Adaptive DM-RS Density for Channel Estimation in 5G
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Solution Overview
Problem
In wireless communication systems, particularly in OFDM systems like 5G New Radio, the transmission of demodulation reference signals (DM-RS) compromises data traffic channel resources, impacting channel estimation quality due to fixed resource allocation, which is not adaptable to varying channel conditions.
Innovation Solution
Adaptive demodulation reference signal density is implemented, increasing density when channel estimation performance is poor (based on negative acknowledgments) and decreasing it when performance is good (based on positive acknowledgments), optimizing resource allocation without compromising channel estimation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If demodulation reference signals are transmitted within resource blocks, then channel estimation quality is improved, but data traffic channel resources are reduced
Solution Approach 1:
The patent applies dynamics by making the DM-RS density adjustable rather than fixed. The network device adapts the DM-RS density based on channel conditions, terminal mobility, and other factors, allowing the system to optimize the balance between channel estimation quality and data resources dynamically. This resolves the contradiction by enabling the DM-RS density to change according to actual needs rather than remaining static.
Solution Approach 2:
The patent changes the parameter of DM-RS density from a fixed value to an adjustable parameter. By modifying the density parameter based on channel conditions, terminal speed, and other factors, the system can improve channel estimation quality when needed while conserving data resources when conditions permit, thus resolving the resource allocation contradiction.
2Quantity of substance
If the number of resource elements for demodulation reference signals is reduced, then data traffic channel resources are increased, but channel estimation quality is impacted
Solution Approach 1:
The system dynamically adjusts DM-RS density based on actual channel conditions and data requirements. When data resources are prioritized and channel conditions are good, the DM-RS density is reduced. When channel estimation quality becomes critical, the density is increased accordingly, resolving the contradiction through adaptive adjustment rather than static allocation.
Solution Approach 2:
The patent modifies the DM-RS density parameter to be adjustable, allowing the system to optimize the trade-off between data resources and channel estimation quality. By changing this parameter based on operational conditions, the system achieves efficient resource allocation without permanently compromising channel estimation capability.
3Device complexity
If fixed resource allocation for demodulation reference signals is used, then resource allocation is simple, but adaptability to varying channel conditions is poor
Solution Approach 1:
The patent transforms fixed resource allocation into dynamic allocation. The network device determines DM-RS density based on channel conditions, terminal mobility, and other varying factors, allowing the system to adapt to different scenarios while maintaining manageable complexity through standardized adjustment rules and procedures.
Solution Approach 2:
The system changes the resource allocation approach from fixed parameters to adjustable parameters. By modifying DM-RS density based on channel conditions and operational requirements, the system achieves adaptability to varying conditions while maintaining reasonable complexity through structured adjustment mechanisms.
Data Source
AI summary
The described technology is generally directed towards adapting the demodulation reference signal sent in a wireless resource data block based on channel estimation performance. In general, if the demodulation reference signal received was not successfully able to be used to demodulate the resource data block, the demodulation reference signal density can be increased up to a maximum density, which costs resource elements but improves the channel estimation accuracy. If the demodulation reference signal received was able to be used to demodulate the resource data block, the demodulation reference signal density can be decreased down to minimum density, which saves resource elements for data. The network device can use HARQ ACK/NACK data (e.g., a current count or counted over a time period) to determine channel estimation performance, and/or the user equipment can recommend a demodulation reference signal density change.