Timing Advance Estimation Using Neural Network Peak Detection
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Solution Overview
Problem
Conventional timing advance estimation schemes in communication systems, particularly in unlicensed spectra, face inaccuracies due to false peaks in autocorrelation of Block-Interleaved Frequency Division Multiplexing (B-IFDM) based preambles, leading to inter-symbol interference and poor alignment of OFDM symbols.
Innovation Solution
A method involving a network device that determines timing advance and error estimation using a random access preamble, employing a neural network to differentiate between main and false peaks, and adjusts communication modes based on error to improve accuracy, including updating weights for better estimation and dynamically managing overhead lengths.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional timing advance estimation schemes are used in unlicensed spectra, then the system can operate with standard procedures, but the estimation accuracy deteriorates due to false peaks in autocorrelation of B-IFDM based preambles
Solution Approach 1:
The patent introduces an intermediary processing stage between the conventional autocorrelation method and the timing advance determination. A neural network or machine learning model is trained to distinguish between main peaks and false peaks in the autocorrelation function, acting as a mediator that filters out erroneous peak detections and improves the reliability of timing advance estimation in unlicensed spectra
Solution Approach 2:
The patent changes the parameter detection approach by transitioning from simple peak detection in autocorrelation to a learned parameter discrimination approach. The system learns to identify characteristics that differentiate main peaks from false peaks, effectively changing how the timing advance parameter is determined and improving accuracy in noisy unlicensed spectrum environments
2Reliability
If dynamic communication mode adjustment based on error estimation is implemented, then the communication robustness is improved, but the system complexity increases
Solution Approach 1:
The patent implements dynamic communication mode adjustment where the system transitions from static to adaptive operation. Based on real-time error estimation from the timing advance determination, the system dynamically selects appropriate communication modes (such as different cyclic prefix lengths or redundancy levels), making the system adaptable to changing channel conditions while maintaining robustness
Solution Approach 2:
The patent incorporates a feedback mechanism where the error estimation from timing advance determination feeds back into communication mode selection. This closed-loop approach allows the system to continuously adjust its operation based on actual performance, improving reliability through adaptive response to estimation quality while managing complexity through structured feedback processing
Data Source
AI summary
In accordance with example embodiments of the invention there is at least a method, device, and computer readable medium for determining a Timing Advance. A method includes, the network device determines an estimation of a timing advance and an error of the timing advance based on a random access preamble received from the terminal device, the network device determines different communication modes with different lengths of overheads for the terminal device based on the error, and the network device can update the estimation of the timing advance based on feedback information from the terminal device. In this way, accuracy of the estimation of the timing advancing is improved.