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Meanwhile, CCIs were assumed to be subject to Nakagami-m fading channels to compute outage probability, error probability and ergodic capacity which were investigated in [16], and over Nakagami-m fading channels, the performance of CSI in AF multi-hop relaying networks under the impact of CCI was considered [17].
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For computing outage probability of direct transmission between source and destination, the received SINR at the destination is represented as γ D = P S h S D 2 ∑ k ∈ Φ S f k 2 P k D + σ D 2 (29).
For the same reason, cloud computing outages are considered newsworthy.
Worldwide computer outage apparently!
Then, using (30) and (37), we can compute the outage probability of the distributed CF as follows.
SIR samples at a given distance from the central BS are recorded in order to compute the outage probability.
To compute the outage, the pdf of SNR is to be obtained first through the inverse MT approach.
In the next theorem we compute the outage exponents for (30) and show that they match with the exponents of the upper bound.
We compute the outage probability, for mobile stations located at any distance from their serving BS, by using a fluid model network that considers the cellular network as a continuum of BS.
As it is very time consuming to compute the outage capacity for relatively large system sizes (even using Conjecture 1), we will use the centralized WCMS performance as a coarse estimate of the lower bound of the outage performance of the distributed schemes in our discussions hereafter.
Although the derived expressions compute the outage for any values of γ ¯ 1 and γ ¯ 2, we limit the discussion to two special cases, i.e., the balanced links case ( γ ¯ 1 = γ ¯ 2, i.e., λ1=λ2) and the unbalanced links case ( γ ¯ 1 = 2 γ ¯ 2, i.e., 2λ1=λ2).
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com