Data Service Maximization in Space-Air-Ground Integrated 6G Networks

Fuente: arXiv
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Autori principali: Ei, Nway Nway, Kim, Kitae, Tun, Yan Kyaw, Han, Zhu, Hong, Choong Seon
Natura: Preprint
Pubblicazione: 2024
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author Ei, Nway Nway
Kim, Kitae
Tun, Yan Kyaw
Han, Zhu
Hong, Choong Seon
author_facet Ei, Nway Nway
Kim, Kitae
Tun, Yan Kyaw
Han, Zhu
Hong, Choong Seon
contents Integrating terrestrial and non-terrestrial networks has emerged as a promising paradigm to fulfill the constantly growing demand for connectivity, low transmission delay, and quality of services (QoS). This integration brings together the strengths of the reliability of terrestrial networks, broad coverage and service continuity of non-terrestrial networks like low earth orbit satellites (LEOSats), etc. In this work, we study a data service maximization problem in space-air-ground integrated network (SAGIN) where the ground base stations (GBSs) and LEOSats cooperatively serve the coexisting aerial users (AUs) and ground users (GUs). Then, by considering the spectrum scarcity, interference, and QoS requirements of the users, we jointly optimize the user association, AU's trajectory, and power allocation. To tackle the formulated mixed-integer non-convex problem, we disintegrate it into two subproblems: 1) user association problem and 2) trajectory and power allocation problem. We formulate the user association problem as a binary integer programming problem and solve it by using the Gurobi optimizer. Meanwhile, the trajectory and power allocation problem is solved by the deep deterministic policy gradient (DDPG) method to cope with the problem's non-convexity and dynamic network environments. Then, the two subproblems are alternately solved by the proposed block coordinate descent algorithm. By comparing with the baselines in the existing literature, extensive simulations are conducted to evaluate the performance of the proposed framework.
format Preprint
id arxiv_https___arxiv_org_abs_2405_19771
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Data Service Maximization in Space-Air-Ground Integrated 6G Networks
Ei, Nway Nway
Kim, Kitae
Tun, Yan Kyaw
Han, Zhu
Hong, Choong Seon
Networking and Internet Architecture
Signal Processing
Integrating terrestrial and non-terrestrial networks has emerged as a promising paradigm to fulfill the constantly growing demand for connectivity, low transmission delay, and quality of services (QoS). This integration brings together the strengths of the reliability of terrestrial networks, broad coverage and service continuity of non-terrestrial networks like low earth orbit satellites (LEOSats), etc. In this work, we study a data service maximization problem in space-air-ground integrated network (SAGIN) where the ground base stations (GBSs) and LEOSats cooperatively serve the coexisting aerial users (AUs) and ground users (GUs). Then, by considering the spectrum scarcity, interference, and QoS requirements of the users, we jointly optimize the user association, AU's trajectory, and power allocation. To tackle the formulated mixed-integer non-convex problem, we disintegrate it into two subproblems: 1) user association problem and 2) trajectory and power allocation problem. We formulate the user association problem as a binary integer programming problem and solve it by using the Gurobi optimizer. Meanwhile, the trajectory and power allocation problem is solved by the deep deterministic policy gradient (DDPG) method to cope with the problem's non-convexity and dynamic network environments. Then, the two subproblems are alternately solved by the proposed block coordinate descent algorithm. By comparing with the baselines in the existing literature, extensive simulations are conducted to evaluate the performance of the proposed framework.
title Data Service Maximization in Space-Air-Ground Integrated 6G Networks
topic Networking and Internet Architecture
Signal Processing
url https://arxiv.org/abs/2405.19771