Outer bounds for multiple-access channels with feedback using dependence balance

Ravi Tandon, Sennur Ulukus

Research output: Contribution to journalArticlepeer-review

8 Scopus citations


We use the idea of dependence balance to obtain a new outer bound for the capacity region of the discrete memoryless multiple-access channel with noiseless feedback (MAC-FB). We consider a binary additive noisy MAC-FB whose feedback capacity is not known. The binary additive noisy MAC considered in this paper can be viewed as the discrete counterpart of the Gaussian MAC-FB. Ozarow established that the capacity region of the two-user Gaussian MAC-FB is given by the cut-set bound. Our result shows that for the discrete version of the channel considered by Ozarow, this is not the case. Direct evaluation of our outer bound is intractable due to an involved auxiliary random variable whose large cardinality prohibits an exhaustive search. We overcome this difficulty by using a composite function and its properties to explicitly evaluate our outer bound. Our outer bound is strictly less than the cut-set bound at all points on the capacity region where feedback increases capacity. In addition, we explicitly evaluate the Cover-Leung achievable rate region for the binary additive noisy MAC-FB in consideration. Furthermore, using the tools developed for the evaluation of our outer bound, we also explicitly characterize the boundary of the feedback capacity region of the binary erasure MAC, for which the Cover-Leung achievable rate region is known to be tight. This last result confirms that the feedback strategies developed by Kramer for the binary erasure MAC are capacity achieving.

Original languageEnglish (US)
Pages (from-to)4494-4507
Number of pages14
JournalIEEE Transactions on Information Theory
Issue number10
StatePublished - 2009
Externally publishedYes


  • Cut-set bound
  • Dependence balance
  • Multiple-access channel with feedback (MAC-FB)

ASJC Scopus subject areas

  • Information Systems
  • Computer Science Applications
  • Library and Information Sciences


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