A Collision Resolution Algorithm for Random Access Channels Using Multiple Transmission Levels

  • Walter Grote
  • Shivendra Panwar


Networks with random access protocols offer a fair access to all users, they also show a robustness towards node failures. These features make them an attractive solution for computer applications. A vast amount of present day networks work under this scheme, being Ethernet one of the most significant technological contributions in this area. Collision Resolution Protocols are a special kind of random access schemes, offering the advantage that stability of the network is guaranteed, provided that the average packet input rate does not exceed a given limit.

Throughput is defined as the number of successful transmissions in a given time period. Pippenger1 offered a non-constructive proof that a throughput of 1 is achievable in the limit if users are able to detect the number of transmissions involved in a collision. A constructive method to achieve a throughput of.532 was found by Georgiadis and Papantoni-Kazakos2, a result which was improved to.553 by Kessler and Sidi3 adding information to each of the transmitted packets. Panwar developed two constructive methods of achieving a throughput of 1 (in the limit) by means of multiple transmission powers4 and the use of detecting matrices5.

The purpose of this paper is to present a protocol that offers an interesting tradeoff when limited transmission power levels are permitted. Using this protocol, the designer is able to raise the achievable throughput to.553 by using 2 different transmission powers and to.578 choosing one of at most 3 selectable transmission powers. We also outline the method to achieve higher throughputs increasing the complexity of the transmitters. The scheme is applicable in today’s networks based on fiber optics and spread spectrum systems, where the number of simultaneous transmissions can be detected.


Transmission Power Arrival Rate Packet Arrival Throughput Performance Achievable Throughput 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer Science+Business Media New York 1994

Authors and Affiliations

  • Walter Grote
    • 1
  • Shivendra Panwar
    • 2
  1. 1.E.E.Dept.UTFSMValparaísoChile
  2. 2.E.E.Dept.Polytechnic UniversityBrooklynUSA

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