Kalman Filter Reception Matrix for Twisted Wave Signal Estimation
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Solution Overview
Problem
Current radio communications systems face challenges in efficiently managing twisted waves, particularly in reducing bandwidth and minimizing interference between adjacent channels, especially when using time-domain-based technologies, which can lead to complexity and compatibility issues.
Innovation Solution
The application of a Kalman filter in the reception matrix at the reception side to optimize the extraction of digital symbols carried via twisted-wave-based digital modulation, enhancing performance by improving noise management and reducing interference.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If time-domain-based technologies are used for twisted wave management, then signal processing capability is improved, but device complexity and compatibility issues increase
Solution Approach 1:
The patent replaces complex time-domain signal processing mechanisms with a frequency-domain filtering approach using a Kalman filter in the reception matrix. This substitution simplifies the system by using mathematical filtering operations instead of complex temporal processing, thereby reducing device complexity while maintaining signal processing capability.
Solution Approach 2:
The patent changes the domain of operation from time-domain to frequency-domain processing by implementing the Kalman filter in the reception matrix. This parameter change allows the system to process twisted wave signals more efficiently, reducing computational complexity and improving compatibility with existing frequency-domain communication infrastructure.
2Object-affected harmful factors
If adjacent channel interference is reduced through conventional methods, then channel isolation is improved, but bandwidth efficiency deteriorates
Solution Approach 1:
The Kalman filter in the reception matrix provides adaptive feedback-based interference cancellation. By continuously estimating and compensating for adjacent channel interference in the frequency domain, the system achieves better channel isolation without requiring excessive bandwidth protection margins, thus maintaining bandwidth efficiency.
Solution Approach 2:
The reception matrix with Kalman filter acts as an intermediary processing stage between signal reception and demodulation. It selectively filters out adjacent channel interference while preserving the desired signal and useful bandwidth, thereby resolving the contradiction between interference reduction and bandwidth efficiency.
3Reliability
If noise management is enhanced in twisted wave systems, then signal-to-noise ratio is improved, but system complexity increases
Solution Approach 1:
The Kalman filter in the reception matrix serves multiple functions simultaneously: it performs noise filtering, interference cancellation, and signal estimation in a unified mathematical framework. This multi-functionality enhances noise management and improves signal-to-noise ratio without adding separate complex processing stages, thereby avoiding increased system complexity.
Data Source
AI summary
A radio communications method includes carrying out, by a transmitter, transmission operations that include generating digital transmission signals carrying symbols to be transmitted and having a predefined time length; and transmitting a radio frequency signal carrying, in successive, non-overlapped time frames or slots having the predefined time length, the digital transmission signals generated. The method further includes carrying out, by a receiver, reception operations that include receiving the radio frequency signal transmitted by the transmitter; processing the received radio frequency signal to obtain a corresponding digital incoming signal; applying an oversampling operation to the digital incoming signal thereby obtaining an oversampled digital incoming signal; detecting successive, non-overlapped time frames/slots with the predefined time length in the oversampled digital incoming signal; and, for each detected time frame/slot, estimating respective symbols carried by the oversampled digital incoming signal in the time frame/slot with a predefined reception matrix incorporating a predefined Kalman filter.