MIMO Transceiver Beamforming Optimization via Block Coordinate Descent
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Solution Overview
Problem
Current wireless communication systems face challenges in maximizing communications system utility due to inter-cell and intra-cell interference, which affects user fairness and overall performance, especially in multiple-input multiple-output (MIMO) systems.
Innovation Solution
The solution involves a method for operating a MIMO communications system that combines joint user scheduling with the design of transmit and receive beamforming vectors, using a block coordinate descent algorithm to optimize resource allocation and beamforming, thereby reducing interference and improving system performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If joint user scheduling with transmit and receive beamforming design is implemented, then system utility and user fairness are improved, but device complexity and computational load increase
Solution Approach 1:
The patent divides the complex beamforming optimization problem into separate transmit and receive beamforming design steps, solved iteratively through block coordinate descent. The transmit beamforming is optimized first while holding receive beamforming fixed, then receive beamforming is optimized while holding transmit beamforming fixed, repeating until convergence. This segmentation reduces the complexity of solving the joint optimization problem directly.
Solution Approach 2:
The patent implements an iterative feedback mechanism where receive beamforming vectors are fed back to the transmitter to update transmit beamforming vectors, and vice versa. This feedback loop allows the system to progressively improve both transmit and receive beamforming designs through multiple iterations, achieving optimal performance while managing computational complexity through structured updates.
2Reliability
If beamforming vectors are optimized to reduce interference, then communication performance improves, but computational load increases
Solution Approach 1:
The patent applies partial action by optimizing beamforming vectors iteratively rather than simultaneously. In each iteration, only one set of beamforming vectors (either transmit or receive) is updated while the other remains fixed. This partial optimization approach achieves progressive improvement in communication performance while significantly reducing the computational load compared to joint optimization of both beamforming vectors at once.
3Device complexity
If distributed algorithm is used for beamforming design, then computational load is reduced, but convergence speed and design accuracy may be affected
Solution Approach 1:
The patent ensures continuity of useful action through iterative updates where transmit and receive beamforming vectors are continuously refined over multiple iterations. Each iteration performs a useful update of beamforming vectors based on current channel conditions and interference levels, maintaining continuous progress toward optimal performance while distributing computational tasks across multiple steps rather than requiring simultaneous computation.
Data Source
AI summary
A method for operating a controller of a multiple input, multiple output communications system includes formulating an objective function according to a resource allocation for a user equipment (UE) and a mean square error expression, and updating the objective function to generate an updated resource allocation for the UE, a transmit beamforming vector to precode a transmission to the UE, and a receive beamforming vector to adjust a receiver to receive the precoded transmission. The method also includes transmitting allocation information about the resource allocation for the UE and the transmit beamforming vector to a communications controller serving the UE.