Channel Estimation Algorithm Based on Compressive Sensing for NC-OFDM Systems in Cognitive Radio Context

Abstract As an effective spectrum utilization technology, non-contiguous orthogonal frequency division multiplexing (NC-OFDM) can be used in the environment of discrete spectrum. Compared with the traditional algorithm, channel estimation algorithm based on compressive sensing can get better performance with fewer pilots and improve the effectiveness of the system spectrum. In NC-OFDM systems, channel estimation algorithm based on OMP (orthogonal matching pursuit) has been proposed, but it is the first time that SAMP (sparsity adaptive matching pursuit) algorithm is applied to channel estimation for NC-OFDM systems. Moreover, for the reconstruction time-consuming of SAMP algorithm is too large, MAMP (modified adaptive matching pursuit) algorithm as an improved SAMP algorithm is introduced. And it can be seen that the computing speed and reconstruction accuracy has been improved.

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