High mobility channel estimation based on amplifyand-forward model in cooperative network - Mohammad Fazle, Rabbi (2016)
Cooperative communication has been proposed for a number of next generation mobile technologies such as Worldwide Interoperability for Microwave Access (WiMAX), wireless Metropolitan Area Network (WMAN), Long Term Evolution (LTE) and LTE-Advanced. In addition to the higher data rate, the upcoming wireless technologies support higher user mobility than the previous technologies. However, due to the fast movement, the channel may experience Doppler spread which may cause the carrier frequency offset (CFO) resulting Inter Carrier Interference (ICI). Modeling and estimating this type of channel is crucial and, play a vital role to fulfil the data rate requirement of the network. In this thesis, an Amplify-and-Forward (AF) relay based cooperative network using Orthogonal Frequency Division Multiplexing (OFDM) system has been studied. The problem of high mobility OFDM channel is investigated first. To alleviate the problem, Basis Expansion Modeling (BEM) for time varying channel has been applied. BEM is used to capture the time variation of the channel with very small coherence time. Following the channel model, the OFDM based AF relaying system model is developed including transmit and receive signal model. In this study, Least Square (LS) and Linear Minimum Mean Square Error (LMMSE) estimators are formulated based on two different pilot patterns for both time and frequency domains. In addition to the estimators, Cramer-Rao lower bound is derived as a benchmark of the estimation performance of the estimation methods. Based on the theoretical analysis and simulation results it was found that the frequency domain channel estimation suffers from the estimation errors due to the ICI from the data symbols in the OFDM block. On the other hand, time domain channel estimation methods can provide interference free and more accurate estimates in high mobility channel conditions. Moreover, being a more complex and advance estimator, LMMSE was found to be more precise in compare to LS estimator in time domain channel estimation. Also, LMMSE performs more close to the CRLB and may be a better choice for channel estimation in high speed mobile environment.