Adaptive channel estimation and tracking for indoor MIMO OFDM mobile communication systems

This paper highlights the performance of the proposed EW-RLS and NLMS channel estimator is evaluated by means of simulation, in the context of communication system with multiple antenna operating in indoor environments. A focus is given to the capabilities of these algorithms to track the time-variations of the channel at different training rates and different Doppler frequencies. Three adaptive algorithms are considered; namely the least squares (LS), the recursive least squares (RLS) algorithm and the least mean square (LMS) algorithm. The RLS is a widely used algorithm in channel estimation, especially when the channel is a slow time-varying. This algorithm has the property of fast convergence compared to the LMS algorithm at the cost of little increase in the computational complexity. The performance is evaluated in terms of the MSE of the channel estimate, and the system BER, for different Doppler frequencies (correspond to different mobility speeds). Simulation results have demonstrated that time-domain adaptive channel estimation and tracking in MIMO OFDM systems based on the DD EW-RLS and DD-NLMS is very effective in slowly to moderate time-varying fading channels. This paper provides analysis, evaluation and computer simulations in MATLAB.