Massive MIMO DPD Coefficient Allocation by Antenna Channel Gain
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Solution Overview
Problem
Massive MIMO systems face challenges in implementing digital predistortion (DPD) due to high complexity and power consumption, particularly when using per-antenna DPDs without considering channel quality variations, leading to inefficient resource utilization and increased costs.
Innovation Solution
Adaptive determination of DPD size based on channel gain estimates, distributing coefficients among antennas to optimize performance and reduce power consumption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If per-antenna DPDs are deployed without considering channel quality variations, then implementation complexity is reduced, but system performance deteriorates due to inefficient resource utilization
Solution Approach 1:
The patent applies local quality by differentiating DPD configuration across antennas based on their individual channel quality. Specifically, it classifies antennas into different groups (e.g., first group with higher channel quality, second group with lower channel quality) and assigns different DPD model complexities to each group. This allows the system to optimize performance for each antenna's specific conditions rather than applying a uniform configuration, thereby resolving the contradiction between simplified implementation and system performance.
2Productivity
If MIMO DPD is used to compensate for channel quality variations, then system performance is improved, but power consumption and complexity increase significantly
Solution Approach 1:
The patent applies parameter changes by dynamically adjusting DPD configuration parameters based on channel quality measurements. It modifies key parameters such as DPD model order, number of coefficients, and complexity level according to the measured channel conditions. This allows the system to achieve optimal performance while adapting power consumption to actual needs, avoiding the constant high power consumption of full MIMO DPD regardless of channel conditions.
Solution Approach 2:
The patent implements dynamics by making DPD configuration adaptive rather than static. It continuously monitors channel quality and adjusts DPD parameters in real-time, allowing the system to transition between different operational states (e.g., high-complexity DPD when channel quality is poor, low-complexity DPD when channel quality is good). This dynamic adaptation resolves the contradiction by aligning power consumption with actual performance requirements.
3Productivity
If the number of antennas at the access node is increased, then spectral efficiency is improved, but RF chain power consumption and digital beamforming complexity grow large
Solution Approach 1:
The patent applies segmentation by dividing the large number of antennas into multiple groups based on channel quality and spatial characteristics. Instead of processing all antennas uniformly through high-complexity digital beamforming, it segments them into groups that can be processed with different levels of complexity. This segmentation allows the system to maintain high spectral efficiency by utilizing multiple antennas while reducing overall power consumption by applying simplified processing to antenna groups with better channel conditions.
Data Source
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AI summary
There is provided mechanisms for DPD size determination of an access node. The access node is configured for operation in a digital massive MIMO system. The access node comprises a plurality of antennas, one radio chain per antenna, and one DPD per radio chain. A method is performed by the access node. The method comprises obtaining channel gain estimates per each of the plurality of antennas. The method comprises determining the size, in terms of number of coefficients, of each DPD according to a utility function that depends on the channel gain estimates per antenna. The method comprises allocating the determined number of coefficients to each DPD.