Elimination of Noise Distortion for OFDM Systems by Compressed Sensing Based on Distance Metric

The clipping method is often applied to reduce the peak to average ratio (PAPR) of orthogonal frequency division multiplexing (OFDM). However, this method will cause in-band distortion, which increases the bit error rate (BER) at the receiver. Clipping distortion recovery techniques can be used to alleviate the problem. This paper proposes a clipping noise recovery scheme based on distance metric (dmCNR). The proposed method estimates the clipping position in the frequency domain, and applies it to the reconstruction algorithm of compressed sensing (CS), which greatly reduces the system complexity. Meanwhile, the method selects the reliable sub-carrier data iteratively to improve the accuracy of clipping distortion recovery. Simulation results verify that the proposed method exhibits good BER performance.

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