Impairment Correlation Lookup for Low-Complexity CDMA Receivers
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Solution Overview
Problem
Existing wireless receivers face challenges in efficiently estimating instantaneous impairment correlations due to high processing speeds and limited processing resources, leading to noisy estimates and increased computational complexity, especially in CDMA systems with multi-path interference.
Innovation Solution
The implementation of an impairment processor using look-up tables to reduce computational complexity by iteratively computing partial impairment correlations and combining them, replacing complex calculations with look-up operations, and utilizing pre-computed pulse correlation estimates to determine impairment correlations between sample streams.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional parametric approaches are used to estimate impairment correlations, then accurate instantaneous impairment correlation estimates are achieved, but processing resources are insufficient and computational complexity is high
Solution Approach 1:
The patent pre-computes and stores pulse correlation values for all possible delay offset differences in look-up tables before actual signal processing. This preliminary action eliminates the need for complex real-time calculations during impairment correlation estimation, thereby reducing processing resource requirements while maintaining estimation accuracy.
Solution Approach 2:
The patent replaces complex analytical calculations with simplified look-up table queries. By copying pre-computed pulse correlation values into easily accessible tables, the system avoids performing resource-intensive mathematical operations during runtime, thus reducing computational complexity while preserving the accuracy of impairment correlation estimates.
2Productivity
If non-parametric approaches with filtering are used to estimate impairment correlations, then processing speed is improved, but the estimates become more of a time average rather than instantaneous correlations
Solution Approach 1:
The patent pre-computes pulse correlation values for all possible delay configurations and stores them in look-up tables. During operation, the system simply queries these tables using current delay offsets, achieving both high processing speed and instantaneous accuracy without requiring temporal filtering that would average out time-varying correlations.
Solution Approach 2:
The patent replaces the mechanical filtering operation (which averages correlations over time) with a direct look-up table query approach. This substitution eliminates the need for filtering while maintaining processing speed, as the system directly retrieves the current instantaneous impairment correlation values based on present delay offsets without computing averages over previous time intervals.
3Productivity
If look-up tables are used to compute impairment correlations, then processing requirements are reduced, but computational complexity increases due to table management
Solution Approach 1:
The patent creates a universal look-up table structure that serves multiple purposes: storing pulse correlation values, providing fast random access for any delay offset combination, and enabling efficient computation of impairment correlations between any pair of sample streams. This single multi-functional table structure reduces overall system complexity despite the added management requirements.
Solution Approach 2:
The patent organizes the look-up table using delay offset differences as indices, transforming the complex multi-dimensional correlation computation into a simple one-dimensional table lookup. By changing the parameter organization from storing full correlation matrices to storing values indexed by delay differences, the system reduces memory access complexity and simplifies table management while maintaining processing efficiency.
Data Source
AI summary
The impairment processor described herein uses a look-up table operation to reduce the computational complexity associated with determining an impairment correlation between first and second sample streams for an interference rejection receiver. One exemplary impairment processor iteratively computes multiple partial impairment correlations based on values selected from look-up table(s), and combines the partial impairment correlations to obtain a final impairment correlation between the first and second sample streams. During each iteration, the impairment processor computes a pair of delay offsets corresponding to the respective processing and path delays of the first and second sample streams, computes an index value as a function of a difference between the pair of delay offsets, selects a pre-computed value from the look-up table based on the index value, determines a pulse correlation estimate based on the selected pre-computed value, and determines the partial impairment correlation for that iteration based on the pulse correlation estimate.