Reliable Data Aided Sparsity-Aware Approaches to Clipping Noise Estimation in OFDM Systems

In this paper, we propose reliable data aided sparsity-aware approaches to estimate and cancel the clipping noise in OFDM systems. Those are motivated by the fact that reliable data can be exploited to estimate the clipping noise in a successive interference cancellation (SIC) manner. When the clipping noise has relatively large support, a data non-aided method is not class enough to estimate the clipping noise well due to the compressed sensing (CS) based measurement shortages. Simulation results demonstrate the effectiveness of our proposed methods in estimating the clipping noise and approaching the performance with no clipping noise.