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The Fast Fourier Transform (FFT) processes 5G signals, important for OFDM (Orthogonal Frequency-Division Multiplexing) modulation. Verifying FFT libraries ensures accurate and efficient transformation of data from the time domain to the frequency domain, crucial for managing 5G bandwidth.
##### Necessity of Validation
Segmenting processes into Time Domain and Frequency Domain through the Fast Fourier Transform (FFT) is a critical division. As most subsequent processing steps do not cross between these domains, accurately determining the optimal input dB level is essential for optimal performance. Additionally, this control of input dB levels is integral to managing power consumption within the system, ensuring both efficiency and effectiveness.
##### Validation Methodology
![](Pasted%20image%2020240715184630.png)
This system automates the generation, processing, and analysis of signal vectors using MATLAB and Ceva. It starts by creating various signal types including random sequences and exponential signals with T00_vec_gen.m. These signals are then processed through Fast Fourier Transforms (FFT) in both MATLAB and Ceva environments, generating time-domain signal vectors. Subsequent steps involve comparing these vectors using T03_plot_compare.m to visually assess discrepancies and calculating the Signal-to-Noise Ratio (SNR) using T04_snr_db.m to evaluate performance differences between the two processing environments.
##### Validation Outcomes
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The graph and the formula together analyze the SNR by comparing the deviation of the FFT outputs between the Ceva and MATLAB implementations. The formula specifically calculates the SNR as: $\text{SNR dB} = 10 \log_{10} \sum_{k=0}^{N} \left( \frac{|\text{fft}_m(k)|^2}{|\text{fft}_m(k) - \text{fft}_c(k)|^2} \right)$
where:
- $\text{fft}_m(k)$ is FFT results from MATLAB (considered as the reference or non-corrupted),
- $\text{fft}_c(k)$ is FFT results from CEVA.
The calculation evaluates how closely the Ceva FFT results match the MATLAB results. The SNR peaks at an input dB of 68.69, indicating that this is the optimal input level for Ceva to match the MATLAB performance most closely, with diminishing returns at higher dB levels.
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