Joint OFDM Symbol Detection and Channel Estimation Over Doubly Selective Channels

Download or read book Joint OFDM Symbol Detection and Channel Estimation Over Doubly Selective Channels written by Yi Wang and published by . This book was released on 2014 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: "Orthogonal Frequency Division Multiplexing (OFDM) is a promising technique for high data rate transmission, that is widely used in modern wireless communication systems because of its good performance over frequency selective channels. However OFDM systems are sensitive to channel time variation resulting in Inter-Carrier Interference (ICI), that without suitable detection methods can degrade performance. Channel State Information (CSI) is essential to various OFDM data detection schemes and its acquisition is a critical factor, in particular over time-varying channels. This work considers a technique for integrating the Kalman filter channel estimation with a version of Sphere Decoding (SD) adapted to OFDM detection. By modelling the OFDM system in frequency domain as a Multiple Input Multiple Output (MIMO) system, we derive a powerful SD technique for data detection. By approximating the channel matrix as banded, we are able to maintain a feasible complexity for SD and deliver competitive performance when compared to other existing scheme. For acquisition of CSI, the Basis Expansion (BE) method is used to model the time-varying channels and a Kalman filter is constructed for tracking. The Kalman filter employs decision-feedback from the SD, requiring only a low pilot symbol density, and hence improves bandwidth efficiency. The performance of this scheme is evaluated by Monte-Carlo computer simulations. Results show that compared with competing algorithm, this scheme provides performance gains. When it is used over moderate time-varying LTE channels, this scheme shows good performance even in the presence of carrier phase noise. " --