This work proposes a distributed power allocation scheme for maximizing the energy efficiency in the uplink of non- cooperative small-cell networks based on orthogonal frequency- division multiple-access technology. This is achieved by modeling users as rational agents that engage in a non-cooperative game in which every user selects the power loading so as to maximize his own utility (the user’s throughput per Watt of transmit power) while satisfying minimum rate constraints. In this framework, we prove the existence of a Debreu equilibrium (also known as generalized Nash equilibrium) and we characterize the structure of the corresponding power allocation profile using techniques drawn from fractional programming. To attain this equilibrium in a distributed fashion, we also propose a method based on an iterative water-filling best response process. Numerical simulations are then used to assess the method’s convergence and the performance of its end-state as a function of the system parameters.

Energy-aware competitive link adaptation in small-cell networks

Giacomo Bacci;SANGUINETTI, LUCA
2014-01-01

Abstract

This work proposes a distributed power allocation scheme for maximizing the energy efficiency in the uplink of non- cooperative small-cell networks based on orthogonal frequency- division multiple-access technology. This is achieved by modeling users as rational agents that engage in a non-cooperative game in which every user selects the power loading so as to maximize his own utility (the user’s throughput per Watt of transmit power) while satisfying minimum rate constraints. In this framework, we prove the existence of a Debreu equilibrium (also known as generalized Nash equilibrium) and we characterize the structure of the corresponding power allocation profile using techniques drawn from fractional programming. To attain this equilibrium in a distributed fashion, we also propose a method based on an iterative water-filling best response process. Numerical simulations are then used to assess the method’s convergence and the performance of its end-state as a function of the system parameters.
2014
9783901882630
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11568/520074
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