Joint Channel Estimation and Decoding Design for 5G-Enabled V2V Channel

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This paper addresses the problem of channel estimation in 5G-enabled vehicu-lar-to-vehicular (V2V) channels with high-mo-bility environments and non-stationary feature. Considering orthogonal frequency division multiplexing (OFDM) system, we perform extended Kalman filter (EKF) for channel es-timation in conjunction with Iterative Detector& Decoder (IDD) at the receiver to improve the estimation accuracy. The EKF is proposed for jointly estimating the channel frequency response and the time-varying time correlation coefficients. And the IDD structure is adopted to reduce the estimation errors in EKF. The simulation results show that, compared with traditional methods, the proposed method ef-fectively promotes the system performance.
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