A Hybrid of BFO and MCS Algorithm for Channel Estimation of MIMO-OFDM System

Abstract: In this paper, challenges regarding the provision of channel state information (CSI) in multiple input multiple output orthogonal frequency division multiplexing (MIMO-OFDM)) systems are addressed. A novel scheme that utilizes a Hybrid of Bacterial Foraging and Modified Cuckoo Search (HBFOMCS) optimization together to design pilot symbols that minimizes the channel estimate mean squared error (MSE) is proposed. The optimal selection of pilot subcarriers is a combinatorial problem that requires heavy computations. To reduce the computational complexity, the HBFOMCS optimization is utilized to determine the position of pilot subcarriers. Then, for a given pilot placement obtained by the HBFOMCS algorithm, the MSE of least squares (LS) and Minimum Mean Square Error(MMSE) based channel estimation are computed. Simulation results indicate that, the proposed pilot symbol design provides better channel estimate MSE as well as the bit error rate (BER) performance with reduced computational complexity for MMSE method when compared with the LS method and other conventional optimization based pilot design.

Keywords: HBFOMCS, LS channel estimation, MMSE channel estimation, MIMO-OFDM,MSE.