MU-MIMO Beam Refinement Using Shared PMI to Mitigate Interference
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Solution Overview
Problem
In MU-MIMO communications, severe interference during simultaneous transmissions between network entities and multiple UEs hinders accurate precoding matrix preparation, leading to inefficient communications and data loss.
Innovation Solution
UEs and network entities refine precoding matrices by exchanging channel state information and interference feedback, adjusting precoding matrix information based on measured channel and predicted interference levels, and communicating with updated beams to mitigate interference.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If network entities transmit multiple data streams to spatially multiplexed UEs simultaneously in MU-MIMO configuration, then system capacity and spectral efficiency are improved, but severe interference occurs between simultaneous transmissions hindering accurate precoding matrix preparation
Solution Approach 1:
The patent applies preliminary action by having UEs transmit channel state information (CSI) and interference feedback before the actual data transmission begins. The network entity receives this information in advance, performs precoding matrix calculations considering predicted interference levels, and prepares the precoding matrices before simultaneous transmission starts. This preliminary preparation allows the system to mitigate interference effects during the actual transmission, resolving the contradiction between high system capacity and accurate precoding preparation.
2Reliability
If UEs transmit precoding matrix information and channel state information to network entities for beam refinement, then communication reliability is improved through interference mitigation, but additional signaling overhead and processing complexity are introduced
Solution Approach 1:
The patent implements feedback mechanisms where UEs transmit channel state information and interference feedback to network entities, which then use this information to refine precoding matrices. The network entity receives feedback about actual interference levels and adjusts precoding matrices accordingly. This feedback loop enables continuous improvement of communication reliability while managing complexity through iterative refinement rather than requiring overly complex one-time calculations.
Solution Approach 2:
The patent applies parameter changes by dynamically adjusting precoding matrix parameters based on measured channel conditions and predicted interference levels. Instead of using fixed or overly complex precoding matrices, the system adapts parameters such as beam directions, precoding weights, and interference cancellation coefficients in real-time. This approach improves reliability through adaptation while reducing processing complexity by focusing on key parameter adjustments rather than complete matrix recomputation.
Data Source
AI summary
Methods, systems, and devices for wireless communications are described. The network entity and a set of UEs may be enabled to refine precoders utilized in communications with each UE. For example, a first UE may utilize reference signaling from a network entity to generate precoding matrix information (PMI) and may transmit the PMI to the network entity, which may forward the PMI to a second UE. The network entity may also forward PMI of the second UE to the first UE. The first UE may utilize the PMI of the second UE, as well as feedback associated with the first UE, to refine the PMI of the second UE, and the second UE may do the same for the first UE. The UEs may transmit the modified PMIs to the network entity, and the network entity may communicate with each of the UEs according to the modified PMIs.