MU-MIMO Precoder Interference Suppression via Distributed Coordination
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Solution Overview
Problem
Current MU-MIMO communication techniques face challenges in efficiently managing interference and optimizing data transmission rates, particularly with errors in channel estimates and peak power capping, especially in distributed MU-MIMO systems.
Innovation Solution
Implementing a base station system with multiple radio units using smart interference suppression (IS) precoding schemes, including global and local IS, and hybrid precoding methods to optimize data transmission rates and handle errors in channel estimates, while capping peak antenna element power.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional SVD precoding is used in MU-MIMO systems, then the system complexity is relatively low, but the data transmission rate is limited and interference management is insufficient
Solution Approach 1:
The patent segments the precoding process into multiple stages: initial SVD precoding to establish basic spatial multiplexing, followed by interference suppression precoding to manage inter-user interference, and peak power capping to handle power constraints. This segmentation allows each stage to address specific aspects of the transmission problem independently, achieving high data rates through coordinated multi-stage processing while keeping individual processing steps manageable.
Solution Approach 2:
The patent applies preliminary action by first performing SVD decomposition to obtain initial precoding matrices before applying interference suppression techniques. The channel matrix is pre-processed to identify dominant spatial modes, and interference suppression precoders are designed based on these pre-computed modes. This preliminary structuring of the channel enables subsequent interference management to be more effective and computationally efficient.
2Productivity
If interference suppression precoding is applied to manage inter-user interference, then the data transmission rate improves, but the sensitivity to channel estimation errors increases
Solution Approach 1:
The patent implements beforehand cushioning by designing the interference suppression precoder to account for potential channel estimation errors in advance. The precoding scheme incorporates robustness mechanisms that cushion against the degradation caused by errors, ensuring that performance does not collapse when channel estimates are imperfect. This pre-built resilience allows the system to maintain high data rates even in the presence of estimation inaccuracies.
3Power
If peak power capping is applied to antenna elements, then the system operates within power constraints, but the data transmission rate may be reduced
Solution Approach 1:
The patent applies dynamics by making the precoding matrices adaptive to power constraints. The interference suppression precoders are designed with dynamic power allocation that adjusts transmit power across different spatial modes and users based on channel conditions and interference levels. This dynamic power management allows the system to operate at peak power when conditions permit high rates while reducing power when constraints are tighter, thereby maintaining the highest possible data transmission rate within power limits.
4Productivity
If distributed MU-MIMO is implemented to improve coverage and capacity, then the system coverage and user capacity increase, but the interference management becomes more complex
Solution Approach 1:
The patent merges the interference suppression functions across multiple distributed radio points into a coordinated precoding framework. Instead of each radio point operating independently, the system combines channel state information from multiple points and applies joint interference suppression precoding that considers interferences from all distributed transmitters. This merging of interference management functions across distributed points achieves high system capacity while keeping the coordination complexity manageable through unified precoder design.
Data Source
AI summary
This disclosure relates to Multi-User Multiple-Input-Multiple-Output (MU-MIMO) (including without limitation Distributed MU-MIMO (D-MU-MIMO)) communication techniques that employ interference suppression (IS) precoding schemes (including, for example, precoding schemes that use local interference suppression and precoding schemes that use global interreference suppression).