Channel Estimation for Reference Signal Interference Cancellation
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Solution Overview
Problem
Wireless communication networks face interference challenges due to neighboring base stations and other wireless transmitters, which degrade performance and make accurate channel estimation difficult, especially as demand for mobile broadband access increases.
Innovation Solution
The method involves initializing channel estimates for all cells using a previous estimate and iteratively canceling interfering reference signals from non-target cells to improve the accuracy of channel estimation for the target cell, either by canceling only non-target cell signals or both target and non-target cell signals, using a recursive process that filters and updates the channel estimates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If reference signals from neighboring cells are not canceled, then the channel estimation process is simpler and faster, but the channel estimation accuracy deteriorates due to interference from neighboring base stations
Solution Approach 1:
The channel estimation process is segmented into multiple stages: initial channel estimation, interference signal reconstruction, interference cancellation, and refined channel estimation. By dividing the estimation process into distinct segments that handle interference removal separately, the patent achieves higher accuracy without making the entire process fundamentally more complex.
Solution Approach 2:
The patent performs preliminary channel estimation before interference cancellation to reconstruct the interfering reference signals. This preliminary action enables the subsequent cancellation step to be effective, as the interfering signals must be estimated first before they can be removed from the received signal.
2Measurement precision
If iterative interference cancellation is performed for all cells, then channel estimation accuracy improves, but the processing time and computational resources increase
Solution Approach 1:
The patent applies interference cancellation selectively rather than uniformly to all cells. It focuses computational resources on canceling interference from specific neighboring cells that have significant impact on the target cell's channel estimation, performing partial cancellation where it matters most rather than exhaustive cancellation everywhere.
Solution Approach 2:
The iterative interference cancellation process is implemented in periodic stages rather than continuously. The algorithm performs initial estimation, then executes one or more cancellation iterations, and finally produces the refined channel estimate. This periodic structure allows the system to balance accuracy improvements against processing time constraints.
Data Source
AI summary
Various aspects disclosed are directed to improvements to channel estimation through more efficient cancelation of neighboring common reference signals (CRS). Cancelation of CRS from other cells allows the user equipment (UE) a better opportunity for accurately detecting the reference signal of the current cell. Alternative aspects have a recursive element that uses previous estimates as the basis for the current channel estimate. The various aspects of the present disclosure generally have two alternative embodiments: (1) initializing the channel estimation for all cells with a previous channel estimate and cancellation of reference signals of non-target cells to accurately update channel estimate of the target cell; and (2) initializing the channel estimate for all cells with a previous channel estimate and cancelation of reference signals of all cells to accurately estimate residual channel estimate of the target cell and update its channel estimate.