Your English writing platform
Discover LudwigExact(60)
The purpose of capacity maximization is to maximize the data transmission rate sum, which is directly related with the CR transmission power on each sub-channel.
To maximize the multiple nodes CR network system, the capacity maximization problem (18) can be rewritten as in (25), in which Opt C i is the optimal channel set selected by STi according to the channel selection criteria.
The channel capacity maximization problem is now changed to the choice of the maximal number of real, non-negative values γ i - 1 i k subject to the power constraint ∑ k = 1 M γ i - 1 i k = snr i.
Capacity maximization and cycle length minimization problems are considered.
We consider two problems: network capacity maximization and network balancing.
Person capacity maximization has been used as an objective for the integrated optimization method.
Outer approximation algorithm (OAA) is proposed to solve capacity maximization problem.
The existing UPPA strategies focusing on capacity maximization or user fairness completely neglect this extremely critical tradeoff.
Capacity maximization, cycle length minimization, and delay minimization problems are formulated to optimize the operation of a roundabout.
With the objective of capacity maximization, the power optimization of D2D sub-system is considered, taking into account quality of service (QoS) requirement.
Based on system capacity maximization, an improved particle swarm optimization (PSO) algorithm is proposed, which is used to search for a global optimal solution in d-dimension space.
Write better and faster with AI suggestions while staying true to your unique style.
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