Uplink MIMO Precoding Matrix Determination via Channel Reciprocity
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Solution Overview
Problem
Current wireless communication systems face challenges in determining and signaling an optimal precoding matrix for uplink MIMO transmissions, particularly in 5G NR networks, which affects transmission performance and interference management.
Innovation Solution
The proposed solution involves determining a precoding matrix for uplink MIMO transmissions based on channel estimates, where the base station or user equipment calculates and signals the precoding matrix to optimize transmission performance and minimize interference, using techniques such as estimating cross-correlation matrices and whitening matrices, and signaling this information through control channels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the base station determines and signals the precoding matrix to the user equipment, then transmission performance is optimized, but signaling overhead increases
Solution Approach 1:
The patent extracts only the essential precoding matrix information (Type 1 PMI) that is critical for uplink transmission performance, separating it from less critical feedback information (Type 2 PMI). This selective extraction reduces the amount of signaling overhead while maintaining the most important performance-optimizing parameters.
Solution Approach 2:
The patent applies different precoding matrix determination approaches to different spatial layers: the first spatial layer uses base station-determined precoding (Type 1 PMI) for optimal performance, while subsequent spatial layers use user equipment-determined precoding (Type 2 PMI). This localized quality approach optimizes performance where needed while reducing overall signaling overhead.
2Loss of information
If the user equipment determines the precoding matrix autonomously, then signaling overhead is reduced, but transmission performance may be suboptimal
Solution Approach 1:
The patent segments the precoding matrix determination process into two distinct parts: Type 1 PMI determined by the base station for the first spatial layer, and Type 2 PMI determined by the user equipment for subsequent spatial layers. This segmentation allows each part to be optimized independently, balancing performance and overhead concerns.
Solution Approach 2:
The base station performs preliminary determination of the precoding matrix (Type 1 PMI) for the first spatial layer before the user equipment needs to transmit data. This preliminary action establishes an optimal foundation for subsequent autonomous user equipment precoding decisions, ensuring performance is optimized before overhead reduction is applied.
3Productivity
If multiple precoding matrices are signaled for different spatial layers, then spectral efficiency is improved, but device complexity increases
Solution Approach 1:
The patent inverts the traditional approach by having the base station determine precoding for only the first spatial layer while the user equipment determines precoding for subsequent layers. This inversion reduces the computational burden on the base station and simplifies device complexity while still enabling multi-layer spectral efficiency improvements.
Data Source
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AI summary
Aspects of the disclosure relate to multiple-input multiple-output (MIMO) signals, and the determination of a precoding matrix for configuring the MIMO signals. An uplink traffic channel may be configured utilizing orthogonal frequency division multiplexing (OFDM) waveform. Determination of the precoding matrix may be based at least in part on an estimate of the uplink carrier, where the uplink carrier estimate is based at least in part on a downlink reference signal, exploiting channel reciprocity in a time division duplex (TDD) carrier. Determination of the precoding matrix may further be based at least in part on a cross-correlation matrix Rnn or a whitening matrix determined by a scheduling entity. Other aspects, embodiments, and features are also claimed and described.