Precoding for the AWGN Channel With Discrete Interference

For a state-dependent discrete memoryless channel with input alphabet X, state alphabet S, and output alphabet Y where the independent and identically distributed (i.i.d.) state sequence is known causally at the transmitter, it is shown that by using at most min{|X||S|-|S| + 1,|Y|} out of |X||S| inputs of the Shannon's derived channel, the capacity is achievable. As an example of state-dependent channels with side information at the transmitter, M-ary signal transmission for the additive white Gaussian noise (AWGN) channel with additive Q-ary interference where the sequence of i.i.d. interference symbols is known causally at the transmitter is considered. The optimal precoding scheme is derived under the constraint that the channel input given any current interference symbol is uniformly distributed over the channel input alphabet. It is shown that at low signal-to-noise ratio (SNR) not doing precoding is optimal. For the special case where the Gaussian noise power is zero, it is shown that the rate log2 M is achievable by a one-shot coding scheme if X is an arithmetic progression.

[1]  Shlomo Shamai,et al.  The Capacity Region of the Gaussian Multiple-Input Multiple-Output Broadcast Channel , 2006, IEEE Transactions on Information Theory.

[2]  Charles R. Johnson,et al.  Matrix analysis , 1985, Statistical Inference for Engineers and Data Scientists.

[3]  Richard E. Blahut,et al.  Computation of channel capacity and rate-distortion functions , 1972, IEEE Trans. Inf. Theory.

[4]  Shlomo Shamai,et al.  On channels with partial channel state information at the transmitter , 2005, IEEE Transactions on Information Theory.

[5]  David Tse,et al.  Sum capacity of the multiple antenna Gaussian broadcast channel , 2002, Proceedings IEEE International Symposium on Information Theory,.

[6]  Laurence A. Wolsey,et al.  Integer and Combinatorial Optimization , 1988, Wiley interscience series in discrete mathematics and optimization.

[7]  Shlomo Shamai,et al.  On the capacity of some channels with channel state information , 1999, IEEE Trans. Inf. Theory.

[8]  Joseph A. O'Sullivan,et al.  Information-theoretic analysis of information hiding , 2003, IEEE Trans. Inf. Theory.

[9]  M. Salehi Capacity and coding for memories with real-time noisy defect information at encoder and decoder , 1992 .

[10]  Claude E. Shannon,et al.  Channels with Side Information at the Transmitter , 1958, IBM J. Res. Dev..

[11]  Wei Yu,et al.  Sum capacity of Gaussian vector broadcast channels , 2004, IEEE Transactions on Information Theory.

[12]  Kenneth C. Gilbert,et al.  MULTIDIMENSIONAL ASSIGNMENT PROBLEMS , 1988 .

[13]  D. A. Bell,et al.  Information Theory and Reliable Communication , 1969 .

[14]  G. David Forney,et al.  Trellis precoding: Combined coding, precoding and shaping for intersymbol interference channels , 1992, IEEE Trans. Inf. Theory.

[15]  Rajiv Laroia Coding for intersymbol interference channels-combined coding and precoding , 1996, IEEE Trans. Inf. Theory.

[16]  Abbas El Gamal,et al.  On the capacity of computer memory with defects , 1983, IEEE Trans. Inf. Theory.

[17]  Shlomo Shamai,et al.  Capacity and lattice strategies for canceling known interference , 2005, IEEE Transactions on Information Theory.

[18]  丸山 徹 Convex Analysisの二,三の進展について , 1977 .

[19]  Gregory W. Wornell,et al.  Quantization index modulation: A class of provably good methods for digital watermarking and information embedding , 2001, IEEE Trans. Inf. Theory.

[20]  William P. Pierskalla,et al.  Letter to the Editor - The Multidimensional Assignment Problem , 1968, Oper. Res..

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

[22]  Yuval Rabani,et al.  Linear Programming , 2007, Handbook of Approximation Algorithms and Metaheuristics.

[23]  Andrea J. Goldsmith,et al.  Duality, achievable rates, and sum-rate capacity of Gaussian MIMO broadcast channels , 2003, IEEE Trans. Inf. Theory.

[24]  Alla R. Kammerdiner Multidimensional Assignment Problem , 2009, Encyclopedia of Optimization.

[25]  Amos Lapidoth,et al.  The Gaussian watermarking game , 2000, IEEE Trans. Inf. Theory.

[26]  Shlomo Shamai,et al.  On the achievable throughput of a multiantenna Gaussian broadcast channel , 2003, IEEE Transactions on Information Theory.

[27]  M. Tomlinson New automatic equaliser employing modulo arithmetic , 1971 .

[28]  Suguru Arimoto,et al.  An algorithm for computing the capacity of arbitrary discrete memoryless channels , 1972, IEEE Trans. Inf. Theory.

[29]  David Tse,et al.  Sum capacity of the vector Gaussian broadcast channel and uplink-downlink duality , 2003, IEEE Trans. Inf. Theory.