Wireless Receiver Data Decoding via Signal Accumulation
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Solution Overview
Problem
IoT receivers face challenges in reliably decoding data in low signal-to-noise ratio (SNR) and frequency hopping environments due to unreliable channel estimation values, especially after frequency band hopping occurs.
Innovation Solution
A data decoding method and device that accumulates data signals across multiple sub-frames, updates channel estimation values based on reference signals, and calculates a log likelihood ratio (LLR) for improved decoding, using either a symbol level combining scheme or an LLR combining scheme depending on environmental conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If channel estimation is performed using reference signals in low SNR environments, then channel estimation accuracy is improved, but the time required for channel training increases
Solution Approach 1:
The patent accumulates reference signals from multiple sub-frames before performing channel estimation. By gathering reference signal data in advance across several sub-frames (preliminary action), the system builds up sufficient signal energy to achieve accurate channel estimation even in low SNR environments, while the actual estimation is performed only after accumulation is complete.
Solution Approach 2:
The patent combines reference signals from multiple sub-frames through accumulation. By merging reference signal data across different time instances (sub-frames), the system increases the effective signal-to-noise ratio for channel estimation, thereby improving estimation accuracy without requiring longer individual training sequences.
2Measurement precision
If data signals are accumulated across multiple sub-frames, then decoding accuracy is improved, but the time required to complete decoding increases
Solution Approach 1:
The patent accumulates data signals from multiple sub-frames before performing decoding. By gathering data signal energy in advance across several sub-frames (preliminary action), the system ensures sufficient signal quality for accurate decoding, particularly in low SNR conditions where individual sub-frames may be too noisy.
Solution Approach 2:
The patent combines data signals from multiple sub-frames through accumulation. By merging data signal data across different time instances, the system increases the effective signal-to-noise ratio for decoding, thereby improving decoding accuracy while managing the time trade-off through efficient signal combining operations.
3Measurement precision
If the receiver waits for multiple sub-frames before decoding, then decoding performance is improved, but power consumption increases
Solution Approach 1:
The patent accumulates data signals from a predetermined number of sub-frames (N sub-frames) before decoding, rather than waiting for all possible retransmissions. By using partial action (decoding after a fixed number of accumulations), the system achieves sufficient decoding performance improvement while limiting the time and power expenditure to a controlled amount.
Data Source
AI summary
Provided is a data decoding method of a wireless communication device. The method includes receiving a plurality of sub-frames. The method further includes accumulating data signals respectively included in each of the plurality of sub-frames. The method further includes updating a channel estimation value based on reference signals included in a most recent sub-frame of the plurality of sub-frames. The method further includes calculating a log likelihood ratio (LLR) based on the accumulated data signals and the updated channel estimation value. Furthermore, the method includes decoding data based on the LLR.