Channel Estimation for Sparse Channel OFDM Systems using Least Square and Minimum Mean Square Error Techniques

Abstract

Orthogonal Frequency Division Multiplexing (OFDM), is a kind of signal modulation that divides a high data rate modulating stream and locates them onto several modulated narrowband channels called sub-carriers. Therefore, signal will be less sensitive to frequency selective fading. Channel estimation is used for increasing the capacity of orthogonal frequency division multiple access (OFDMA) systems by improving the system performance in terms of bit error rate. OFDM pilot based channel estimation is applied in this paper. Channel tracking and channel estimation techniques must be employed at the receiver side of the OFDM system. Channel estimations require channel state information in order to decode the data. In this paper, a proposed Least square (LS) method is considered for sparse channels. Channel coefficients for OFDM are estimated by applying this method and Minimum Mean Square Error (MMSE) method. Results show that the performance of MMSE technique is better than LS method. It is found that the LS method for sparse channel gives lower bit error rate than the general LS method.