Sparse Discrete Fourier Transform Code Acquisition
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Solution Overview
Problem
Conventional direct sequence spread spectrum (DSSS) systems face challenges in achieving high coding gain and low-latency synchronization, particularly in ultra-wideband communications, due to limitations in coarse code acquisition methods that require excessive computational resources and latency, making them unsuitable for mobile and high-speed applications.
Innovation Solution
The implementation of a method using a spectrally synthesized preamble-codeword and Sparse Discrete Fourier Transform (SDFT) for fast and low-complexity synchronization, which includes generating a preamble-codeword with non-uniformly distributed frequencies, performing SDFT on the received signal, and applying iterative filtering to estimate delay, thereby reducing computational complexity and latency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional direct sequence spread spectrum (DSSS) systems use traditional coarse code acquisition methods, then code acquisition can be achieved, but computational resources and latency are excessive
Solution Approach 1:
The patent extracts only the essential spectral information from the received signal by performing SDFT at specifically selected non-uniform frequencies rather than processing the entire signal spectrum. This extraction approach reduces computational complexity while maintaining synchronization performance by focusing only on frequencies where spectral peaks occur.
Solution Approach 2:
The patent changes the frequency sampling parameters by using non-uniformly distributed frequencies selected based on expected spectral peak locations rather than uniform frequency sampling. This parameter change enables faster acquisition by concentrating computational resources at critical frequencies where signal energy is concentrated.
2Loss of time
If conventional DSSS systems use traditional synchronization methods, then synchronization can be achieved, but latency is excessive for mobile and high-speed applications
Solution Approach 1:
The patent performs preliminary action by pre-selecting the non-uniform frequency locations where spectral peaks are expected to occur before signal processing. This preliminary preparation enables the system to directly process only relevant frequencies during synchronization, significantly reducing latency while maintaining reliability through the use of a correlation peak detector.
3Measurement precision
If conventional DSSS systems use full-spectrum processing for code acquisition, then accurate delay estimation can be achieved, but power consumption and computational resources are excessive
Solution Approach 1:
The patent extracts only the necessary spectral components at non-uniform frequencies where signal energy is concentrated, rather than processing the entire frequency spectrum. This extraction maintains delay estimation accuracy by focusing on critical frequencies while dramatically reducing power consumption and computational requirements.
Solution Approach 2:
The patent applies partial action by performing Fourier transform only at a subset of non-uniform frequency points rather than across the entire spectrum. This partial processing approach provides sufficient delay estimation accuracy for synchronization while reducing power consumption and computational complexity.
Data Source
AI summary
A code acquisition module for a direct sequence spread spectrum (DSSS) receiver includes: a Sparse Discrete Fourier transform (SDFT) module configured to perform an SDFT on a finite number of non-uniformly distributed frequencies comprising a preamble of a received DSSS frame to calculate Fourier coefficients for the finite number of non-uniformly distributed frequencies; a multiplier configured to multiply the Fourier coefficients for the finite number of non-uniformly distributed frequencies of the received DSSS frame by complex conjugate Fourier coefficients for the finite number of non-uniformly distributed frequencies to generate a cross-correlation of the received DSSS frame and the complex conjugate Fourier coefficients; and a filter module configured to input the cross-correlation and output a delay estimation for the received DSSS frame.