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Energy-Aware Resource Optimization for Improved URLLC in Multi-hop Integrated Aerial Terrestrial Networks

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Energy-Aware Resource Optimization for Improved URLLC in Multi-hop Integrated Aerial Terrestrial Networks. / Awais, Muhammad; Pervaiz, Haris; Jamshed, Muhammad Ali et al.
In: IEEE Transactions on Green Communications and Networking, Vol. 8, No. 1, 31.03.2024, p. 252-264.

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Awais M, Pervaiz H, Jamshed MA, Yu W, Ni Q. Energy-Aware Resource Optimization for Improved URLLC in Multi-hop Integrated Aerial Terrestrial Networks. IEEE Transactions on Green Communications and Networking. 2024 Mar 31;8(1):252-264. Epub 2023 Nov 3. doi: 10.1109/tgcn.2023.3330018

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Awais, Muhammad ; Pervaiz, Haris ; Jamshed, Muhammad Ali et al. / Energy-Aware Resource Optimization for Improved URLLC in Multi-hop Integrated Aerial Terrestrial Networks. In: IEEE Transactions on Green Communications and Networking. 2024 ; Vol. 8, No. 1. pp. 252-264.

Bibtex

@article{01b4f952c4f5478e9b15bae69f3ab81f,
title = "Energy-Aware Resource Optimization for Improved URLLC in Multi-hop Integrated Aerial Terrestrial Networks",
abstract = "The development of futuristic wireless infrastructure necessitates low power consumption, high reliability, and massive connectivity. One of the most promising solutions to address these requirements is the integration of aerial base station (ABS) based communication systems that employ both in the air (aerial) and on the ground (terrestrial) components. This integration enhances line of sight connections, enabling the fulfillment of escalating quality-of-service (QoS) demands. This article examines the problem of resource allocation in ABS assisted multi-hop wireless networks. We investigate a joint optimization problem that involves subcarrier (SC) assignment, power allocation, and blocklength allocation, subject to delay, reliability, and QoS constraints to improve the sum-rate under the finite blocklength (FBL) regime. We propose an approach for SC allocation and selection of cooperative ABSs based on matching theory. Subsequently, we employ an alternating optimization method to propose a novel bisection-based low-complexity adaptation (BLCA) algorithm to optimize the resource allocation policy. This algorithm includes a two-step projected gradient descent-based strategy to optimize the power allocation on each SC using dynamic and geometric programming. Furthermore, we examine flexible blocklength and power allocation use cases under the next generation of multiple access techniques. Monte-Carlo simulations validate that the proposed algorithmic solution significantly achieves a near-optimal solution while requiring 1600 times less computational cost compared to benchmarks in its counterparts.",
keywords = "Computer Networks and Communications, Renewable Energy, Sustainability and the Environment",
author = "Muhammad Awais and Haris Pervaiz and Jamshed, {Muhammad Ali} and Wenjuan Yu and Qiang Ni",
year = "2024",
month = mar,
day = "31",
doi = "10.1109/tgcn.2023.3330018",
language = "English",
volume = "8",
pages = "252--264",
journal = "IEEE Transactions on Green Communications and Networking",
issn = "2473-2400",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
number = "1",

}

RIS

TY - JOUR

T1 - Energy-Aware Resource Optimization for Improved URLLC in Multi-hop Integrated Aerial Terrestrial Networks

AU - Awais, Muhammad

AU - Pervaiz, Haris

AU - Jamshed, Muhammad Ali

AU - Yu, Wenjuan

AU - Ni, Qiang

PY - 2024/3/31

Y1 - 2024/3/31

N2 - The development of futuristic wireless infrastructure necessitates low power consumption, high reliability, and massive connectivity. One of the most promising solutions to address these requirements is the integration of aerial base station (ABS) based communication systems that employ both in the air (aerial) and on the ground (terrestrial) components. This integration enhances line of sight connections, enabling the fulfillment of escalating quality-of-service (QoS) demands. This article examines the problem of resource allocation in ABS assisted multi-hop wireless networks. We investigate a joint optimization problem that involves subcarrier (SC) assignment, power allocation, and blocklength allocation, subject to delay, reliability, and QoS constraints to improve the sum-rate under the finite blocklength (FBL) regime. We propose an approach for SC allocation and selection of cooperative ABSs based on matching theory. Subsequently, we employ an alternating optimization method to propose a novel bisection-based low-complexity adaptation (BLCA) algorithm to optimize the resource allocation policy. This algorithm includes a two-step projected gradient descent-based strategy to optimize the power allocation on each SC using dynamic and geometric programming. Furthermore, we examine flexible blocklength and power allocation use cases under the next generation of multiple access techniques. Monte-Carlo simulations validate that the proposed algorithmic solution significantly achieves a near-optimal solution while requiring 1600 times less computational cost compared to benchmarks in its counterparts.

AB - The development of futuristic wireless infrastructure necessitates low power consumption, high reliability, and massive connectivity. One of the most promising solutions to address these requirements is the integration of aerial base station (ABS) based communication systems that employ both in the air (aerial) and on the ground (terrestrial) components. This integration enhances line of sight connections, enabling the fulfillment of escalating quality-of-service (QoS) demands. This article examines the problem of resource allocation in ABS assisted multi-hop wireless networks. We investigate a joint optimization problem that involves subcarrier (SC) assignment, power allocation, and blocklength allocation, subject to delay, reliability, and QoS constraints to improve the sum-rate under the finite blocklength (FBL) regime. We propose an approach for SC allocation and selection of cooperative ABSs based on matching theory. Subsequently, we employ an alternating optimization method to propose a novel bisection-based low-complexity adaptation (BLCA) algorithm to optimize the resource allocation policy. This algorithm includes a two-step projected gradient descent-based strategy to optimize the power allocation on each SC using dynamic and geometric programming. Furthermore, we examine flexible blocklength and power allocation use cases under the next generation of multiple access techniques. Monte-Carlo simulations validate that the proposed algorithmic solution significantly achieves a near-optimal solution while requiring 1600 times less computational cost compared to benchmarks in its counterparts.

KW - Computer Networks and Communications

KW - Renewable Energy, Sustainability and the Environment

U2 - 10.1109/tgcn.2023.3330018

DO - 10.1109/tgcn.2023.3330018

M3 - Journal article

VL - 8

SP - 252

EP - 264

JO - IEEE Transactions on Green Communications and Networking

JF - IEEE Transactions on Green Communications and Networking

SN - 2473-2400

IS - 1

ER -