Research On The Fast Compressed Reconstuction Of Wireless Channel State Information

Compressed sensing (CS) is a new signal acquisition method. It enables signals to be sampled below the Nyquist rate given that the signal is sparse, with an accurate reconstruction. Because of the multipath effect, the channel state information in delay domain has sparsity. When we apply CS theory into channel estimation of OFDM system, the pilots’ number decreases, and the accuracy increases.The traditional CS theory doesn’t concern the natural property of the sparse signal, such as block-sparstiy. Applying with this, we can improve the recovery accuracy and promote the efficiency. However, most of the exist reconstruction algrithms, such as BOMP can only get wonderful performance when the lengths of nonzero blocks are the same, and the intervals between them are integral multiple of the length. So, we propose a modified BOMP algorithm for the more general block sparse singals in this paper. And we combine the reconstuction of block-sparsity singal with DPSS basis expand model to estmate the channel state information in time-delay domain. In this way, we can overcome the energy leak of Fourier basisi expand model, and reduce the sensitivity to Doppler shift.