MU-MIMO Grouping via Channel Variation and SINR Estimation
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Solution Overview
Problem
Existing Multiple-Input Multiple-Output (MIMO) grouping methods fail to maximize downlink cell throughput due to the lack of consideration for wireless device channel variation rates and signal-to-noise ratios, leading to increased interference and reduced throughput, especially in scenarios with high mobility devices or low SNR.
Innovation Solution
A method that estimates channel variation coefficients and signal-to-interference-plus-noise ratios (SINR) to determine the information carrying capacity (ICC) of wireless devices, ensuring that only devices improving the ICC are added to MIMO groups, based on spatial separability and channel stability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the number of paired wireless devices is increased to improve spectral efficiency, then spatial multiplexing capability is enhanced, but residual mutual interference increases and cell throughput may decrease
Solution Approach 1:
The patent changes the grouping parameters from purely spatial metrics to include channel variation coefficients and SINR penalties. By dynamically adjusting the grouping based on channel conditions and interference characteristics, the system optimizes the number and composition of paired devices to maximize throughput while controlling interference.
Solution Approach 2:
The patent implements feedback mechanisms where channel estimates from uplink reference symbols are used to compute channel variation coefficients. This feedback loop allows the system to adaptively adjust MU-MIMO groupings based on observed channel conditions, ensuring optimal performance while managing interference levels.
2Device complexity
If uplink reference symbol transmission period is increased to reduce overhead, then system complexity is reduced, but channel estimate accuracy degrades leading to increased leakage interference
Solution Approach 1:
The patent performs preliminary computation of channel variation coefficients using available uplink reference symbols before downlink MU-MIMO transmission. By pre-characterizing the channel variation behavior, the system can compensate for longer reference symbol periods and maintain accurate channel estimates without increasing overhead.
Solution Approach 2:
The patent introduces channel variation coefficients as an intermediary parameter that bridges the gap between sparse reference symbols and accurate channel estimation. These coefficients capture channel behavior between reference measurements, enabling accurate channel state information without frequent reference transmissions.
3Device complexity
If spatial separation-based grouping is used to simplify device selection, then grouping complexity is reduced, but throughput is not maximized when high mobility or low SNR devices are included
Solution Approach 1:
The patent extends the grouping criteria beyond spatial separation by incorporating channel variation coefficients and SINR penalties. This multi-parameter approach maintains manageable complexity while significantly improving throughput by accounting for device mobility and channel conditions in the grouping decision.
Data Source
AI summary
According to one or more embodiments, a network node is provided. The network node includes processing circuitry configured to: determine a subset of a plurality of candidate wireless devices for Multiple-Input Multiple-Output, MIMO, grouping based at least on an information carrying capacity, ICC, of a MIMO transmission to the MIMO grouping; and cause the MIMO transmission to the MIMO grouping.