Beyond Nyquist: efficient sampling of sparse bandlimited signals
IEEE Transactions on Information Theory
Compressed-Sensing-Enabled Video Streaming for Wireless Multimedia Sensor Networks
IEEE Transactions on Mobile Computing
IEEE Transactions on Information Theory
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The use of an under-sampling technique is presented in this paper allowing the reconstruction of the sparse information transmitted over Orthogonal Frequency Division Multiplexing (OFDM). The inherent data sparsity and the properties of the Discrete Fourier Transform employed by OFDM modulation allows the estimation of several samples from others that have already been retrieved at the side of the receiver. The Forward Error Correction techniques employed can further assist the information recovery with fewer samples. The presented method allows the estimation of up to 1/4 of the values required by the Discrete Fourier Transform at the side of the receiver from other values that have already been sampled. The proposed method can save buffer memory size for sample storage by up to 25% while the power consumption of the Analog Digital Converter at the side of the receiver is also reduced by slowing down the sampling rate at known time intervals. The presented simulations demonstrate the efficiency of different error correcting schemes like Viterbi and Reed-Solomon for information recovery with the proposed method.