriate beamforming strategies and resource allocations, reducing the disruptive impact of mobile device movements on overall data distribution efficiency.
3Productivity
If comprehensive client data is collected and processed for optimized grouping, then spectral efficiency improves, but system complexity increases
Solution Approach 1:
The patent applies segmentation by dividing the complex client grouping management task into distinct modules: RF characteristic analysis, device type identification, mobility status detection, and data usage pattern recognition. Each module processes a specific aspect of client information independently, and their results are integrated to form the final grouping decision. This modular segmentation reduces the computational burden on the access point and simplifies the overall system architecture while still achieving comprehensive client characterization for optimized spectral efficiency.
Data Source
AI summary
Systems, methods, and devices for grouping client devices based on sensor data in an assisted wireless communication system are provided. Sensor data may include device mobility, device type, and device application data usage, among other characteristics. An assisted wireless communication system may include client devices sending data to an access point. The clients may send conventional protocol data over a channel and, concurrently, send sensor data over an alternative channel. In some cases, client devices may exchange their protocol data, modify their own protocol data based on the exchanged data, and send the modified protocol data to the access point. This may allow the clients to adjust their grouping.