Data Reconstruction Using Actual Fading Factor Estimation
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Solution Overview
Problem
Existing data reconstruction methods in interference cancellation technologies do not accurately reflect the actual fading factors, leading to inefficient interference cancellation and reduced system performance.
Innovation Solution
A method and apparatus that acquire and process self-correlation functions and fading factors to estimate actual fading factors, reconstructing data using these estimates to simulate the actual sending process, thereby improving cancellation efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a fading factor obtained by channel estimation is used during data reconstruction, then the reconstruction process can be completed, but the reconstructed data largely deviates from the actual sent data, affecting interference cancellation gain
Solution Approach 1:
The patent introduces a deconvolution process as an intermediary step between channel estimation and data reconstruction. The deconvolution operation removes the filtering effect of the root raised cosine filter from the estimated fading factor, producing a corrected fading factor that accurately represents the actual channel conditions. This intermediary correction enables both accurate fading factor representation and effective interference cancellation.
2Reliability
If root raised cosine filters are applied at transmit and receive ends, then signal transmission quality is improved, but the fading factor becomes a convolution of actual fading and filter response, not the actual fading factor
Solution Approach 1:
The patent extracts the actual fading factor information from the filtered estimation by applying deconvolution. The deconvolution process separates the actual fading factor from the filtering effects of the root raised cosine filters, extracting the true channel characteristics while preserving the benefits of filter-based signal transmission. This extraction restores the actual fading factor information that would otherwise be obscured by the filter convolution.
Data Source
AI summary
Embodiments of the present invention provide a method and an apparatus for reconstructing data. The method includes: acquiring a self-correlation function of a root raised cosine filter coefficient and a fading factor of each antenna of channel estimation; constructing an L-dimension matrix of the self-correlation function according to the antenna; processing a result of superposing the L-dimension matrix of the self-correlation function and the fading factor of each antenna to obtain an estimate value of an actual fading factor of the each antenna; and reconstructing received data according to the estimate value of the actual fading factor to obtain reconstructed data used for cancellation. In the embodiments of the present invention, a process of performing interference cancellation for data reconstruction is closer to an actual sending process and closer to an originally sent signal, thereby improving cancellation efficiency and reducing interference.