Research on channel estimation based on adaptive filtering for LTE uplink

Long Term Evolution (LTE) is designed for high speed data rate, higher spectral efficiency, and lower latency. LTE implements Single Carrier Frequency Division Multiple Access (SC-FDMA) for its uplink. A main challenge for the terminal implementation of LTE uplink is efficient realization of channel estimation. A Wiener filter-type estimator based on pilot symbols is often used to solve the problem. However, this estimator requires statistic prior knowledge of channel and noise that is not easily obtained. In this paper, adaptive channel estimators based on the normalized least mean square (NLMS) algorithm and recursive least square (RLS) algorithm are presented for LTE uplink. The estimators update coefficients continually and do not need prior knowledge. Simulation results show that the adaptive estimators have excellent performance measured in terms of the normalized mean square error (NMSE) in different channel environment.