Iterative Decoding of Virtual Differentially Coded OFDM Systems

This paper describes a virtual differentially coded system without a differential encoder at the transmitter and channel estimates at the receiver. Without the assistance of a differential encoder, a differential decoder detects a linearly multiplexed symbol that is constituted by two transmitted symbols in different times. In the virtual differentially coded system, the multiplexed symbol is regarded as a virtual symbol. In order to resolve the virtual symbol into the two original symbols, extrinsic log likelihood ratio (LLR), which is fed back from the channel decoder, is exploited with the aid of iterative decoding. For the sake of improving the convergence property of iterative decoding, sparse pilot symbols are doped in a stream of transmitted symbols. We demonstrate that the proposed system with a small number of sparse pilot tones is very assistive in terms of frame error rate (FER) performance. Furthermore, we explicitly show that the proposed approach outperforms the conventional differential and coherent detection schemes under the condition of a few sparse pilots.

[1]  Stephan ten Brink,et al.  Convergence behavior of iteratively decoded parallel concatenated codes , 2001, IEEE Trans. Commun..

[2]  Joachim Hagenauer,et al.  The exit chart - introduction to extrinsic information transfer in iterative processing , 2004, 2004 12th European Signal Processing Conference.

[3]  Umberto Mengali,et al.  A comparison of pilot-aided channel estimation methods for OFDM systems , 2001, IEEE Trans. Signal Process..

[4]  Dariush Divsalar,et al.  Multiple-symbol differential detection of MPSK , 1990, IEEE Trans. Commun..

[5]  Lajos Hanzo,et al.  Turbo Coding, Turbo Equalisation and Space-Time Coding for Transmission over Fading Channels , 2002 .

[6]  R. Koetter,et al.  Turbo equalization , 2004, IEEE Signal Processing Magazine.

[7]  Sinem Coleri Ergen,et al.  Channel estimation techniques based on pilot arrangement in OFDM systems , 2002, IEEE Trans. Broadcast..

[8]  V. K. Jones,et al.  Channel estimation for wireless OFDM systems , 1998, IEEE GLOBECOM 1998 (Cat. NO. 98CH36250).

[9]  Sekhar Tatikonda,et al.  Control under communication constraints , 2004, IEEE Transactions on Automatic Control.

[10]  Henk Wymeersch Iterative Receiver Design: Digital communication , 2007 .

[11]  Fredrik Tufvesson,et al.  Channel estimation with superimposed pilot sequence , 1999, Seamless Interconnection for Universal Services. Global Telecommunications Conference. GLOBECOM'99. (Cat. No.99CH37042).

[12]  Lajos Hanzo,et al.  Joint channel-and-network coding using EXIT chart aided relay activation , 2011, 2011 IEEE Wireless Communications and Networking Conference.

[13]  Georgios B. Giannakis,et al.  Optimal training and redundant precoding for block transmissions with application to wireless OFDM , 2002, 2001 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.01CH37221).

[14]  Lajos Hanzo,et al.  Near-Capacity Multi-Functional MIMO Systems , 2009 .

[15]  David Tse,et al.  Asynchronous Capacity per Unit Cost , 2010, IEEE Transactions on Information Theory.