End-to-End Channel Capacity of a Wireless Sensor Network Under Reachback

Muhammad U. Ilyas, Hayder Radha

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Many wireless sensor network applications will impose a many-to-one traffic flow pattern. This phenomena in communication networks is referred to as reachback. The higher volume of traffic in traffic hotspots, which usually form around the base station, limits the number of sensors that can participate in the formation of a wireless sensor network with a fixed per sensor data rate. To alleviate the effects of reachback, spatial correlation of sensor data has enabled the use of Slepian-Wolf coding as a compression technique to reduce the volume of traffic in sensor networks. Within a cluster, Slepian-Wolf coding is used to compress the sensor readings. Clusterheads then transmit the compressed sensor readings over the overlay network which is formed by all clusterheads. We develop an expression for the end-to-end (sensor-to-base station) channel capacity of such a wireless sensor network and observe the effect of variations in the number of clusterheads on end-to-end capacity.
Original languageEnglish
Title of host publication2006 40th Annual Conference on Information Sciences and Systems
PublisherIEEE
Pages1713-1718
Number of pages6
ISBN (Electronic)1424403502 (CD)
ISBN (Print)1424403499
DOIs
Publication statusPublished - 22 Jan 2007
Event2006 40th Annual Conference on Information Sciences and Systems - Princeton, NJ, USA
Duration: 22 Mar 200624 Mar 2006

Publication series

NameAnnual Conference on Information Sciences and Systems
PublisherIEEE
ISSN (Print)2837-0163
ISSN (Electronic)2837-178X

Conference

Conference2006 40th Annual Conference on Information Sciences and Systems
Period22/03/0624/03/06

Keywords

  • Channel capacity
  • Wireless sensor networks
  • Base stations
  • Telecommunication traffic
  • Routing
  • Frequency
  • Sensor phenomena and characterization
  • Scalability
  • Clustering algorithms
  • Communication networks

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