ML based estimation of carrier frequency offset for multi antenna OFDM system.

The Maximum Likelihood (ML) estimation of carrier frequency offset (CFO) for multiple-input multiple-output (MIMO) systems using orthogonal frequency division multiplexing (OFDM) across Rayleigh fading channels is discussed in this study. CFOs are sensitive to OFDM, which is caused through oscillator frequency imbalances and/or Doppler shifts. CFO presents Inter-Carrier Interference (ICI), which is a type of interference that causes subcarriers to disturb their orthogonality. Maximum likelihood (ML) estimation of carrier-frequency offsets for uplink transmission of orthogonal frequency-division multiple access is a complicated issue to estimate using several parameters. The ML technique is based on the global optima search issue, which is impractical in practice due to the need for a multidimensional extensive search of the huge number of users. Simulation results indicate the performance of the ML estimation technique of CFO estimation in OFDM and OFDM-MIMO uplink systems in terms of accuracy and complexity. [ABSTRACT FROM AUTHOR]