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To maximize the objective function (LC × BRC/DC), CMRP selects MRs one by one among all the MR candidate locations.
Assume that the user locations and the MR candidate locations satisfy the geographic and RF constraints.
Input: user location V, demand q i | i ∈ V, MR candidate locations M c, and IGW location IGW.
In this way, the objective function picks MR candidate locations that largely adds to the backbone capacity, more users' demand coverage, and lower deployment cost.
First, given a user demand vector, we can use some existing IGW selection scheme, such as the one given in [9], to place an IGW at one of MR candidate locations.
Given internetwork demand q i, ∀i ∈ V, MR candidate locations V ', and the price of an MR and the price of a pair of directional antennas, the goal of MRP is to deploy MRs and directional antennas to meet users' traffic demand with minimum cost.
Similar(51)
Next, the BS polls all MR candidates on the feasibility of the connection by sending a MIH_N2N_HO_Query_Resources.response.response
Based on these results, we further selected the MR candidates.
Finally, we found 42 TFs as MR candidates.
Finally, the two sets of MR candidates that were selected in terms of the specificity and the coverage were compared, to define the final MR candidates.
As a result, 108 TFs were identified as the MR candidates in Table 3.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com