Compressed Sensing Based Recovery of Nonlinearly Distorted OFDM Signals
نویسندگان
چکیده
The high peak to average power ratio (PAPR) of the transmit signal is a major drawback in orthogonal frequency division multiplexing (OFDM) systems. A high PAPR can lead to saturation in the power amplifier and consequently distorts the signal. In this paper, we propose a method based on compressed sensing (CS) to recover nonlinearly distorted OFDM signals. The method exploits pilot tones inserted in the OFDM signal for channel estimation. The key steps are a CS-based estimation of clipping noise and its removal from the received OFDM signal. In our work, we also include the effect of nonlinear distortion on channel estimation. Numerical results show that the proposed CS-based method significantly improves the bit error rate (BER) performance over previously proposed techniques which iteratively estimate the clipping noise and cancel it from the received signal.
منابع مشابه
Joint Channel Estimation and Nonlinear Distortion Recovery Based on Compressed Sensing for OFDM Systems
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