MIMO Beam Pair Grouping for Millimeter Wave WLAN Interference
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Solution Overview
Problem
Current beamforming techniques in WLAN systems are limited in their ability to efficiently manage multiple input multiple output (MIMO) transmissions, leading to suboptimal performance in terms of signal quality and interference mitigation.
Innovation Solution
The proposed solution involves an Access Point (AP) or a Proxy Coordination Point (PCP) performing user selection, pairing, and grouping based on measurements of signal quality, such as signal-to-noise ratio (SNR) or signal-to-interference-plus-noise ratio (SINR), acquired through analog beam training. This process allows for the identification of best and worst beams or beam pairs, which are then fed back to the AP/PCP for optimal MIMO frame setup and transmission.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If current beamforming techniques are used in WLAN systems, then device complexity is reduced, but MIMO transmission efficiency and signal quality deteriorate
Solution Approach 1:
The beamforming technique is segmented into distinct phases: analog beam training for initial beam pair identification, followed by digital MIMO setup for optimized multi-user transmission. This segmentation allows each phase to specialize in specific tasks, improving overall MIMO transmission efficiency while managing device complexity through modular design
Solution Approach 2:
Analog beam training is performed as a preliminary action before MIMO transmission setup. Stations feed back best and worst beam pairs to the AP/PCP, which uses this information to preconfigure optimal beam assignments for subsequent MIMO transmissions, thereby improving transmission efficiency before actual data transfer begins
2Object-affected harmful factors
If user selection and grouping based on SNR/SINR measurements are implemented, then interference mitigation is improved, but measurement and processing time increases
Solution Approach 1:
Instead of evaluating all possible beam combinations, the system performs partial evaluation by identifying only the best and worst beam pairs for each station. Stations feed back limited information about top-performing and bottom-performing beams, which reduces measurement and processing time while still enabling effective interference mitigation through selective user grouping
Solution Approach 2:
Stations provide feedback to the AP/PCP regarding their best and worst beam pairs based on SNR/SINR measurements. This feedback mechanism enables the AP/PCP to make informed decisions about user grouping and beam assignment, improving interference mitigation while keeping the selection process efficient through targeted information exchange
3Measurement precision
If multiple analog beams are transmitted for beam training, then beam selection accuracy is improved, but signal transmission time increases
Solution Approach 1:
The system transmits multiple analog beams during training but only requires stations to evaluate and report the best and worst performers among them. This partial evaluation approach maintains measurement precision by considering multiple beam options while reducing overall training time by not requiring exhaustive analysis of all possible beam combinations
Data Source
AI summary
An AP/PCP may perform user selection/pairing/grouping based on a measurement of an analog transmission (e.g., signal to noise ratio (SNR) or signal to interference plus noise ratio (SINR)). The SNRs may be used, for example by the station, to determine best beams and/or beam pairs and/or worst beams and/or beam pairs. A station may feed back the best few beams and/or beam pairs for a Tx and Rx virtual antenna pair. A station may feed back the worst few beams for the Tx and Rx virtual antenna pair. The AP/PCP may receive the indication(s) and/or use the indication(s) to group the stations.