A compressed sensing（CS） based channel estimation algorithm is proposed by using the delay-Doppler sparsity of the fast fading channel.A compressive basis expansion channel model with sparsity in both time and frequency domains is given.The pilots in accordance with a novel random pilot matrix in both time and frequency domains are sent to measure the delay-Doppler sparsity channel.The relatively nonzero channel coefficients are tracked by random pilots at a sampling rate significantly below the Nyquist rate.The sparsity channels are estimated from a very limited number of channel measurements by the basis pursuit algorithm.The proposed algorithm can effectively improve the channel estimation performance when the number of pilot symbols is reduced with improvement of throughput efficiency.
In this letter, the problem of blind source separation of Multiple-Phase-Shift-Keying (MPSK) digital signal is considered. The geometry of received MPSK signals constellation is exploited. The column vectors of received signals can be regarded as the points of hyper-cube. All the possible distinct vectors of received signals are found by clustering, and mixing matrix and sources are estimated by searching out the pairing vectors and eliminating redundant information in all possible distinct vectors. Simulation results give the polar diagram of estimated original signals. They show that the proposed algorithm is effective when the original signals is Quadrature-Phase-Shift-Keying (QPSK) or 8-Phase-Shift-Keying (8PSK).
