Work

Throughput and transmission capacity of ad hoc networks with channel state information

Year: 2006

Type: conference-paper

Abstract: This paper develops a general framework for deriving the spatial throughput and transmission capacity of spatially Poisson distributed ad hoc networks for (i) random (e.g., fading) channels, and (ii) random transmission distances.In both of these scenarios the randomness of the channels and ranges invariably lowers both throughput and transmission capacity assuming that users randomly elect to transmit with some probability (i.e., Aloha).Assuming each node knows the channel state information (CSI, e.g., the channel gain and/or channel distance) to just its intended receiver, we propose a simple distributed threshold-based scheduling rule and derive the threshold that optimizes throughput.The gains are surprisingly large: a factor of three increase in throughput over Aloha is typical even with no further coordination between the nodes in the network.

Source: Illinois Digital Environment for Access to Learning and Scholarship (University of Illinois at Urbana-Champaign)

Authors: Steven Weber, Jeffrey G. Andrews, Nihar Jindal

Institutions: Drexel University, The University of Texas at Austin, University of Minnesota

Language: English

Topic: Mobile Ad Hoc Networks

Subfield: Computer Networks and Communications

Field: Computer Science

Domain: Physical Sciences

SDG: Industry, innovation and infrastructure

Open Access status: green

Funder: National Science Foundation

Awards: Collaborative Research: Cognititve Ad Hoc Networks: Capacity Optimization Through Local Adaptation, Collaborative Research: Cognitive Ad Hoc Networks: Capacity Optimization Through Local Adaptation, Collaborative Research: Cognitive Ad Hoc Networks: Capacity Optimization Through Local Adaptation