Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Trellis-Based Iterative Adaptive Blind Sequence Estimation for Uncoded/Coded Systems with Differential Precoding | EURASIP Journal on Applied Signal Processing 2005 6 828-843 2005 Hindawi Publishing Corporation Trellis-Based Iterative Adaptive Blind Sequence Estimation for Uncoded Coded Systems with Differential Precoding Xiao-Ming Chen Information and Coding Theory Lab Faculty of Engineering University of Kiel 24143 Kiel Germany Email xc@ Peter A. Hoeher Information and Coding Theory Lab Faculty of Engineering University of Kiel 24143 Kiel Germany Email ph@ Received 1 October 2003 Revised 23 April 2004 We propose iterative adaptive trellis-based blind sequence estimators which can be interpreted as reduced-complexity receivers derived from the joint ML data channel estimation problem. The number of states in the trellis is considered as a design parameter providing a trade-off between performance and complexity. For symmetrical signal constellations differential encoding or generalizations thereof are necessary to combat the phase ambiguity. At the receiver the structure of the super-trellis representing differential encoding and intersymbol interference is explicitly exploited rather than doing differential decoding just for resolving the problem of phase ambiguity. In uncoded systems it is shown that the data sequence can only be determined up to an unknown shift index. This shift ambiguity can be resolved by taking an outer channel encoder into account. The average magnitude of the soft outputs from the corresponding channel decoder is exploited to identify the shift index. For frequency-hopping systems over fading channels a double serially concatenated scheme is proposed where the inner code is applied to combat the shift ambiguity and the outer code provides time diversity in conjunction with an interburst interleaver. Keywords and phrases joint data channel estimation blind sequence estimation iterative processing turbo equalization. 1. INTRODUCTION In most digital communication systems a training sequence is inserted in each data burst for .
