THE ELEVENTH IEEE SENSOR ARRAY AND MULTICHANNEL SIGNAL PROCESSING WORKSHOP (IEEE SAM2020)

21 / 2019-12-04 03:07:00

Sparse Adaptive Algorithm for High Channel Reconstruction in MIMO-FBMC Systems

MIMO; FBMC; Sparse adaptive; Channel reconstruction

IEEE SAM 2020: Special Sessions > Array Signal Processing with Imperfect Scenarios

Intrinsic interference has become an obstacle to high performance channel reconstruction (CR) in multiple-input multiple-output (MIMO) filter bank multi-carrier employing offset quadrature amplitude modulation (FBMC/OQAM) system. Conventional preamble-based channel reconstruction approach cannot work effectively. By utilizing channel sparsity, CR could be researched as a sparse compressed sensing (CS) signal reconstruction issue. This paper focuses on the CS-based CR approach in the MIMO system, and proposes a sparse adaptive CR method. In the proposed algorithm, the unknown sparsity channel can be reconstructed by automatic adjusting the selected atoms, and partial information of the target channel is reconstructed by utilizing the backtracking theory in the iterative process. The simulation results indicate that CS approach provides remarkable better CR performance than conventional method. The proposed CS-based algorithm outperforms conventional sparse adaptive CS-based method.