Closed-Loop MIMO Beamforming with Reduced Channel Matrix Dimension
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Solution Overview
Problem
In wireless communication systems, when the number of antennas at the transmitter (beamformer) is less than that at the receiver (beamformee), existing closed loop type MIMO communication methods face challenges in performing effective beamforming without increasing processing capability or circuit size, leading to reduced communication efficiency and increased overhead.
Innovation Solution
The system notifies the receiver of a maximum dimension for computing the transmission weight matrix, allowing it to suppress the channel matrix dimension to match the transmitter's processing capability, enabling efficient beamforming by transmitting a training sequence corresponding to the transmitter's antennas and estimating the channel matrix with reduced dimensions, thereby allowing the transmitter to compute the transmission weight matrix within its processing limits.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the receiver computes the transmission weight matrix using the full channel matrix dimension, then beamforming accuracy is improved, but circuit size and power consumption increase
Solution Approach 1:
The receiver extracts only the necessary portion of the channel matrix corresponding to the transmitter's antenna count, discarding redundant dimensions. This extraction allows accurate beamforming computation using only the required channel information, reducing circuit size while maintaining beamforming accuracy.
Solution Approach 2:
The system changes the dimension parameter of the channel matrix from the receiver's antenna count to the transmitter's antenna count. By adapting the matrix dimension to match the actual computational requirements of the transmitter, the system achieves efficient beamforming with reduced circuit complexity.
2Measurement precision
If the receiver computes the transmission weight matrix using the full channel matrix dimension, then beamforming accuracy is improved, but power consumption increases
Solution Approach 1:
The receiver extracts only the necessary portion of the channel matrix corresponding to the transmitter's antenna count, discarding redundant dimensions. This extraction allows accurate beamforming computation using only the required channel information, reducing power consumption while maintaining beamforming accuracy.
Solution Approach 2:
The system changes the dimension parameter of the channel matrix from the receiver's antenna count to the transmitter's antenna count. By adapting the matrix dimension to match the actual computational requirements of the transmitter, the system achieves efficient beamforming with reduced power consumption.
3Device complexity
If the receiver suppresses the channel matrix dimension to match the transmitter's processing capability, then circuit size is reduced, but beamforming accuracy may deteriorate
Solution Approach 1:
The receiver extracts the precise sub-matrix of the channel matrix that corresponds to the transmitter's antenna configuration. This targeted extraction ensures that all necessary channel information is retained while removing only the redundant dimensions, thus maintaining beamforming accuracy with reduced circuit size.
4Loss of information
If the receiver transmits training sequence corresponding to its own antenna count, then channel estimation completeness is improved, but transmitter processing burden increases
Solution Approach 1:
Instead of the receiver transmitting training sequences corresponding to its own antennas, the system inverts the approach: the transmitter's antenna count determines the training sequence dimension. The receiver suppresses the channel matrix to match the transmitter's capability, eliminating the need for the transmitter to process high-dimensional channel information.
Data Source
AI summary
A wireless communication system is disclosed. The wireless communication system performs data transmission using spatially multiplexed streams from a first terminal including N antennas to a second terminal including M antennas (N and M are integers larger than or equal to 2 and N>M).