FBMC/OQAM Interference Cancellation via Iterative Log-Likelihood Estimation
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Solution Overview
Problem
The FBMC/OQAM system faces challenges with residual inherent interference, which complicates channel estimation and increases implementation complexity, affecting spectral efficiency and design flexibility, especially in multi-path fading channels.
Innovation Solution
A method for interference cancellation is introduced, involving calculating mean and variance values of the received signal, estimating log-likelihood ratios, and performing iterative hard decisions to output data bits, which reduces residual ISI and ICI, thereby improving spectral efficiency and design flexibility.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If FBMC/OQAM system is used to achieve high spectral efficiency and power efficiency, then spectral efficiency and power efficiency are improved, but residual inherent interference increases channel estimation complexity and implementation complexity
Solution Approach 1:
The patent applies preliminary action by performing interference cancellation before channel estimation. The received signal is processed to cancel inherent interference (ISI and ICI) using estimated channel responses and interference coefficients calculated from filter bank parameters, thereby simplifying subsequent channel estimation operations and reducing overall system complexity
Solution Approach 2:
The patent segments the received signal processing into distinct stages: interference cancellation stage and channel estimation stage. By separating these functions and processing interference components (real part and imaginary part) independently using different mathematical operations, the system reduces the complexity of each individual stage while maintaining overall performance
2Reliability
If iterative interference cancellation is performed to eliminate residual interference, then interference cancellation performance is improved, but computational complexity increases
Solution Approach 1:
The patent implements dynamic iterative interference cancellation where the number of iterations and processing depth can be adjusted based on channel conditions and performance requirements. The system dynamically updates interference coefficients and channel responses across iterations, allowing flexible trade-off between cancellation performance and computational complexity
Solution Approach 2:
The patent employs feedback mechanisms where channel estimation results from previous iterations are used to improve interference cancellation, which in turn provides cleaner signals for updated channel estimation. This feedback loop continuously refines both channel knowledge and interference suppression, improving performance while managing complexity through iterative convergence
Data Source
AI summary
The present disclosure provides a method for interference cancellation which includes: calculating a mean value and a variance value of a received signal to obtain statistics information of the received signal; calculating an estimating log-likelihood ratio using the statistics information of the received signal; calculating a decoding log-likelihood ratios of the received signal using the estimating log-likelihood ratio of the received signal, and performing calculations to update the statistics information of the received signal; repeating the above steps for a pre-determined number of times, performing hard decisions on the decoding log-likelihood ratios of the received signal, and outputting data bits obtained from the hard decision. The present disclosure also provides an apparatus, an auxiliary method, a base station and a terminal device for interference cancellation. The mechanism of the present disclosure can reduce the impact of inherent interference in the FBMC/OQAM system on system performances, and increase spectral efficiency and design flexibility of the FBMC/OQAM system.