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We introduce a frequentist (non-Bayesian) method for model-based link prediction from link data in which (a) there may be unobserved links, and (b) an observed link is reliable, i.e., there are no observed links that are spurious.
However, it can provide an idea of how much a predicted link is reliable.
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And the network designer doesn't know in advance which links are reliable and which aren't.
We consider a strong failure model, in which links are reliable but nodes fail independently with probability q per round and never recover.
Links are reliable.
Links are reliable, and, thus, messages exchanged between any two correct processes are never lost, corrupted or duplicated.
In[16], the impact of heterogeneous backhauls is investigated for coherent CoMP transmission in the downlink of femtocells, assuming that both the wired and wireless backhaul links are reliable.
If j is correct, it will eventually receive m since the links are reliable and will deliver m in line 41.
This article assumes that the communication links are reliable, the network time is slotted and well synchronized, and the exchanged information is not quantized.
The RSs are placed in suitable locations, where the BS-to-RS links are reliable, so that the RSs can correctly decode the signals received from the BS.
Since the links are reliable and do not create messages, it follows that a message is delivered only if it was previously broadcasted (there is no creation of messages).
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com