Improving the stability of DFT error recovery codes by using sparse oversampling patterns

This paper proposes a new approach for improving the stability of discrete Fourier transform (DFT) codes for burst error recovery. The decoding algorithms for DFT codes become unstable in burst error situations because of the ill-conditioned matrices that arise in the recovery algorithms. This paper proposes a collection of oversampling patterns instead of consecutive zero oversampling and proves the ability to recover the original signal. Also the effects of these oversampling patterns on the stability of recovery algorithms are studied. This paper proves that these patterns greatly improve the stability of these algorithms in burst error situations. The effect of some special kinds of sparse error patterns on the proposed method is analyzed and a method is suggested to avoid this situation. The simulation results include different situations and error patterns and their effect on DFT codes. These experimental results also show the robustness of the proposed method against the quantization noise and burst of errors.