Adaptive channel estimation in MIMO-OFDM for indoor and outdoor environments

With the rapid change in wireless communication technologies, there is always a demand for higher data rates, improved system capacity and service quality. Several technologies and standards have been developed to provide services to the end users. To find out a solution to meet these challenges, channel modeling and estimation of channel state information play a vital role in communication system design. However, due to the adverse effects of channel fading and the Doppler shifts caused by user mobility, channel modeling and estimation of channel parameters is quite difficult. Adaptive modeling for indoor and outdoor channels is an efficient approach to track the time-varying and fading behavior of the channels. This paper addresses the problem of channel estimation in a MIMO-OFDM environment with different indoor and outdoor channel models. The performance of the adaptive estimation model is evaluated through comparison results with the inclusion of sparsity and block processing to conventional Least Mean Square (LMS) algorithm.