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| Content Provider | Springer Nature Link |
|---|---|
| Author | Nilsson, Thomas Jäntti, Riku |
| Copyright Year | 2013 |
| Abstract | In this paper, we study the characteristics of two different backoff schemes: one that maximizes the channel utilization and one that maximizes the probability of a successful transmission. Our results indicate that while the latter provides slightly lower channel utilization, its shape is much less sensitive to the number of contending nodes. That is, the channel utilization is kept almost constant for a very wide range of node densities if the backoff distribution has increasing shape. This motivates us to propose a simple heuristic backoff scheme called the Truncated Geometric Backoff Distribution (TGBD). We provide simple analytical expressions for the probability of a successful transmission and the channel utilization. We also show that the TGBD can easily be extended to support service differentiation by adjusting the window lengths, and we provide a simple approximation that gives the relative share of the capacity for a node in a priority class compared to nodes in other classes. This extended backoff scheme easily outperforms the much more complex Quality of Service (QoS) standard, IEEE802.11e EDCA. Finally, a two-stage backoff model, based on the TGBD, is proposed that further increases the probability of a successful transmission. Results indicate that the channel utilization is almost independent of the number of contending nodes. |
| Starting Page | 383 |
| Ending Page | 398 |
| Page Count | 16 |
| File Format | |
| ISSN | 10184864 |
| Journal | Telecommunication Systems |
| Volume Number | 56 |
| Issue Number | 3 |
| e-ISSN | 15729451 |
| Language | English |
| Publisher | Springer US |
| Publisher Date | 2013-08-17 |
| Publisher Place | Boston |
| Access Restriction | One Nation One Subscription (ONOS) |
| Subject Keyword | Stationary backoff distribution Performance modeling QoS IEEE 802.11 IEEE 802.11e Business Information Systems Computer Communication Networks Artificial Intelligence (incl. Robotics) Probability Theory and Stochastic Processes |
| Content Type | Text |
| Resource Type | Article |
| Subject | Electrical and Electronic Engineering |
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