MU-MIMO Scheduling Weight Calculation via Information Bits
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Solution Overview
Problem
Conventional proportional fairness scheduling (PFS) algorithms for MU-MIMO wireless transmissions fail to fully utilize the advantages of MU-MIMO in increasing cell throughput due to their reliance on estimated signal-to-interference-plus-noise ratio (SINR), which is not linearly mapped to data rate, leading to suboptimal channel quality weight calculations.
Innovation Solution
The method involves calculating channel quality weights based on the number of information bits per resource element, rather than SINR, allowing for improved scheduling weights and increased cell throughput by considering MU-MIMO scenarios and recalculating weights during the scheduling phase if necessary.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional PFS algorithm uses estimated SINR to calculate channel quality weight, then the scheduling can be implemented, but the cell throughput cannot be fully maximized due to non-linear mapping between SINR and data rate
Solution Approach 1:
The patent changes the parameter used for channel quality weight calculation from estimated SINR to actual information bits per resource element. This parameter transformation directly addresses the non-linear mapping issue because information bits are linearly related to data rate, allowing the scheduler to accurately reflect the actual throughput contribution of each user without the distortion introduced by SINR estimation and non-linear mapping.
2Adaptability or versatility
If conventional PFS algorithm calculates weight based on per-bearer or per-priority queue, then QoS can be maintained, but MU-MIMO pairing opportunities are reduced
Solution Approach 1:
The patent merges the weight calculation from multiple bearers or priority queues into a single aggregated weight per wireless device. By combining the information bits across all bearers and priority queues for a device, the system creates a unified metric that reflects the total contribution of that device to cell throughput, enabling more flexible MU-MIMO pairing decisions that optimize overall system performance rather than being constrained by individual bearer limitations.
3Ease of operation
If more resources are allocated to users in bad channel conditions to improve fairness, then user equity increases, but system performance degrades
Solution Approach 1:
The patent implements a feedback mechanism where the actual information bits successfully transmitted are used to update the channel quality weight calculation. This feedback loop allows the system to adaptively adjust resource allocation based on real transmission outcomes rather than relying on inaccurate SINR predictions. The system can therefore make more informed decisions about fairness versus throughput optimization by observing actual performance rather than estimated performance.
Data Source
AI summary
According to certain embodiments, a method for use in a network node for scheduling wireless transmissions comprises determining a channel quality weight for a first wireless channel based on its number of information bits and a channel quality weight for a second wireless channel based on its number of information bits. The number of information bits is based on a signal to interference plus noise (SINR) measurement and a modulation coding scheme of the wireless channels. The method further comprises determining a scheduling weight for the first wireless device based on the channel quality weight for the first wireless channel, determining a scheduling weight for the second wireless device based on the channel quality weight for the second wireless channel, and scheduling a transmission to one of the first and second wireless devices based on the scheduling weights of the first and second wireless devices.