Relaxed Beamforming Matrix for mmWave Precoding Complexity
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Solution Overview
Problem
Designing digital and analog precoders for mmWave communication systems is overly complex, particularly due to the need for iterative design and the challenge of severe path loss, penetration loss, and rain fading in 5G wireless networks, which complicates achieving high sum rates with limited RF chains.
Innovation Solution
A precoding method that computes a relaxed beamforming matrix based on desired and interfering channel correlation matrices, approximates it to ensure constant magnitude entries, selects and updates data streams, and uses an analog precoder to perform precoding operations, leveraging uplink-downlink duality to decouple user precoding designs and reduce computation complexity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If iterative design of digital and analog precoders is used, then precoding performance is improved, but computation complexity increases excessively
Solution Approach 1:
The patent segments the precoding design into two independent stages: (1) computing a relaxed beamforming matrix without constant magnitude constraints, and (2) approximating it to enforce constant magnitude entries. This segmentation eliminates the need for iterative design while maintaining good precoding performance, thereby reducing computation complexity significantly.
Solution Approach 2:
The patent extracts the constant magnitude constraint from the beamforming matrix computation and applies it only in the approximation stage. By taking out this constraint from the main optimization process, the system avoids the computational burden of iterative design while still achieving satisfactory precoding performance.
2Reliability
If number of antennas is increased to combat path loss, then signal quality is improved, but system complexity and cost increase
Solution Approach 1:
The patent applies local quality by using hybrid beamforming with different precoding strategies for different parts of the system: relaxed beamforming for the digital precoder and constant magnitude approximation for the analog precoder. This allows the system to handle large numbers of antennas effectively without proportionally increasing overall complexity.
Solution Approach 2:
The patent changes the parameter constraints by removing the constant magnitude constraint from the beamforming matrix computation and applying it only in the approximation stage. This parameter change allows the system to scale to more antennas while maintaining manageable complexity through the two-stage approach.
3Device complexity
If number of RF chains is reduced to lower cost, then system cost is reduced, but precoding performance degrades
Solution Approach 1:
The patent performs preliminary action by computing the relaxed beamforming matrix first, which captures the optimal beamforming directions without constant magnitude constraints. This preliminary computation provides a high-quality starting point that can be approximated to constant magnitude with minimal performance loss, even when the number of RF chains is reduced.
Solution Approach 2:
The patent creates an approximation of the relaxed beamforming matrix that enforces constant magnitude entries. This copying approach allows the system to use fewer RF chains while maintaining good precoding performance by closely replicating the optimal beamforming directions obtained from the relaxed computation.
Data Source
AI summary
A precoding method is provided. The precoding method includes computing a relaxed beamforming matrix according to multiple desired channel correlation matrices and multiple interfering channel correlation matrices; computing an approximated beamforming matrix according to the relaxed beamforming matrix; computing multiple degradations corresponding to the data streams according to multiple relaxed beamforming vectors within the relaxed beamforming matrix and multiple approximated beamforming vectors within the approximated beamforming matrix; selecting a selected data stream index according to the degradations; decomposing a selected relaxed beamforming vector corresponding to the selected data stream index into a first vector and a second vector; and updating the approximated beamforming matrix according to the first vector and augmenting the approximated beamforming matrix according to the second vector, to obtain an updated-and-augmented beamforming matrix.