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The transmission threshold is therefore predicted analytically based on the corresponding saddle-node bifurcation.
Therefore, a specific user is scheduled if its best channel is greater than the transmission threshold.
For the optimized α ∗ →, the corresponding transmission threshold vector κ ∗ → = [ κ N ∗ … κ 1 ∗ ] can be computed using (11) and vice versa.
A transmission threshold κ i is defined as the minimum short-term fading value allowing for scheduling a packet (virtual user) with state i.
The DL/UL joint probability is that the transmission of the leader and the transmission of a member are performed within the DL coverage threshold and the UL transmission threshold.
The optimized transmission threshold vector is found using a recursive procedure explained in the following: 1. Start the optimization procedure for N=2 such that the optimization is a scalar problem and we only need to find the threshold κ N since κ 1=0. 2.
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Next, we would like to optimize the transmission thresholds.
The energy in (7) is not a convex function of the transmission thresholds.
Next, we state a few fundamental properties of these transmission thresholds.
In the following, we discuss two heuristic optimization techniques to compute transmission thresholds.
e The state in SA refers to the configuration of the system, i.e. the current transmission thresholds.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com