Decision-Oriented Communications: Application to Energy-Efficient Resource Allocation

Hang Zou (1) , Chao Zhang (1) , Samson Lasaulce (1) , Lucas Saludjian (2) , Patrick Panciatici (2)

1 L2S - Laboratoire des signaux et systèmes
2 RTE - Réseau de Transport d'Electricité [Paris]

In this paper, we introduce the problem of decision-oriented communications, that is, the goal of the source is to send the right amount of information in order for the intended destination to execute a task. More specifically, we restrict our attention to how the source should quantize information so that the destination can maximize a utility function which represents the task to be executed only knowing the quantized information. For example, for utility functions under the form u (x; g), x might represent a decision in terms of using some radio resources and g the system state which is only observed through its quantized version Q(g). Both in the case where the utility function is known and the case where it is only observed through its realizations, we provide solutions to determine such a quantizer. We show how this approach applies to energy-efficient power allocation. In particular, it is seen that quantizing the state very roughly is perfectly suited to sum-rate-type function maximization, whereas energy-efficiency metrics are more sensitive to imperfections.

Mots clés: Quantization; Resource Allocation; Learning; Neural Networks; Energy-Efficiency

Domaines: Apprentissage [cs.LG]; Réseau de neurones [cs.NE]; Optimisation et contrôle [math.OC]; Réseaux et télécommunications [cs.NI]

Hang Zou, Chao Zhang, Samson Lasaulce, Lucas Saludjian, Patrick Panciatici. Decision-Oriented Communications: Application to Energy-Efficient Resource Allocation. The 6th International Conference on Wireless Networks and Mobile Communications (WINCOM’18), Oct 2018, Marrakesh, Morocco. ⟨10.1109/wincom.2018.8629632⟩. ⟨hal-02289317⟩