Study Of Compressed Sensing Based Sparse Channel Estimation And Pilot Optimization In MIMO-OFDM Systems

As a combination of multiple input multiple output(MIMO)and orthogonal frequency division multiplexing(OFDM)systems,multiple input multiple output-orthogonal frequency division multiplexing(MIMO-OFDM)system has high band utilization and can effectively combat multipath effects in wireless channels.Since wireless multipath channels are often sparse in time domain,the traditional channel estimation method can not fully utilize the sparse characteristics of wireless channels,and the performance of channel estimation for sparse channel is poor.The application of compressed sensing(CS)technology to sparse channel estimation can reduce the number of pilots and increase spectrum utilization.The pilot allocation employed in traditional channel estimation is not optimal in channel estimation based on CS.In this paper,sparse channel estimation and pilot optimization of MIMO-OFDM system based on CS theory are studied.The main research contents are as follows:1)In OFDM systems,the CS-based channel estimation and its pilot optimization method are studied.For the problem of pilot optimization,the SSS(Stochastic Sequential Search)algorithm based on stochastic sequential search and SPS(Stochastic Parallel Search)algorithm based on stochastic parallel search are studied.The pilots obtained by above two pilot optimization methods are employed in the CS-based channel estimation,and their performance gains for channel estimation are compared by simulations.Above research lays the foundation for further research on MIMOOFDM channel estimation and pilot optimization based on CS theory.2)The problem of sparse channel estimation for MIMO-OFDM systems is researched studied,The channel estimation problem in MIMO-OFDM systems is transformed into the sparse signal reconstruction problem in CS theory.The pilot optimization is based on minimizing the mutual coherence of the measurement matrix.In combination with existing SSS and pilot shift mechanism,a fast pilot optimization algorithm Stochastic Sequential Search-Shift Mechanism(SSS-SM)is proposed.The algorithm has lower computational complexity,and the time of computation will not be affected by the number of transmit antennas.The pilot design results obtained by SSS-SM algorithm and ES2 algorithm are applied to the channel estimation of MIMO-OFDM systems.Simulation results show that SSS-SM algorithm can obtain better channel estimation performance than ES2 algorithm with lower algorithm complexity.