Channel Estimation For LTE-V2V System In High-Speed Mobile Channel

Internet of Vehicles(IoV)is a system network for information exchange and wireless communication between vehicles and everything.As an important application of the Internet of Things,the IoV is widely used in traffic safety,automatic driving,and car entertainment.In the future,the IoV is capable of realizing intelligent transportation system,improving the efficiency and safety of vehicle driving,relieving urban traffic congestion and ensuring traffic safety effectively.It is a great challenge for the IoV system accurately realizing information exchange and wireless communication over high Doppler spreading channel.For vehicle-to-vehicle(V2V)communications,the performance of conventional channel estimation(CE)and equalization is significantly degraded in single carrier frequency division multiple access(SC-FDMA)receivers.Developed from the LTE uplink,the long term evolution-vehicle to everything(LTE-V2X)standard increases the overhead of pilot symbols in order to acquire channel information robustly.The major contributions of this thesis are summarized as follows:Firstly,the simulation platform of the LTE physical downlink baseline,consisting of channel encoding/decoding and MIMO-OFDM modulation/demodulation modules,is established and further verified through simulations.The accuracy of the following traditional interpolation schemes,i.e.,statistical feature based interpolation algorithm,fixed coefficients based interpolation algorithm and low-pass filter based interpolation algorithm,are deeply compared in multi-path fading channels.These conventional CE algorithms provide a performance reference for the proposed time-domain CE algorithms.Secondly,the time-domain CE algorithms are proposed for coping with extremely high-speed mobile channels.Referring to the performance degradation of CE in highspeed mobile environments,we propose to estimate time-varying pieces of channel rays for pilot symbols based on the basis expansion model(BEM),and subsequently to reconstruct time-domain channel response for data symbols by utilizing the Slepian sequences based piece-wise interpolation(SS-MPI).Furthermore,two simplified schemes,i.e.,the Slepian sequences based multiple-point interpolation(SS-MPI)and the segmented BEM(S-BEM),are developed to significantly reduce the computational complexity of the time-domain CE methods.The proposed algorithms are capable of estimating the CIR effectively and improving the demodulation performance of the SCFDMA receiver.Thirdly,a new equalization algorithm is introduced,and further implemented to the LTE-V system for verifying its demodulation performance.At first,we introduce common MMSE equalization and one-tap equalization methods.With the light of the sparsity of CIR,we design an iterative LSQR algorithm to equalize the SC-FDM symbols with a relatively low complexity.Simulations are implemented on the LTE-V platform,on which we consider the relative velocity of 500 km/h in the simulated channel.The simulation results demonstrate that the traditional frequency domain methods cause the demodulation failure,while the proposed time-domain processing schemes achieve ideal error probability performance and preserve a relatively low calculation complexity.