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In this paper a novel graph based approach to the self coordination of robotic Mobile Ad-hoc NETworks (MANETs) to be used in disaster scenarios is presented.
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In this paper, we target the self-coordination problem in a small cell network.
For the self-coordination frameworks based on coordination game and 3GPP approaches.
An improved model predictive control strategy with power self-coordination is put forward.
The self-coordination framework aims then at founding a Nash equilibrium through the coordination game, maximizing the average reward.
We now further analyze the results provided by the independent implementation of ICIC and CCO, in comparison to the results obtained when the self-coordination framework is active.
This is referred to in 3rd Generation Partnership Project (3GPP) as a SON conflict, which needs to be handled by means of a self-coordination framework.
When executing the two SON functions in parallel, conflicts may arise, so we need the support of a self-coordination function.
This is why we consider that they are appropriate to model the problems that the self-coordination function has to face.
The simulation experiments showed the effectiveness of the self-coordination approach in terms of system performance by achieving a good compromise among conflicting actions.
Electromyography can provide information about muscle function within the gait cycle, and the timing of the muscles as they work in self-coordination [17].
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