Hybrid MIMO Beamforming Vector Determination via Subsystem Segmentation
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Solution Overview
Problem
Current wireless communication systems face challenges in determining optimal beamforming vectors, especially in hybrid MIMO systems, without explicit channel knowledge and with multipath propagation, which limits transmission quality and efficiency.
Innovation Solution
The method involves splitting the hybrid MIMO beamforming system into asymmetric subsystems, allowing for the determination of beamforming vectors using training matrices and channel estimation without MIMO signal processing, and optimizing beamforming parameters based on the beamforming channel matrix.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If MIMO signal processing is used to determine beamforming vectors, then transmission quality can be improved, but device complexity and computational effort increase significantly
Solution Approach 1:
The patent segments the hybrid MIMO beamforming system into multiple independent subsystems, each handling a specific MIMO branch. This segmentation allows beamforming vectors to be determined separately for each branch using simplified methods, avoiding the need for complex full-system MIMO signal processing while maintaining transmission quality.
Solution Approach 2:
The patent extracts the essential beamforming function from the complex MIMO signal processing framework. By using training matrices and channel estimation specifically tailored for beamforming rather than full MIMO processing, the system achieves the necessary transmission quality without the computational overhead of complete MIMO signal processing.
2Measurement precision
If full MIMO beamforming system is trained, then optimal beamforming vectors can be determined, but the number of required transmissions and training time increase
Solution Approach 1:
The training process is segmented into independent subsystem Trainings, each requiring fewer transmissions. By determining beamforming vectors for each MIMO branch separately through its own training sequence, the overall training time is reduced while maintaining the accuracy needed for optimal beamforming performance.
Solution Approach 2:
The patent employs preliminary channel estimation using training matrices before actual data transmission. This preliminary action allows the system to pre-determine beamforming vectors based on channel conditions, reducing the need for extensive real-time training transmissions and thereby reducing training time while maintaining vector accuracy.
3Adaptability or versatility
If beamforming is implemented without explicit channel knowledge, then system adaptability improves, but measurement precision of channel conditions deteriorates
Solution Approach 1:
The system performs preliminary channel estimation using dedicated training matrices before data transmission. This preliminary measurement of channel conditions provides the necessary precision for beamforming vector determination, while the system remains adaptable by using these estimates rather than requiring explicit continuous channel knowledge during operation.
Solution Approach 2:
The patent introduces training matrices as an intermediary mechanism that bridges the gap between no channel knowledge and explicit channel knowledge. These training matrices enable indirect channel estimation, providing sufficient measurement precision for beamforming while maintaining system adaptability to varying channel conditions without requiring continuous explicit channel state information.
Data Source
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AI summary
A method for determining beamforming vectors for a transmitting station (502) in a wireless communication system (500) and beamforming vectors for a receiving station (506) in the wireless communication system (100) is described. The transmitting station (502) or the receiving station (506) comprise a hybrid MIMO beamforming configuration including a plurality of MIMO branches (5111, 5112, 5211, 5212), each MIMO branch (5111, 5112, 5211, 5212) comprising a plurality of antennas (5161-5164, 5321-5324). The method includes splitting the hybrid MIMO beamforming system into a plurality of subsystems, each subsystem comprising at least one MIMO transmit branch (5111, 5112) on the transmitting side and at least one MIMO receive branch (5211, 5212) on the receiving side, and wherein the hybrid MIMO beamforming system is a hybrid SIMO (single-input multiple-output) or a hybrid MISO (multiple-input single-output) beamforming system, wherein for a hybrid SIMO beamforming system first, the M×∑q=1QNq beamforming system is considered and a suitable transmitting beamforming vector is determined, and then the hybrid SIMO beamforming overall system is split into Q Mx Nq subsystems, and for every subsystem, a suitable receiving beamforming vector is determined, wherein during determining the receiving beamforming vectors, the previously determined transmitting beamforming vector is considered, and wherein for a hybrid MISO beamforming system first the ∑p=1PMp×N beamforming system is considered and a suitable receiving beamforming vector is determined without considering transmitting beamforming vectors, and then the hybrid MISO beamforming overall system is divided into P Mp x N subsystems, and for every beamforming subsystem, a suitable transmitting beamforming vector is determined, wherein during determining the transmitting beamforming vectors, the previously determined receiving beamforming vector is considered.