Pruned-DFT-s-FBMC_Matlab-master: PAPR Reduction in FBMC Systems Using Pruned DFT Technique

This article discusses the application of pruned DFT technique in FBMC systems for suppressing Peak-to-Average Power Ratio (PAPR). The technique effectively reduces nonlinear distortion in the system by controlling signal amplitude peaks. In FBMC systems, high PAPR represents a common challenge that can lead to signal distortion and transmission errors, making it a critical issue for wireless communication systems. The pruned DFT approach offers an efficient method to enhance system performance and reliability while maintaining signal integrity.

The core algorithm of pruned DFT technique involves dividing the signal into multiple sub-signals and applying DFT transformation to each sub-signal. In MATLAB implementation, this typically uses the fft() function with proper windowing and segmentation. Following the transformation, frequency-domain clipping is performed on each sub-signal to reduce amplitude peaks - this can be implemented using threshold-based amplitude limiting functions. The processed sub-signals are then recombined using inverse DFT (ifft()) to form the complete output signal. This process effectively lowers PAPR without significant performance degradation, maintaining bit error rate (BER) performance while improving power amplifier efficiency.

While pruned DFT technique improves system performance, it introduces additional computational overhead. The MATLAB implementation should carefully consider computational complexity and power consumption factors. Key optimization strategies include implementing efficient DFT pruning algorithms, using optimized FFT sizes, and balancing clipping thresholds to minimize performance impact. The code should include complexity analysis functions to evaluate real-time processing requirements and ensure overall system optimization.