Channel Estimation Based on Complete Complementary Sequence and Compressive Sensing for MIMO System

In this paper, a new multiple-input multiple-output (MIMO) communication system channel estimation architecture based on complete complementary sequence (CC-S) and compressive sensing (CS) is developed. CC-S can be used for MIMO system to combat multipath fading and decrease bit error rate (BER). CS can reconstruct a sparse signal from fewer samples than those obtained by the Nyquist rate, which can be applied for sparse wireless communication channel estimation. The key in the proposed architecture relies on the perfect orthogonal performance of CC-S and the ultra Nyquist sample feature of CS. Complementary sequences were assigned to each antenna to achieve spreading gain in MIMO communication system. A BER analysis for compressive sensing domain is presented in this paper. Both measured data and a practical MIMO system model with CC-S and CS are used for evaluation. It is shown that CS theory based on CC-S is able to improve the MIMO system performance. Simulation results demonstrate the feasibility and validity of the two technologies applied in MIMO system.