Symbol-Level Equalizer Using Adaptive IIR Code Detection
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Solution Overview
Problem
Chip-level equalizers do not effectively account for spreading code usage distribution in receivers, leading to suboptimal performance in mitigating Inter-Symbol Interference (ISI) and Multi-user Access Interference (MAI) due to their assumption of independent and identically distributed chips.
Innovation Solution
The implementation of a symbol-level equalizer that uses spreading code usage information, obtained through a code detector, to adjust the equalization process, accounting for the actual spreading code distribution and improving the separation of data streams by incorporating adaptive Infinite Impulse Response (IIR) filtering and SNR matrix analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a chip-level equalizer is used to mitigate ISI and MAI, then the equalization process is simplified, but the performance deteriorates because the spreading code usage distribution is not accounted for
Solution Approach 1:
The patent transitions from a static chip-level equalization approach to a dynamic symbol-level equalization approach that adapts to the actual spreading code usage distribution. The symbol-level equalizer dynamically adjusts its operation based on the detected spreading codes, allowing it to handle varying code usage patterns effectively while maintaining manageable complexity through structured processing stages.
Solution Approach 2:
The patent elevates the equalization process from the chip level to the symbol level, adding a new dimension of processing. This dimensional change allows the equalizer to operate on complete symbols rather than individual chips, enabling it to account for spreading code usage distribution and achieve better mitigation of ISI and MAI while maintaining computational feasibility.
2Measurement precision
If a symbol-level equalizer accounting for spreading code usage is implemented, then the detection performance is improved, but the device complexity increases
Solution Approach 1:
The patent segments the equalization process into distinct functional stages: spreading code detection, channel estimation, and symbol-level equalization. This segmentation allows each component to be optimized independently and simplifies the overall implementation by dividing the complex task into manageable parts, reducing the effective complexity while maintaining high detection performance.
Solution Approach 2:
The patent introduces spreading code usage information as an intermediary element that bridges the gap between the received signal and the equalization process. This intermediary allows the symbol-level equalizer to incorporate knowledge of the spreading codes without directly processing the complex chip-level signals, thereby improving accuracy while managing complexity through information transformation.
Data Source
AI summary
Code detection to assist a symbol-level equalizer in a receiver is described. In an embodiment, code detection uses adaptive Infinite Impulse Response (IIR) filtering to determine spreading code usage information and active code channels in a received signal. The spreading code usage information indicates if a spreading code associated with a code channel is among spreading codes used in the received signal. In another embodiment, the spreading code usage information is determined based on a forgetting factor associated with the filtering of a symbol power associated with the code channel.