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This yields a distinctive problem structure where long term average variables are determined by the expectation of a not necessarily concave functional of the resource allocation functions.
In this article, we consider the two resource allocation functions for maximizing the total service quality.
These restrictions define a set of admissible resource allocation functions that we denote as P : = { p : p ( h ) ∈ P ( h ), for all h ∈ ℋ }. (19).
In general, problems in optimal wireless networking are such that the Lagrangian maximizer resource allocation functions p are unique to within a set of zero measure.
If these points belong tho Y there exist respective resource allocation functions p ∈ P and p ′ ∈ P such that y = E f 1 ( h, p ( h ) ), y ′ = E f 1 ( h, p ′ ( h ) ). (47).
As we observed after (65) the computation of Lagrangian maximizing ergodic limits and resource allocation functions can be separated as can the computation of resource allocation values corresponding to different fading channel realizations.
Similar(52)
In addition, the resource allocation function is concerned with intangible assets such as goodwill, patents, workers, and brand names.
This section illustrates our approach by first presenting the design of the resource allocation function.
The computation of the resource allocation function in (67) can be further separated.
Consequently, it is adequate to refer to the set p : = { p ( h ) } h ∈ ℋ of all resource allocations as the resource allocation function.
Once the eNB has collected the CQIs for the entire bandwidth, it schedules resources for each user according to its resource allocation function.
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