Fundamentals of Channel Estimation for Mobile Communications

Recently, mobile communications have developed rapidly due to the endless demand for broadband multimedia access and wireless connection anywhere, and any time. To harvest the advantages of these enabling technologies maximally, both tremendous opportunities, and major challenges are current in the research of signal processing specially for channel estimation (CE). CE algorithms allow the receiver to approximate the impulse response of the channel and explain the behavior of the channel. The focus of this work is to investigate and evaluate the different CE techniques in a single carrier frequency division multiple access (SC-FDMA) system. Here we analyze new variable step size (VSS)-least mean squares (LMS) and normalized VSS (NLMS)-normalized LMS (NLMS) blind CE algorithm that can automatically adapts the optimum weighting coefficients to the channel condition. This time-varying step size method is updated at each iteration to minimize the sum of the squares of the prior estimation errors up to that current time point. In addition, this CE algorithm uses phase discriminating weighting scheme such that algorithm is reduces error owing to noise as well as decision error.