A lattice Compress-and-Forward strategy for canceling known interference in Gaussian multi-hop channels

We present a nested-lattice encoding and decoding strategy for Compress-and-Forward (CF) relaying. This complements previous work on a nested-lattice encoding and decoding scheme for Decode-and-Forward (DF) relaying, and provides an alternative to random codes for CF relaying which may be a useful coding strategy for larger networks. The proposed nested-lattice CF schemes utility is demonstrated by using it to cancel interference in a two-hop Gaussian network with a source, a relay and a destination, in which additive interference experienced at the relay and known at the destination (but not the source). The proposed scheme achieves the same rate as a CF scheme without interference, and to within 1/2 bit from the “clean” channel outer bound. We further illustrate this schemes power by discussing extensions to multi-hop networks in which one or more interference terms are known by receivers “down-the-line.”

[1]  Simon Litsyn,et al.  Lattices which are good for (almost) everything , 2005, IEEE Transactions on Information Theory.

[2]  Shlomo Shamai,et al.  Nested linear/Lattice codes for structured multiterminal binning , 2002, IEEE Trans. Inf. Theory.

[3]  Shlomo Shamai,et al.  Bounds on the capacity of the relay channel with noncausal state information at source , 2010, 2010 IEEE International Symposium on Information Theory.

[4]  Natasha Devroye,et al.  Structured interference-mitigation in two-hop networks , 2011, 2011 Information Theory and Applications Workshop.

[5]  S. Shamai,et al.  Nested linear/lattice codes for Wyner-Ziv encoding , 1998, 1998 Information Theory Workshop (Cat. No.98EX131).

[6]  Abbas El Gamal,et al.  Capacity theorems for the relay channel , 1979, IEEE Trans. Inf. Theory.

[7]  Uri Erez,et al.  Achieving 1/2 log (1+SNR) on the AWGN channel with lattice encoding and decoding , 2004, IEEE Transactions on Information Theory.

[8]  Natasha Devroye,et al.  List decoding for nested lattices and applications to relay channels , 2010, 2010 48th Annual Allerton Conference on Communication, Control, and Computing (Allerton).

[9]  Abbas El Gamal,et al.  Capacity theorems for relay channels , 1979 .

[10]  Uri Erez,et al.  Lattice Strategies for the Dirty Multiple Access Channel , 2007, IEEE Transactions on Information Theory.

[11]  Aaron D. Wyner,et al.  The rate-distortion function for source coding with side information at the decoder , 1976, IEEE Trans. Inf. Theory.

[12]  S. Sandeep Pradhan,et al.  A proof of the existence of good nested lattices , 2007 .

[13]  Ram Zamir,et al.  On the Loss of Single-Letter Characterization: The Dirty Multiple Access Channel , 2009, IEEE Transactions on Information Theory.

[14]  Sae-Young Chung,et al.  Nested Lattice Codes for Gaussian Relay Networks With Interference , 2011, IEEE Transactions on Information Theory.

[15]  Young-Han Kim,et al.  Multiple user writing on dirty paper , 2004, International Symposium onInformation Theory, 2004. ISIT 2004. Proceedings..

[16]  Max H. M. Costa,et al.  Writing on dirty paper , 1983, IEEE Trans. Inf. Theory.

[17]  Hans-Andrea Loeliger,et al.  Averaging bounds for lattices and linear codes , 1997, IEEE Trans. Inf. Theory.

[18]  R. Zamir Lattices are everywhere , 2009, 2009 Information Theory and Applications Workshop.

[19]  G. David Forney,et al.  On the role of MMSE estimation in approaching the information-theoretic limits of linear Gaussian channels: Shannon meets Wiener , 2004, ArXiv.