Adaptive Weighting for PIC Channel Estimation
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Solution Overview
Problem
The existing weight determining method in Pilot Interference Canceller (PIC) systems for CDMA communication systems uses a constant weighting factor, leading to suboptimal performance in terms of Mean Square Error (MSE), which results in large errors and inefficient pilot interference cancellation.
Innovation Solution
A method and apparatus that apply an adaptive weighting factor using a weight algorithm with a minimum Mean Square Error (MSE) in a short-term average to the output of the channel estimator, improving the channel estimation accuracy by over-sampling, generating a Pseudo Noise sequence, despreading, and determining an optimized weighting factor for channel estimation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a constant weighting factor is used in the PIC channel estimator, then the device complexity is reduced and ease of operation is improved, but the measurement precision and reliability of channel estimation deteriorate due to large Mean Square Error
Solution Approach 1:
The patent applies dynamics by transitioning from a static constant weighting factor to a dynamic adaptive weighting factor that changes over time. The weighting factor is updated using a recursive algorithm that adapts to instantaneous channel conditions, thereby improving channel estimation accuracy while maintaining reasonable computational complexity through efficient recursive calculations.
Solution Approach 2:
The patent changes the parameter of the weighting factor from a fixed constant to a time-varying adaptive parameter. The weighting factor is continuously adjusted based on instantaneous signal conditions and past estimation errors, allowing the system to optimize channel estimation accuracy for varying channel conditions without requiring complex reconfiguration.
2Reliability
If an adaptive weighting factor with minimum MSE is applied, then the reliability and measurement precision of channel estimation are improved, but the use of energy and computational resources increases due to real-time weight optimization
Solution Approach 1:
The patent implements feedback by using the channel estimation error as a feedback signal to continuously adjust the weighting factor. The recursive least squares algorithm utilizes past estimation errors and current signal conditions to optimize the weighting factor, creating a closed-loop system that improves reliability while avoiding exhaustive search methods that would consume excessive energy.
Solution Approach 2:
The patent applies preliminary action by pre-calculating and storing correlation values and other statistical parameters during training periods or low-activity phases. These pre-computed values are then reused during active communication periods, reducing real-time computational energy requirements while maintaining high reliability in channel estimation and pilot interference cancellation.
Data Source
AI summary
A method and an apparatus apply an adaptive weight in a wireless communication system. In the method, channel estimation is performed. A weighting factor that reduces a Mean Square Error (MSE) is determined with respect to a channel in a specific section. A channel estimate value is multiplied by the weighting factor.