OFDM-PAPR Reduction using Statistical Clipping and Window based Noise Filtering

This paper presents an alternate approach for the iterative clipping and filtering (ICF) method used for the peak-to-averagepower-ratio (PAPR) reduction in OFDM systems. As the resultant in-band noise due to clipping after Z consecutive iterations is approximately proportional to the clipping noise generated in the single iteration, therefore this in-band noise obtained after first iteration is statistically scaled to measure the in-band clipping noise of Z iterations. This approximated in-band clipping noise may be further used for refining the OFDM signal by using statistical clipping (SC) approach [1]. However, the outof-band clipping noise is also a significant drawback for OFDM systems, which restricts the efficiency of transmitter. Therefore, the main focus of presented research work is on the out-of-band clipping noise suppression using the Kaiser window based filtering, in addition to the in-band clipping noise excision using SC method, which may be termed as statistical clipping and window based filtering approach (SC-W). The simulation results are presented to compare the bit-error-rate (BER) performance of the underlying wireless OFDM systems using the ICF, SC, SC-W techniques for PAPR reduction. The complementary cumulative density function (CCDF) and power spectral density (PSD) characteristics are also investigated to infer the results, which depict that the proposed SC-W PAPR reduction technique meets the requirements of transmit mask specified in IEEE 802.11a. The exclusive advantage of SC-W method over ICF approach is low computational complexity and reduced out of band clipping noise.

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