On the Transport Capacity of Gaussian Multiple Access and Broadcast Channels

  • Authors:
  • G. A. Gupta;S. Toumpis;J. Sayir;R. R. Muller

  • Affiliations:
  • Indian Institute of Technology;Telecommunications Research Center Vienna;Telecommunications Research Center Vienna;Norwegian University of Science and Technology

  • Venue:
  • WIOPT '05 Proceedings of the Third International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks
  • Year:
  • 2005

Quantified Score

Hi-index 0.00

Visualization

Abstract

We study the transport capacity of a Gaussian multiple access channel, which consists of a set of transmitters and a single receiver. The transport capacity is defined as the sum, over all transmitters, of the product of the transmission rate with a reward r(x), which is a function of the distance x between the transmitter and the receiver, and quantifies the usefulness of transmitting information over a distance x. Assuming that the sum of the transmitter powers is upper bounded, we present in closed form the optimal power allocation among the transmitters, that maximizes the transport capacity. We then present simple expressions for the optimal power allocation and induced transport capacity, as the number of transmitters approaches infinity. We also study the transport capacity of a Gaussian broadcast channel, which consists of a single transmitter and multiple receivers. Here, the transport capacity is defined as the sum, over all receivers, of the product of the transmission rate with a reward r(x). We determine in closed form the maximum possible transport capacity and the distribution of the available transmitter power among the receivers that achieves it. Although this result has already been reported in the literature, our derivation is shorter, and leads to simpler expressions. Our results can be used to gain intuition and develop good design principles in a variety of settings. For example, they apply to the uplink and downlink channel of cellular networks, and also to sensor networks which consist of multiple sensors that communicate with a single central station.