A LARGE-SCALE MIMO CHANNEL INFORMATION FEEDBACK ALGORITHM BASED ON COMPRESSED SENSING

Jing Jiang, Shuang Xu, Guangyue Lu, Yongbin Xie

School of Communication and Information Engineering, Xi'an University of Posts & Telecommunications, Xi’an, 710061, China

 In order to effectively reduce the feedback overhead of channel state information (CSI), a channel state information feedback algorithm based on compressed sensing was proposed for Large-scale MIMO system. Firstly considering the sparsity of spatial-frequency domain for the large-scale MIMO channel, the channel information was compressed in space domain firstly and in frequency domain subsequently, the receiver acquired the measurement vector based on compressed sensing algorithm; then feedback. CSI observations to the transmitter according to the proposed adaptive feedback protocol, at last the transmitter reconstructed CSI based on the Basis Pursuit (BP) algorithm. It is show in stimulation results that the proposed algorithm can acquire similar BER performance with perfect channel information feedback. The proposed algorithm, which feedbacks the compressed channel information, not only can significantly reduce the feedback overhead, but also ensure that large-scale MIMO performance gain.