Analog Beamforming Using Covariance Weighting for User Fairness
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Solution Overview
Problem
Existing communication networks face challenges in providing user fairness without significantly reducing overall performance, particularly for users near the cell edge or with weak signal strength, using conventional techniques like Non-Orthogonal Multiple Access (NOMA) and digital beamforming.
Innovation Solution
A beamforming-based approach that adjusts analog beamforming using a weighted sum of client device covariance matrices, determining weights based on client device priority and network conditions, and adjusting phase shifters to improve user fairness.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional techniques like NOMA or digital beamforming are used to improve user fairness, then users with weak signals (cell edge users) receive better service, but overall network performance significantly deteriorates
Solution Approach 1:
The patent changes the parameter representation from individual user channel states to covariance matrices that capture spatial correlation. By operating in the covariance domain rather than individual channel realizations, the system achieves more robust beamforming that maintains performance across varying channel conditions, improving fairness without sacrificing overall network throughput
Solution Approach 2:
The patent segments the beamforming problem into two independent components: covariance matrix computation (capturing spatial statistics) and beamformer design (optimizing signal transmission). This segmentation allows the system to pre-compute covariance matrices that reflect user distribution and channel characteristics, then design beamformers that optimize both fairness and throughput based on these pre-analyzed spatial patterns
2Reliability
If beamforming is optimized for cell edge users to improve their data transfer rate, then user fairness improves, but users in better coverage areas experience reduced performance
Solution Approach 1:
The patent applies local quality by designing beamformers that adapt to local spatial characteristics captured in covariance matrices. Different users receive beamforming weights optimized for their specific spatial location and channel conditions, allowing cell edge users to receive enhanced signals while users in better coverage areas maintain their performance through appropriately tailored beamforming vectors
3Device complexity
If analog beamforming is used instead of digital beamforming, then device complexity is reduced, but precision in controlling signal direction and user fairness deteriorates
Solution Approach 1:
The patent substitutes complex digital signal processing with simpler analog beamforming operations. By computing covariance matrices that encapsulate spatial correlation and using these to directly configure analog beamformers (phase shifters and amplifiers), the system replaces digitally-intensive per-user processing with analog hardware that naturally performs the beamforming based on pre-computed spatial statistics, reducing complexity while maintaining precision
Data Source
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AI summary
A beamforming based user fairness arrangement is disclosed. In the arrangement analog beamforming is adjusted using a weighted sum of client device covariance matrices. The weighted sum of covariance matrices is used in designing an analog beamformer, which is then applied to at least one phase shifter. The phase shifters provide the phase shifted radion frequency signal to antennas that are used in transmitting the radio frequency signal to client devices.