Singular Value Combiner Precoder Matrices for SNR Balancing
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Solution Overview
Problem
Existing wireless communication systems face challenges in balancing signal-to-noise ratios (SNR) across multiple data streams, leading to inefficient modulation and coding schemes that are limited by the weakest stream, increasing complexity and power consumption for user equipment (UEs).
Innovation Solution
A network entity determines a precoding matrix using singular value decomposition (SVD) to dynamically combine or separate data streams, indicating which streams to combine and which to leave separate, allowing UEs to demodulate combined streams with a more complex decoder and non-combined streams with a less complex decoder.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If all data streams are processed with a complex decoder to achieve optimal SNR balancing, then communication reliability is improved, but device complexity and power consumption increase
Solution Approach 1:
The patent segments data streams into two categories: combined streams that require complex decoding (e.g., PSRD) and non-combined streams that use simpler decoding (e.g., MMSE). This segmentation allows the system to apply appropriate decoding complexity to each stream type, improving overall reliability while reducing total device complexity and power consumption compared to uniformly applying complex decoding to all streams.
2Reliability
If complex decoders are applied to all data streams, then signal-to-noise ratio balancing is improved, but power consumption increases
Solution Approach 1:
The patent segments data streams into combined and non-combined categories, applying complex decoders only to combined streams where they are necessary for SNR balancing, while using simpler decoders for non-combined streams. This selective application reduces overall power consumption while maintaining effective SNR balancing for the streams that require it.
3Productivity
If dynamic stream combining is implemented to balance SNR, then communication efficiency is improved, but system complexity increases
Solution Approach 1:
The patent implements dynamic stream combining by segmenting streams into combined and non-combined groups, with the network entity indicating which streams fall into each category. This approach enables communication efficiency improvement through SNR balancing while controlling system complexity by using standardized signaling mechanisms and well-defined decoding algorithms for each stream type.
Solution Approach 2:
The patent enables dynamic stream combining where the network entity can adaptively determine which streams to combine based on current channel conditions and communication requirements. This dynamic approach improves communication efficiency by optimizing SNR balancing in real-time while maintaining manageable system complexity through flexible yet structured implementation.
Data Source
AI summary
Methods, systems, and devices for wireless communications using a singular value decomposition (SVD) combiner precoder are described. The described techniques may enable a network entity to determine which streams of a set of multiple data streams to combine in the SVD combiner precoder to increase a lowest signal-to-noise ratio of the set of multiple data streams, and which streams of the multiple streams to leave separate. The network entity may determine a precoding matrix using a square matrix α, which may allow the network entity to dynamically combine (e.g., or not combine) data streams. The network entity may transmit an indication to a UE indicating which streams the network entity will combine and which streams the network entity will not combine. The UE may accordingly demodulate the non-combined streams with a relatively less complex demodulator and may demodulate the combined streams with a relatively more complex demodulator.