Multiple multicasts with the help of a relay

  • Authors:

  • Deniz Gündüz;Osvaldo Simeone;Andrea J. Goldsmith;H. Vincent Poor;Shlomo Shamai

  • Affiliations:

  • Centre Tecnològic de Telecomunicacions de Catalunya, Barcelona, Spain and Department of Electrical Engineering, Stanford University, Stanford, CA and Department of Electrical Engineering, Pri ...;CWCSPR, New Jersey Institute of Technology, Newark, NJ;Department of Electrical Engineering, Stanford University, Stanford, CA;Department of Electrical Engineering, Princeton University, Princeton, NJ;Department of Electrical Engineering, Technion, Haifa, Israel

  • Venue:
  • IEEE Transactions on Information Theory
  • Year:
  • 2010

Quantified Score

Hi-index 754.84

Visualization

Abstract

The problem of simultaneous multicasting of multiple messages with the help of a relay terminal is considered. In particular, a model is studied in which a relay station simultaneously assists two transmitters in multicasting their independent messages to two receivers. The relay may also have an independent message of its own to multicast. As a first step to address this general model, referred to as the compound multiple access channel with a relay (cMACr), the capacity region of the multiple access channel with a "cognitive" relay is characterized, including the cases of partial and rate-limited cognition. Then, achievable rate regions for the cMACr model are presented based on decode-and forward (DF) and compress-and-forward (CF) relaying strategies. Moreover, an outer bound is derived for the special case, called the cMACr without cross-reception, in which each transmitter has a direct link to one of the receivers while the connection to the other receiver is enabled only through the relay terminal. The capacity region is characterized for a binary modulo additive cMACr without cross-reception, showing the optimality of binary linear block codes, and thus highlighting the benefits of physical layer network coding and structured codes. Results are extended to the Gaussian channel model as well, providing achievable rate regions for DF and CF, as well as for a structured code design based on lattice codes. It is shown that the performance with lattice codes approaches the upper bound for increasing power, surpassing the rates achieved by the considered random coding-based techniques.