1 research outputs found
A Satisfactory Power Control for 5G Self-Organizing Networks
SmallCells are deployed in order to enhance the network performance by
bringing the network closer to the user. However, as the number of low power
nodes grows increasingly, the overall energy consumption of the SmallCells base
stations cannot be ignored. A relevant amount of energy could be saved through
several techniques, especially power control mechanisms. In this paper, we are
concerned with energy aware self organizing networks that guarantee a
satisfactory performance. We consider satisfaction equilibria, mainly the
efficient satisfaction equilibrium (ESE), to ensure a target quality of service
(QoS) and save energy. First, we identify conditions of existence and
uniqueness of ESE under a stationary channel assumption. We fully characterize
the ESE and prove that, whenever it exists, it is a solution of a linear
system. Moreover, we define satisfactory Pareto optimality and show that, at
the ESE, no player can increase its QoS without degrading the overall
performance. Under a fast fading channel assumption, as the robust satisfaction
equilibrium solution is very restrictive, we propose an alternative solution
namely the long term satisfaction equilibrium, and describe how to reach this
solution efficiently. Finally, in order to find satisfactory solution per all
users, we propose fully distributed strategic learning schemes based on
Banach-Picard, Mann and Bush Mosteller algorithms, and show through simulations
their qualitative properties. fully distributed strategic learning schemes
based on Banach Picard, Mann and Bush Mosteller algorithms, and show through
simulations their qualitative properties