Achieving Csiszár's source-channel coding exponent with product distributions

نویسندگان

  • Adrià Tauste Campo
  • Gonzalo Vazquez-Vilar
  • Albert Guillén i Fàbregas
  • Tobias Koch
  • Alfonso Martinez
چکیده

We derive a random-coding upper bound on the average probability of error of joint source-channel coding that recovers Csiszár’s error exponent when used with product distributions over the channel inputs. Our proof technique for the error probability analysis employs a code construction for which source messages are assigned to subsets and codewords are generated with a distribution that depends on the subset.

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تاریخ انتشار 2012