Receiver-Aided MU-MIMO Beamforming Interference Suppression
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Solution Overview
Problem
Current MU-MIMO and Coordinated Beamforming technologies face inefficiencies due to incomplete downlink channel information and limited precoder selection, leading to increased multi-user interference.
Innovation Solution
A receiver-aided approach is introduced, where User Equipments (UEs) provide Channel State Information (CSI) tailored to actual data transmission conditions, enabling better decision-making by the base station for MU-MIMO and CB operations, and allowing UEs to estimate and suppress multi-user interference.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If the base station uses traditional precoding methods without receiver feedback, then the system complexity is reduced, but the beamforming efficiency and interference suppression deteriorate
Solution Approach 1:
The patent implements a feedback mechanism where UEs report CSI including interference measurements to the base station. The base station uses this feedback to adjust precoding matrices and beamforming weights, creating a closed-loop system that adapts to actual channel conditions and interference levels to optimize beamforming efficiency.
Solution Approach 2:
The system performs preliminary channel estimation and interference measurement before final precoding decision. The base station requests and receives CSI reports from UEs in advance, allowing the system to pre-calculate optimal beamforming parameters and select appropriate precoding matrices before actual data transmission occurs.
2Device complexity
If the base station uses limited precoder selection, then the device complexity is reduced, but the multi-user interference increases
Solution Approach 1:
The patent dynamically changes the precoder selection parameters based on real-time channel conditions and interference measurements. The base station adjusts the number of precoding matrices to select from, the selection criteria, and the beamforming weights according to the reported CSI and measured interference levels, optimizing the balance between complexity and interference suppression.
Solution Approach 2:
The system transitions from static, pre-determined precoder selection to dynamic, adaptive precoder selection. The base station continuously monitors channel conditions and interference levels, adjusting the precoding strategy in real-time based on actual system state, allowing flexible adaptation to changing environmental conditions.
3Ease of operation
If the base station lacks complete downlink channel information, then the system operation is simplified, but the interference suppression capability deteriorates
Solution Approach 1:
The patent introduces CSI reports as an intermediary information carrier between the UE and base station. These reports contain processed channel state information and interference measurements that bridge the information gap, allowing the base station to make informed precoding decisions without requiring direct, complete downlink channel measurements.
Solution Approach 2:
Instead of the base station directly measuring downlink channel conditions, the system inverts the approach by having the UE measure and report channel state information and interference levels. This reverse information flow provides the base station with the necessary channel knowledge through UE feedback rather than direct base station measurement.
Data Source
AI summary
Embodiments include systems and methods for improving the beamforming efficiency of Multi-User Multiple Input Multiple Output (MU-MIMO) and/or Coordinate Beamforming (CB) in wireless multi-access networks. In one aspect, a receiver-aided approach for MU-MIMO and/or CB is provided. Unlike conventional MU-MIMO/CB operation which is transparent to the UE, the receiver-aided approach herein makes information about potential MU-MIMO and/or CB multi-user interference available to UEs being considered for MU-MIMO and/or CB transmission. As such, the UEs can provide Channel State Information (CSI) that is better tailored to actual data transmission conditions than in conventional operation, and the base station can make better decisions regarding MU-MIMO and/or CB operation, user selection, and transmission parameters (e.g., number of data streams, precoder matrix, etc.).