Partial Interference Cancellation for TD-SCDMA Channel Estimation
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Solution Overview
Problem
In TD-SCDMA intra-frequency networks, existing methods fail to effectively perform joint channel estimation, leading to interference and incorrect channel window activation, which hampers joint cell detection due to poor inter-relativity of Basic Midamble Codes (BMC) and interference cancellation.
Innovation Solution
The implementation of a Partial Interference Cancellation (IC) method using multiple branches for channel estimation, where each branch processes received signals through Partial IC units, channel estimation units, and recovery units, with coefficients β adjusting with iterations to subtract interference and refine channel responses, and noise depression techniques to enhance signal recovery.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If independent channel estimation is performed in each cell using BMC, then channel estimation can be done separately, but interference from adjacent cells occurs and channel window activation is wrongly detected
Solution Approach 1:
The patent segments the channel estimation process into multiple iterations, where in each iteration, interference from specific adjacent cells is canceled separately. The received signal is divided into components from different cells, and interference cancellation is performed iteratively for each cell component, allowing independent processing while reducing overall interference.
Solution Approach 2:
The patent converts the harmful interference from adjacent cells into useful information by using the known BMC sequences of adjacent cells to estimate their channel responses. These estimated interference signals are then subtracted from the received signal, transforming the harmful interference into a cancellable component that improves the overall channel estimation accuracy.
2Object-affected harmful factors
If joint channel estimation is performed to reduce interference, then interference cancellation improves, but the complexity of the estimation process increases
Solution Approach 1:
The patent implements joint channel estimation through periodic iterative processing. In each iteration, the algorithm performs channel estimation for multiple cells, cancels interference, and refines the estimates. This periodic iterative approach breaks down the complex joint estimation into manageable cycles, reducing computational complexity while maintaining interference cancellation benefits.
Solution Approach 2:
The patent applies partial interference cancellation where only the dominant interfering cells are targeted in each iteration rather than attempting to cancel all interference simultaneously. The algorithm identifies and cancels interference from the strongest adjacent cells first, then proceeds to weaker ones in subsequent iterations, making the process more tractable while still achieving significant interference reduction.
3Adaptability or versatility
If BMC code number is broadcasted in present and adjacent cells, then cell recognition is enabled, but inter-relativity of BMC channel training remains poor
Solution Approach 1:
The patent uses feedback from the channel estimation process to improve BMC training effectiveness. By estimating channels from multiple cells including adjacent cells, the system gains feedback information about the actual channel conditions and interference patterns. This feedback is used to refine the channel estimation and improve the reliability of BMC-based channel training in subsequent operations.
Data Source
AI summary
This invention discloses a channel estimation method for partial IC in TD-SCDMA intra-frequency cell, Specifically IC or de-correlation multi-user detection is utilized. Partial IC is implemented to realize the joint detection of the channel in several intra-frequency cells. As to n cells, the detailed procedures go as follows:At first, n 2×128 memories are established, just as s1, s2, s3 . . . sn, in order to store the complex serial. Midamble codes of the received signal constitute the 128-chip data. Step 1: The data taken from Midamble codes of the received signals undergo the Partial IC process of the residual past in the first cell. The process of channel estimation in the first cell is undertaken. Afterwards, the received signals of UE from the 1st cell are recovered. The channel of the other cells is estimated from the received signals and the received signals of corresponding Midamble code is recovered to repeat the above procedures, until the completion of the process of the received signal, and it comes to Step (n+1). Iteration once is finished from Step 1 to Step (n+1), in which n processes are involved and one process is correspondent to one cell. The iteration after m times will finalize the channel estimation.