Waveform Correlation Calculator Complexity Reduction
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Solution Overview
Problem
The high computational complexity of conventional multicode detectors in CDMA systems, which grows exponentially with the number of codes, hinders efficient suppression of Inter-symbol Interference (ISI) and Multiple Access Interference (MAI) due to channel dispersion, especially in systems using low spreading factors and multicode transmission.
Innovation Solution
A multicode receiver apparatus that reduces computational complexity by reusing channel coefficients and net channel correlations across multiple symbol periods and processing windows, and exploiting Hermitian symmetry to compute waveform correlations, thereby simplifying the calculation of waveform correlations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional multicode detectors compute waveform correlations for each processing window independently, then detection accuracy is maintained, but computational complexity grows exponentially with the number of codes
Solution Approach 1:
The patent precomputes waveform correlations for a reference processing window and stores them for later reuse. This preliminary computation avoids redundant calculations in subsequent processing windows, significantly reducing computational complexity while maintaining detection accuracy through the use of these precomputed values.
Solution Approach 2:
The precomputed waveform correlations serve multiple processing windows simultaneously. A single set of computed correlations is reused across multiple windows, making the computation universal rather than window-specific, thereby reducing the overall computational burden exponentially.
2Reliability
If waveform correlations are computed for every processing window, then interference suppression performance is optimized, but processing time increases
Solution Approach 1:
Waveform correlations are computed in advance for a reference window and stored for reuse. This preliminary computation eliminates the need to recalculate correlations for every processing window, significantly reducing processing time while maintaining interference suppression performance through the use of these precomputed correlation values.
Solution Approach 2:
The patent maintains continuous interference suppression performance by reusing precomputed waveform correlations across multiple processing windows. This approach ensures that the useful action of interference suppression continues efficiently without the time penalty of repeated full computations, achieving both performance optimization and time reduction.
3Productivity
If low spreading factor and multicode transmission are used to increase data rates, then throughput is improved, but sensitivity to multi-path dispersion and interference increases
Solution Approach 1:
By precomputing and storing waveform correlations before processing multiple processing windows, the system reduces computational complexity and enables more robust interference suppression. This preliminary computation allows the system to maintain reliability in low spreading factor and multicode transmission scenarios where interference suppression is critical.
Solution Approach 2:
The system uses precomputed waveform correlations to provide feedback-based interference suppression in multicode detection. This feedback mechanism helps mitigate the increased sensitivity to dispersion and interference that occurs with low spreading factors and multicode transmission, thereby maintaining reliability while achieving high data rates.
Data Source
AI summary
A method and apparatus for reducing the complexity of waveform correlation computations used by a multicode receiver is described herein. One exemplary multicode receiver includes a despreading unit, channel estimator, and waveform correlation calculator. The despreading unit despreads a received multicode signal to generate despread symbols. The channel estimator estimates channel coefficients associated with the despread symbols. The waveform correlation calculator determines waveform correlations between the transmitted symbols in successive processing windows that span two or more symbol periods and that overlap in time. To reduce the computational complexity associated with computing waveform correlations, the calculator may reuse channel coefficients and/or net channel correlations for multiple symbol periods and/or processing windows. The calculator may also reduce complexity by reusing one or more waveform correlations from a previous processing window as waveform correlations for one or more subsequent processing windows and/or by exploiting the Hermitian symmetry of the waveform correlation matrix.