MIMO-OFDM System Simulation and Channel Estimation Algorithms

MIMO technology, or Multiple-Input Multiple-Output systems, was initially proposed by Marconi in 1908. This technique employs multiple antennas to combat channel fading. Depending on the antenna configuration at both transmission and reception ends, MIMO systems encompass SIMO (Single-Input Multiple-Output) and MISO (Multiple-Input Single-Output) systems, compared to standard SISO (Single-Input Single-Output) systems. From an implementation perspective, this involves coding schemes like Space-Time Block Codes (STBC) and spatial multiplexing techniques. The channel capacity demonstrates linear growth with increasing antenna numbers, which can be computationally verified through eigenvalue decomposition of channel correlation matrices. Consequently, MIMO channels enable exponential improvement in wireless channel capacity without requiring additional bandwidth or increased transmission power. From a simulation standpoint, we can provide various corresponding models and algorithms - including channel estimation methods like LS (Least Squares) and MMSE (Minimum Mean Square Error), and detection algorithms such as ZF (Zero Forcing) and ML (Maximum Likelihood) - to further research and apply MIMO technology in practical communication systems.