Matching Dyadic Distributions to Channels

Preprint English OPEN
Böcherer, Georg; Mathar, Rudolf;
  • Subject: Computer Science - Information Theory | Mathematics - Probability
    arxiv: Computer Science::Information Theory | Physics::Biological Physics

Many communication channels with discrete input have non-uniform capacity achieving probability mass functions (PMF). By parsing a stream of independent and equiprobable bits according to a full prefix-free code, a modu-lator can generate dyadic PMFs at the channel inpu... View more
  • References (14)
    14 references, page 1 of 2

    [1] F. R. Kschischang and S. Pasupathy, “Optimal nonuniform signaling for Gaussian channels,” IEEE Trans. Inf. Theory, vol. 39, no. 3, pp. 913-929, 1993.

    [2] A. Lempel, S. Even, and M. Cohn, “An algorithm for optimal prefix parsing of a noiseless and memoryless channel,” IEEE Trans. Inf. Theory, vol. 19, no. 2, pp. 208-214, 1973.

    [3] K. J. Kerpez, “Runlength codes from source codes,” IEEE Trans. Inf. Theory, vol. 37, no. 3, pp. 682-687, 1991.

    [4] G. Ungerboeck, “Huffman shaping,” in Codes, Graphs, and Systems, R. Blahut and R. Koetter, Eds. Springer, 2002, ch. 17, pp. 299-313.

    [5] J. Abrahams, “Variable-length unequal cost parsing and coding for shaping,” IEEE Trans. Inf. Theory, vol. 44, no. 4, pp. 1648-1650, 1998.

    [6] G. Bo¨cherer, F. Altenbach, and R. Mathar, “Capacity achieving modulation for fixed constellations with average power constraint,” 2010, submitted to ICC 2011.

    [7] G. Bo¨cherer, “Geometric huffman coding,”, Dec. 2010.

    [8] T. M. Cover and J. A. Thomas, Elements of Information Theory, 2nd ed. John Wiley & Sons, Inc., 2006.

    [9] T. H. Cormen, C. E. Leiserson, R. L. Rivest, and C. Stein, Introduction to Algorithms, 2nd ed. The MIT Press, 2001.

    [10] R. G. Gallager, Principles of Digital Communication. Cambridge University Press, 2008.

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