Precoding Matrix Determination for MIMO Throughput
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Solution Overview
Problem
MIMO wireless communications systems face increased implementation complexity and require strict channel calibration and significant data exchange between transmit ends for joint precoding, which complicates spectral efficiency improvements and system throughput.
Innovation Solution
A data processing method that determines an optimal precoding matrix at the receive end, ensuring orthogonalization between downlink spatial channels, and notifies each transmit end, allowing for improved system throughput without increasing complexity, by dividing data flows into sub-flows and allocating them on the same time-frequency resources, reducing the need for inter-end coordination.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If joint precoding collaboration between all transmit ends is performed, then spectral efficiency is improved, but implementation complexity increases
Solution Approach 1:
The patent segments the joint precoding problem by allowing each transmit end to independently determine its precoding matrix based on channel state information, rather than requiring all transmit ends to collaboratively compute a unified precoding matrix. This segmentation reduces implementation complexity while maintaining spectral efficiency through independent optimization at each transmit end.
Solution Approach 2:
The patent introduces channel state information as an intermediary that enables transmit ends to make precoding decisions without direct collaboration. Each transmit end uses the channel state information to independently select precoding matrices that achieve spectral efficiency gains without requiring complex inter-transmit-end coordination.
2Productivity
If joint precoding collaboration is performed, then spectral efficiency is improved, but data exchange between transmit ends increases
Solution Approach 1:
The patent segments the data exchange requirement by allowing each transmit end to independently process channel state information and determine precoding matrices without exchanging precoding data with other transmit ends. This eliminates the need for extensive data exchange while maintaining spectral efficiency through distributed decision-making.
3Productivity
If joint precoding is ensured, then spectral efficiency is improved, but signaling interworking delay requirements increase
Solution Approach 1:
The patent segments the signaling process by allowing each transmit end to independently determine precoding matrices based on received channel state information, eliminating the need for iterative signaling exchanges between transmit ends. This reduces signaling delay requirements while achieving spectral efficiency through independent optimization.
4Productivity
If data flows are divided and allocated to multiple transmit ends, then system throughput is improved, but coordination between transmit ends is required
Solution Approach 1:
The patent uses channel state information as an intermediary that enables transmit ends to independently allocate and transmit data flows without direct coordination. Each transmit end uses the channel state information to determine optimal data flow allocation and precoding, achieving high system throughput without complex coordination mechanisms.
Data Source
AI summary
Embodiments of the present application provide a data processing method. In the data processing method, before channel coding, a transmission control device divides a data flow into N sub-data flows, allocates the N sub-data flows to N transmit ends, and notifies the N transmit ends of a same time-frequency resource used for sending the allocated sub-data flows. By applying the technical solution, the N transmit ends can send different sub-data flows of a same data flow to a same receive end on the same time-frequency resource without a large amount of signaling interworking, and a system throughput can be improved without increasing network implementation complexity.


