Fast Accurate Fourier Transform for Data Modulation
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Solution Overview
Problem
Conventional OFDM systems face inefficiencies due to the need for large FFT sizes and zero padding, leading to reduced useful data transmission and increased computational costs as data rates increase, and struggle with resolving low-frequency signals.
Innovation Solution
The implementation of the Fast Accurate Fourier Transform (FAFT) with tunable frequency and time windows reduces the need for zero padding, allowing for higher data transmission efficiency and improved resolution of low-frequency signals.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional FFT with zero padding is used to increase sampling rate, then signal interference issues are improved, but the ratio of useful transmitted data is severely reduced and computational costs increase
Solution Approach 1:
The patent applies parameter changes by modifying the FFT algorithm to use a sliding window approach with overlapping segments. Instead of using fixed-size FFT blocks with zero padding, the system varies the window position and size parameters to process signals continuously, thereby maintaining high useful data ratios while achieving the required sampling rate and interference resistance.
Solution Approach 2:
The invention introduces dynamics by implementing a sliding window mechanism where the analysis window moves continuously through the signal. This dynamic approach allows the system to process incoming data streams in real-time without requiring large static buffers or zero padding, thus improving both data transmission efficiency and computational utilization.
2Speed
If larger FFT sizes are used to increase data transmission rate, then data rate is improved, but the proportion of useful transmitted data decreases due to increased zero padding
Solution Approach 1:
The patent applies partial action by processing only the necessary portions of the signal using a sliding window approach. Instead of transforming the entire signal block at once with large FFT sizes, the system processes overlapping segments incrementally, applying FFT only to the active window region. This eliminates the need for excessive zero padding while maintaining high data transmission rates.
3Measurement precision
If conventional FFT is used for signal processing, then computational resources are consumed, but resolution of low-frequency signals is insufficient
Solution Approach 1:
The patent applies segmentation by dividing the continuous signal into overlapping segments using a sliding window. Each segment is processed individually with FFT, allowing the system to achieve high frequency resolution for low-frequency signals through cumulative analysis of multiple segments. This segmented approach improves measurement precision without requiring a single excessively large FFT that would demand prohibitive computational resources.
Data Source
AI summary
Methods and systems for modulating and demodulating data in systems. Bits can be converted into complex-valued symbols. An Inverse Fast Fourier Transform (FFT) can be applied to the complex-valued symbols that represent the bit groups. An FFT time window can be replaced with a time window and a frequency window. A signal comprising the time window and the frequency window can be transmitted. The signal can be converted into a complex-valued symbol. The complex-valued symbols can be converted into bits.