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b Simplified application profile using an access probability.
For this, if the user transmitted in the previous time slot, it decreases its current access probability and increases the access probability otherwise.
where p(i) is the access probability of user i given in (10).
For the first adaptive approach, the average access probability sharply decreases at the beginning.
We then presented the analysis of the average access probability for this scheme.
We can now express the access probability of user i as (10).
Figure 8 Probability of successful transmission per SU vs. SU channel access probability for five SUs. Figure 9 Probability of successful transmission per SU vs. SU channel access probability for ten SUs. Figure 10 Probability of collision among SUs vs. SU channel access probability for five SUs. Figure 11 Probability of collision among SUs vs. SU channel access probability for ten SUs.
In general, 1/K is modeled as the access probability of the contenders in a slot.
More specifically, we propose mechanisms to adaptively control the access probability at the users.
The resulting optimal access probability still shows low throughput, even in a slotted ALOHA.
Each user may have a transmission in a frame with probability p, called the access probability.
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