Low complexity of computational cost of RF signal processing based diversity scheme for MIMO-OFDM systems

It is is capable of doubling the capacity without expanding the occupied frequency bandwidth in Radio Frequency (RF) signal processing based diversity scheme for Multi-Input Multi-Output Orthogonal Frequency Division Multiplexing (MIMO-OFDM) systems using 2×2 dimension antenna. This technique is great because the additional diversity can be gained when the method of the linear MIMO decomposition is used. The resulting performance trends show a significant increase when it is compared to MIMO-OFDM schemes using conventional antenna for 2×2. But the complexity of computational cost is high, especially for the larger antenna size. For that reason the complexity of computation cost is proposed by applying technology of RF signal processing for MIMO-OFDM. So the technique, called Kalman filter MIMO equalizer is used to reduce low complexity of computational cost. In this technique the reduction of the matrix size of original channel matrix is made into 2×4 of matrix size for the number of sub-carrier. In additional part error correction coding technique is added by using convolution code techniques and viterbi algorithm applied at receiver side. Computer simulation result shows that the proposed scheme gives low complexity of computational cost and gives additional diversity gain.