Adaptive Unbiased Least Square Algorithm for CDMA Interference Mitigation
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Solution Overview
Problem
Conventional methods for mitigating inter-symbol interference (ISI) and inter-chip interference (ICI) in CDMA downlink communication systems, such as least mean square (LMS) algorithms, produce biased signals and require frequent matrix inversion, which is complex and inefficient, especially when channel conditions change rapidly.
Innovation Solution
An adaptive unbiased least square (LS) algorithm that iteratively calculates the inverse of the channel matrix without actual inversion, updating the weights based on recent channel information to mitigate interference effectively, reducing computational complexity and maintaining signal quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If conventional LMS algorithms are used to mitigate interference, then computational complexity is reduced by avoiding matrix inversion, but signal quality deteriorates due to biased signal production
Solution Approach 1:
The patent applies matrix inversion to the correlation matrix R to obtain the optimal weight vector w = R^(-1)p, directly inverting the mathematical approach rather than avoiding inversion. This produces unbiased signal estimates while the iterative update method keeps computational complexity manageable by only inverting small-dimensional matrices at each step.
Solution Approach 2:
The patent uses an adaptive iterative algorithm that dynamically updates the weight vector as channel conditions change. The weights are continuously adapted using the update rule w(n+1) = w(n) + μe(n)p*, allowing the system to maintain optimal performance in time-varying environments while avoiding the need to recompute the full inverse matrix.
2Measurement precision
If direct matrix inversion is performed to achieve unbiased signal recovery, then signal quality improves, but computational complexity and processing time increase significantly
Solution Approach 1:
The patent pre-calculates and stores the inverse of the correlation matrix R^(-1) when the channel is relatively stable. This preliminary computation allows for rapid signal recovery without repeated full matrix inversions, reducing computational complexity while maintaining unbiased signal quality through the stored inverse matrix.
Solution Approach 2:
The patent performs full matrix inversion periodically or when significant channel changes are detected, rather than continuously. Between these periodic updates, the system uses the previously computed inverse or iterative updates, reducing overall computational complexity while maintaining signal quality when channel conditions permit.
3Adaptability or versatility
If frequent matrix inversion is performed to adapt to rapidly changing channel conditions, then adaptability improves, but processing time and computational load increase
Solution Approach 1:
The patent employs a dynamic adaptive algorithm that updates weights iteratively based on current error signals and channel estimates. This allows continuous adaptation to changing channel conditions without requiring frequent full matrix inversions, maintaining high adaptability while reducing processing time through incremental updates.
Solution Approach 2:
The patent uses feedback from the error signal e(n) = d(n) - y(n) to continuously adjust the weight vector. This feedback mechanism enables the system to adapt to channel changes in real-time using computationally efficient update rules, achieving high adaptability without the time cost of frequent full matrix inversions.
Data Source
AI summary
A multipath wireless communication is processed to recover a transmitted data signal without performing a direct matrix inversion (DMI). First, the multipath wireless communication is received. Then HHH and HHH values associated with the multipath wireless communication are determined. Weights based on HHH and HHH associated with the received data signal may then be determined and used to recover the transmitted data signal from the received multipath wireless communication.