A New Approach to Iterative Clipping and Filtering PAPR Reduction Scheme for OFDM Systems

While achieving reduced/good peak-to-average power (PAPR) in orthogonal frequency division multiplexing (OFDM) systems is attractive, this must not be performed at the expense of the transmitted signal with over-reduced signal power, as it leads to degraded bit error ratio (BER). We introduce a uniform distribution approach to solving the PAPR reduction problem of OFDM signals and then use Lagrange multiplier (LM) optimization to minimize the number of iterations involved in an adaptive fashion. Due to the nonlinear attenuation of the PAPR reduction scheme, we compensate the output signal using a correlation factor that minimizes the error floor in the in-band distortion of the clipped signal using the minimum mean square error method so as to improve the BER performance. Three different methods are introduced each enabling PAPR reduction by clipping followed by filtering with no direct dependence on a clipping ratio parameter. We find that our approach significantly reduces the PAPR of the OFDM signals (especially with LM optimization) better than the conventional adaptive iterative clipping and filtering operating without LM optimization. Based on our proposed methods, we additionally outline two simple steps for achieving perfect PAPR reduction (i.e., 0 dB). We also evaluate the performance of the three new models over high power amplifier (HPA) for completeness; the HPA is found to induce negligible BER degradation effects on the processed signal compared with the unprocessed signal.