Interference Cancellation Efficiency Estimation in Wireless Systems
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Solution Overview
Problem
Conventional methods for estimating interference cancellation efficiency in wireless communication systems overlook the noise addition and desired signal energy removal during interference cancellation, leading to overly optimistic performance estimates that do not account for the presence of other signals.
Innovation Solution
A wireless communication apparatus estimates interference cancellation efficiency as a joint function of signal parameters for the interfering signal and additional signals present, considering multiple interferers and desired signals in each interference cancellation processing iteration.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional interference cancellation estimation methods are used, then the estimation process is simple and fast, but the accuracy of cancellation efficiency estimation is poor because noise addition and desired signal energy removal are overlooked
Solution Approach 1:
The estimation process is segmented into multiple iterations, where each iteration estimates cancellation efficiency for one interfering signal while considering the presence of other signals. This allows accurate accounting of noise addition and desired signal energy removal for each cancellation operation without requiring a completely complex new approach.
Solution Approach 2:
The method performs preliminary estimation of cancellation efficiency before actual interference cancellation processing. This preliminary estimate accounts for the expected noise addition and desired signal energy removal, allowing the system to configure receiver operations optimally before the actual cancellation occurs.
2Reliability
If conventional cancellation efficiency estimation is used, then the receiver operations can be configured quickly, but the performance gains are not fully realized due to overly optimistic estimates
Solution Approach 1:
The system performs self-configuration based on its own estimated cancellation efficiency. By autonomously determining the expected performance impact of interference cancellation and configuring receiver operations accordingly, the system ensures reliable performance gain realization without requiring external calibration or lengthy setup procedures.
3Productivity
If interference cancellation is performed without accurate efficiency estimation, then processing is faster, but receiver operations are not optimally configured leading to suboptimal performance
Solution Approach 1:
The system performs preliminary cancellation efficiency estimation and receiver configuration before actual interference cancellation processing. This preliminary action ensures that receiver operations are optimally configured based on expected performance impacts, while the actual cancellation processing remains efficient.
Solution Approach 2:
The system changes receiver operation parameters based on the estimated cancellation efficiency. By adjusting parameters such as signal combining weights and interference suppression levels according to the predicted efficiency, the system achieves optimal performance without sacrificing processing speed.
Data Source
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AI summary
Estimation of interference cancellation efficiency as disclosed herein advantageously accounts for the real-world or effective performance of interference cancellation by estimating the interference cancellation efficiency expected for a signal targeted for interference cancellation as a joint function of signal parameters for the targeted signal and one or more other signals that will remain after such cancellation. For example, a wireless communication apparatus, such as a user equipment configured for operation in a cellular communication network, is configured to estimate the interference cancellation efficiency expected for an interfering signal received in conjunction with a desired signal, based on a joint function of signal parameters for the interfering signal and the desired signal. Such processing extends directly, of course, to the consideration of multiple interferers and/or multiple desired signals, and may be carried out in each of two or more interference cancellation processing iterations.