• DocumentCode
    2488114
  • Title

    Lattice network codes based on Eisenstein integers

  • Author

    Sun, Qifu Tyler ; Yuan, Jinhong

  • Author_Institution
    Inst. of Network Coding, Chinese Univ. of Hong Kong, Hong Kong, China
  • fYear
    2012
  • fDate
    8-10 Oct. 2012
  • Firstpage
    225
  • Lastpage
    231
  • Abstract
    In this paper, we investigate lattice network codes (LNCs) constructed from lattices over the ring of Eisenstein integers. Quantization and encoding algorithms over Eisenstein integers are first introduced. Then, a union bound estimation (UBE) of the decoding error probability is derived when the shaping region of the LNC is a product of regular hexagons. We show that the UBE is in the same form as the one for hypercube shaped LNCs, such as in the Gaussian integer case. We also demonstrate that in the Eisenstein integer case, the nominal coding gain and the shaping gain of a baseline LNC are, respectively, 0.625 dB and 0.167 dB, in contrast to the Gaussian integer case, where both gains are 0 dB. This is consistent with the simulation results comparing the performance of decoding error probability of baseline LNCs.
  • Keywords
    decoding; error statistics; network coding; quantisation (signal); Eisenstein integer case; Gaussian integer case; decoding error probability; encoding algorithms; hypercube shaped LNC; lattice network codes; nominal coding gain; quantization algorithms; regular hexagons; shaping gain; union bound estimation; Decoding; Encoding; Error probability; Gain; Hypercubes; Lattices; Vectors; Computer-and-forward; Eisenstein integers; lattice network codes; union bound estimation of decoding error;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Wireless and Mobile Computing, Networking and Communications (WiMob), 2012 IEEE 8th International Conference on
  • Conference_Location
    Barcelona
  • ISSN
    2160-4886
  • Print_ISBN
    978-1-4673-1429-9
  • Type

    conf

  • DOI
    10.1109/WiMOB.2012.6379080
  • Filename
    6379080