Age-Aware Utility Maximization in Relay-Assisted Wireless Powered Communication Networks.

Ning Luan,Ke Xiong,Gang Qu,Haina Zheng,Yu Zhang,Zhifei Zhang,Pingyi Fan

doi:10.3390/e23091177

Abstract

This article investigates a relay-assisted wireless powered communication network (WPCN), where the access point (AP) inspires the auxiliary nodes to participate together in charging the sensor, and then the sensor uses its harvested energy to send status update packets to the AP. An incentive mechanism is designed to overcome the selfishness of the auxiliary node. In order to further improve the system performance, we establish a Stackelberg game to model the efficient cooperation between the AP–sensor pair and auxiliary node. Specifically, we formulate two utility functions for the AP–sensor pair and the auxiliary node, and then formulate two maximization problems respectively. As the former problem is non-convex, we transform it into a convex problem by introducing an extra slack variable, and then by using the Lagrangian method, we obtain the optimal solution with closed-form expressions. Numerical experiments show that the larger the transmit power of the AP, the smaller the age of information (AoI) of the AP–sensor pair and the less the influence of the location of the auxiliary node on AoI. In addition, when the distance between the AP and the sensor node exceeds a certain threshold, employing the relay can achieve better AoI performance than non-relaying systems.

Highlights

With the large-scale deployment of the Internet of things (IoT) devices in applications such as environment surveillance and industrial control [1,2], status update systems that report real-time system information become increasingly more important
The auxiliary nodes are randomly placed between access point (AP) and sensor
We study a relay-assisted wireless powered communication network (WPCN) based on age of information (AoI) with a focus on the case when the auxiliary nodes are selfish

Summary

Introduction

With the large-scale deployment of the Internet of things (IoT) devices in applications such as environment surveillance and industrial control [1,2], status update systems that report real-time system information become increasingly more important. In such systems, it is required to make accurate decisions based on fresh information update and measurement of information freshness becomes necessary. For real-time update systems, the goal is to get status update information as fresh as possible, which can be considered as the minimization of AoI. The concept of age of information (AoI) was introduced as the time duration from the generation time of the latest received status update packet to the current time moment [3].

Methods

Results

Conclusion