论文标题

蓝色数据计算最大化6G空间空气 - 空 - 非事物网络

Blue Data Computation Maximization in 6G Space-Air-Sea Non-Terrestrial Networks

论文作者

Hassan, Sheikh Salman, Tun, Yan Kyaw, Saad, Walid, Han, Zhu, Hong, Choong Seon

论文摘要

非事物网络(NTN),包括空间和空气平台,是即将到来的第六代(6G)蜂窝网络的关键组成部分。同时,由于用于国防,研究,娱乐活动,国内和国际贸易的海洋运输,海上网络的交通近年来大大增长。在本文中,研究了海上无线网络中对沟通和计算的无缝和可靠需求。考虑了两种类型的船用用户设备(UES),即低 - 安德滕纳的增益和高度安德滕纳的增益。加权总和最大化的联合任务计算和时间分配问题被提出为混合企业线性编程(MILP)。目的是设计一种算法,该算法使网络能够有效地向无人机(UAV)提供回程资源,并将色调任务卸载到Leo卫星以获取蓝色数据(即Marine用户的数据)。为了解决这一MILP,提出了基于弯管和原始分解的解决方案。 Bender将MILP分解为二进制任务决策的主要问题和连续时间分配的子问题。此外,原始分解涉及子问题中的耦合约束。最后,数值结果表明,所提出的算法在多项式时间计算复杂性中提供了海上UES的覆盖需求,并实现了近乎最佳的解决方案。

Non-terrestrial networks (NTN), encompassing space and air platforms, are a key component of the upcoming sixth-generation (6G) cellular network. Meanwhile, maritime network traffic has grown significantly in recent years due to sea transportation used for national defense, research, recreational activities, domestic and international trade. In this paper, the seamless and reliable demand for communication and computation in maritime wireless networks is investigated. Two types of marine user equipment (UEs), i.e., low-antenna gain and high-antenna gain UEs, are considered. A joint task computation and time allocation problem for weighted sum-rate maximization is formulated as mixed-integer linear programming (MILP). The goal is to design an algorithm that enables the network to efficiently provide backhaul resources to an unmanned aerial vehicle (UAV) and offload HUEs tasks to LEO satellite for blue data (i.e., marine user's data). To solve this MILP, a solution based on the Bender and primal decomposition is proposed. The Bender decomposes MILP into the master problem for binary task decision and subproblem for continuous-time resource allocation. Moreover, primal decomposition deals with a coupling constraint in the subproblem. Finally, numerical results demonstrate that the proposed algorithm provides the maritime UEs coverage demand in polynomial time computational complexity and achieves a near-optimal solution.

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