Two-dimensional recursive least square adaptive channel estimation for OFDM systems

In orthogonal frequency division multiplexing (OFDM) system, time- and frequency-domain two-dimensional minimum mean square error (2D-MMSE) channel estimation is optimum. However, accurate channel statistics, which are often time-varying and unavailable in practice, are required to realize it. In this paper, we propose two-dimensional recursive least square (2D-RLS) adaptive channel estimation for OFDM system. 2D-RLS adaptive channel estimation does not require accurate channel statistics, and at the same time can make full use of time-and frequency-domain correlations of the frequency response of time-varying wireless channels. With properly chosen parameters, 2D-RLS adaptive channel estimation can converge into the steady state in only several OFDM symbols´ time. Computer simulations demonstrate that 2D-RLS adaptive channel estimation is very effective and suitable for a broad range of channel conditions. Furthermore, with proper training sequences design on transmitter antennas, 2D-RLS adaptive channel estimation can be applied to multiple inputs multiple outputs (MIMO) OFDM system.