MU-MIMO Grouping via Location and Signal Strength
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Solution Overview
Problem
In wireless digital networks, existing technologies face challenges in effectively grouping client devices for simultaneous MU-MIMO transmissions while minimizing interference and ensuring fairness in airtime allocation, as specified by the IEEE 802.11ac standard, which requires careful management of spatial streams and scheduling to maintain high throughput and fairness across all client devices.
Innovation Solution
A system and method for grouping client devices based on their characteristics, such as signal strength and location, to reduce interference and ensure equal airtime allocation, involving the selection of subsets of client devices for concurrent communication and the use of lower modulation and coding schemes to align transmissions with the same PHY symbol boundaries, thereby optimizing MU-MIMO transmissions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If client devices are grouped for simultaneous MU-MIMO transmissions, then throughput is improved, but inter-user interference increases
Solution Approach 1:
The patent applies local quality by grouping client devices based on their specific characteristics such as location, signal strength, and channel conditions. Each group is formed with devices that have similar local conditions, allowing the system to optimize transmissions for each group while minimizing interference. This is achieved through characteristic-based grouping where devices with comparable signal properties are transmitted to simultaneously, reducing inter-user interference while maintaining high throughput.
2Adaptability or versatility
If frames have different airtime lengths, then client device requirements are met, but MU-MIMO alignment complexity increases
Solution Approach 1:
The patent applies parameter changes by dynamically adjusting modulation and coding schemes (MCS) for different client devices within MU-MIMO groups. By changing transmission parameters such as MCS index, the system can equalize airtime lengths for devices with different data rates and buffer sizes. This allows frames to be aligned to the same PHY symbol boundaries without requiring complex padding mechanisms, thereby reducing alignment complexity while accommodating diverse client device requirements.
3Productivity
If scheduling is optimized for throughput, then transmission efficiency improves, but fairness among client devices deteriorates
Solution Approach 1:
The patent applies dynamics by implementing a flexible scheduling mechanism that adapts to both throughput requirements and fairness considerations. The system dynamically adjusts group formation and scheduling decisions based on current channel conditions, client device characteristics, and fairness metrics. This allows the scheduler to optimize transmission efficiency for MU-MIMO groups while simultaneously ensuring fair access to the medium for all client devices, preventing any single device or group from monopolizing the channel.
Data Source
AI summary
Disclosed herein, one embodiment of the disclosure is directed to a system, apparatus, and method for grouping client devices for simultaneous MU-MIMO transmissions. When client devices are being grouped for simultaneous MU-MIMO transmissions, a first wireless network device may obtain information corresponding to a plurality of client devices that are associated with the first wireless network device. This information may correspond to signals received from one or more of the client devices by each of the wireless network devices other than the first wireless network device. Then, a subset of the client devices may be selected for concurrent communications based, at least in part, on the information corresponding to the plurality of client devices for concurrent communication. Thereafter, the subset of client devices, referred to as the first group, may be concurrently communicated with.