Wireless Device Symbol Group Processing for 5G Latency
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Solution Overview
Problem
Current wireless communication devices face challenges in processing downlink signals efficiently, particularly in 5G communication systems, which require rapid processing and memory optimization to support low-latency services.
Innovation Solution
A symbol-based processing method is implemented in wireless communication devices, involving channel estimation and demodulation operations on physical downlink shared channels (PDSCH) using reference signals, with a focus on processing in symbol group units to enhance processing speed and memory efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If channel estimation and demodulation operations are performed on all symbols in a downlink signal, then demodulation accuracy is improved, but processing time increases and processing speed deteriorates
Solution Approach 1:
The patent divides the downlink signal into symbol groups and performs channel estimation and demodulation operations selectively on specific symbols within each group rather than all symbols. This segmentation approach maintains adequate demodulation accuracy while significantly reducing processing time and improving processing speed.
Solution Approach 2:
The patent performs channel estimation and demodulation operations on only a subset of symbols (partial action) rather than all symbols in the downlink signal. By selecting specific symbols for processing based on their importance and channel conditions, the system achieves acceptable demodulation accuracy with reduced processing overhead.
2Reliability
If buffer capacity is increased to store all downlink signal information, then processing completeness is improved, but device complexity and manufacturing costs increase
Solution Approach 1:
The patent extracts and processes only the most critical symbols from the downlink signal for channel estimation and demodulation. By identifying and extracting specific symbols that contribute most to processing completeness, the system reduces buffer capacity requirements while maintaining adequate processing reliability.
Solution Approach 2:
The patent applies different processing quality levels to different symbols based on their importance. Critical symbols receive full channel estimation and demodulation operations, while less critical symbols are processed differently or skipped, optimizing the balance between processing completeness and device complexity.
3Measurement precision
If channel estimation operations are performed on every symbol group, then channel estimation accuracy is improved, but memory usage increases and memory efficiency deteriorates
Solution Approach 1:
The patent segments the symbol groups into different categories and performs channel estimation operations only on selected segments rather than all symbol groups. This selective approach maintains channel estimation accuracy for critical symbols while reducing overall memory usage.
Solution Approach 2:
The patent changes the processing parameters dynamically, performing channel estimation on some symbol groups and using different estimation methods or skipping estimation on others based on channel conditions and resource constraints, thereby optimizing the balance between accuracy and memory efficiency.
Data Source
AI summary
A symbol-based processing method for downlink signals of a wireless communication device includes receiving a first downlink signal including a plurality of symbols, detecting a physical downlink shared channel (PDSCH) from the first downlink signal, performing a first channel estimation operation using a first reference signal for demodulating the PDSCH, performing a second channel estimation operation on at least one second symbol between at least two first symbols included in a symbol group unit based on a result of the first channel estimation operation, each time the first channel estimation operation on the symbol group unit is completed, and performing a demodulation operation on the PDSCH based on a result of the second channel estimation operation.