Mmimo Scheduling Using Channel Correlation to Reduce Wi-Fi Interference
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Solution Overview
Problem
Current scheduling algorithms for massive MIMO (mMIMO) systems operating in the unlicensed band fail to effectively manage interference between user equipment (UEs) and Wi-Fi devices, leading to reduced throughput and potential regulatory violations due to poor channel correlation handling and inefficient resource allocation.
Innovation Solution
A method for scheduling user equipment in the unlicensed band that estimates channel correlations between UEs and access nodes, selecting UEs with lower correlation to access nodes' channels to reduce interference, and using precoding operations to form beams that minimize interference with Wi-Fi devices, thereby optimizing resource usage and coexistence.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If channel correlation between UEs and access nodes is not considered in scheduling, then scheduling complexity is reduced, but interference between mMIMO-U signals and Wi-Fi devices increases
Solution Approach 1:
The system performs preliminary channel correlation estimation between UEs and access nodes before scheduling decisions are made. This advance assessment of channel relationships enables the scheduler to identify and avoid scheduling UEs that would create high interference with cochannel Wi-Fi devices, thus resolving the contradiction by preparing interference mitigation information in advance without adding significant complexity to the scheduling process itself
2Productivity
If UEs with high channel correlation to access nodes are scheduled, then more UEs can be served simultaneously, but interference with Wi-Fi devices increases and regulatory compliance deteriorates
Solution Approach 1:
The system changes the scheduling parameter from purely throughput-based selection to correlation-based selection. By using channel correlation values as the primary scheduling criterion, the system identifies UEs with low correlation to access nodes, thereby reducing interference to Wi-Fi devices while maintaining acceptable productivity levels. This parameter change enables simultaneous achievement of regulatory compliance and reasonable system throughput
3Object-generated harmful factors
If channel correlation estimation and correlation-based scheduling are implemented, then interference is reduced and coexistence improves, but computational complexity and processing time increase
Solution Approach 1:
The system applies local quality by focusing channel correlation estimation only on specific spatial directions and frequency resources where Wi-Fi devices are detected to operate. Rather than performing full-matrix channel estimation across all dimensions, the system locally estimates correlation in relevant spatial-frequency regions, thereby reducing computational complexity while maintaining effective interference mitigation in the critical coexistence scenarios
Data Source
AI summary
A method of scheduling user equipment, a multiple antenna network node and computer program are disclosed. The method comprises: estimating at least one access network node channel within the unlicensed band between at least one access node operable to transmit in the unlicensed band, such as a WiFi Access Point, and the multiple antenna network node. Estimating a plurality of user equipment channels within the unlicensed band between a plurality of user equipment and the multiple antenna network node. Determining a degree of channel correlation of each of the plurality of user equipment channels and the at least one access node channel. Selecting at least one of the multiple user equipment to be scheduled, using the degree of channel correlation as a selection parameter, a lower degree of channel correlation increasing a user equipment's chance of being selected. In this manner the interference that LTE transmissions from and to scheduled UEs create on the at least one access node is reduced.