Resource allocation of 5G network by exploiting particle swarm optimization

Waleed, Syed; Ullah, Inam; Khan, Wali Ullah; Rehman, Ateeq Ur; Rahman, Taj; Li, Shanbin

doi:10.1007/s42044-021-00091-5

Cited by 9 publications

(3 citation statements)

References 34 publications

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“…Paper [ 79 ] unveils a groundbreaking approach to energy-efficient resource allocation in 5G networks, capitalizing on the integration of passive reflectors to bolster connectivity, particularly in areas marred by physical obstructions. This initiative is a significant leap in the ongoing efforts to refine resource allocation strategies in cognitive hybrid RF/VLC systems, promising advancements in network capacity and user mobility.…”

Section: Hybrid Systems Reviewmentioning

confidence: 99%

A Review of Cognitive Hybrid Radio Frequency/Visible Light Communication Systems for Wireless Sensor Networks

Miranda,

Barriquello,

Reguera

et al. 2023

Sensors

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The development and growth of Wireless Sensor Networks (WSNs) is significantly propelled by advances in Radio Frequency (RF) and Visible Light Communication (VLC) technologies. This paper endeavors to present a comprehensive review of the state-of-the-art in cognitive hybrid RF-VLC systems for WSNs, emphasizing the critical task of seamlessly integrating Cognitive Radio Sensor Networks (CRSNs) and VLC technologies. The central challenge addressed is the intricate landscape of this integration, characterized by notable trade-offs between performance and complexity, which escalate with the addition of more devices and increased data rates. This scenario necessitates the development of advanced cognitive radio strategies, potentially facilitated by Machine Learning (ML) and Deep Learning (DL) approaches, albeit introducing new complexities such as the necessity for pre-training with extensive datasets. The review scrutinizes the fundamental aspects of CRSNs and VLC, spotlighting key areas like Energy Efficient Resource Allocation, Industrial Scenarios, and Energy Harvesting, and explores the synergistic amalgamation of these technologies as a promising pathway for enhanced spectrum utilization and network performance. By delving into the integration of cognitive radio technology with visible light, this study furnishes valuable insights into the potential for innovative applications in wireless communication, presenting a balanced overview of the current advancements and prospective avenues in the field of cognitive hybrid RF/VLC systems.

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Section: Hybrid Systems Reviewmentioning

confidence: 99%

A Review of Cognitive Hybrid Radio Frequency/Visible Light Communication Systems for Wireless Sensor Networks

Miranda,

Barriquello,

Reguera

et al. 2023

Sensors

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show abstract

“…Moreover, the impact of the terrain profile on communication is addressed by proposing a three-dimensional (3D) propagation model for IoD2V communication to enhance the communication quality between IoD in the air and vehicles on the ground. Population-based metaheuristic search algorithms, such as particle swarm optimization (PSO) and anti colony (ACO), have been widely applied to various problems [18]. In this study, the proposed approach employs improved version of PSO (IPSO) algorithm for deployment, where the optimal deployment of IoD nodes is obtained by implementing IPSO.…”

Section: Introductionmentioning

confidence: 99%

3D Simulation Model for IoD-to-Vehicles Communication in IoD-assisted VANET

Ahmed

Sheltami

Mahmoud

et al. 2023

Preprint

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Vehicle ad-hoc networks (VANETs) have gradually emerged to enhance transportation information, entertainment, safety, and other services. However, such infrastructures have certain limitations, causing intermittent network disconnection. Further, in urban areas, terrain heights act as obstacles and hinder or attenuate transmitted signals. In this study, we propose a dynamic 3D internet of drones (IoD) collaborative communication approach for efficient VANET-assistance (3DIoDAV) by integrating the IoD network and VANET to support terrestrial communication. We model IoD locations as an optimization problem to optimize the IoD nodes in three-dimensional terrain. Improved particle swarm optimization is used to optimally deploy IoD nodes in 3D terrain for minimizing the number of isolated vehicles. The proposed approach considers the terrain profile influence on communication. Therefore, we propose a 3D propagation model for efficient IoD-to-vehicle (IoD2V) communication in 3D space. Experiments are performed based on the received signal from ground vehicles to examine the performance of the proposed model and the 3DIoDAV approach. Simulation results show different behaviors of IoD nodes in two-dimensional (2D) and 3D scenarios. Comparison with 2D VANET-assisted and IoDAV approaches demonstrates the proposed 3DIoDAV approach’s ability to detect terrain obstacles, which guarantees the dispatching of IoD nodes into the most appropriate locations in 3D space, thereby minimizing the impact of terrain obstacles on communication.

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“…Moreover, the impact of the terrain profile on communication is addressed by proposing a threedimensional (3D) propagation model for IoD2V communication to enhance the communication quality between IoD in the air and vehicles on the ground. Population-based metaheuristic search algorithms, such as particle swarm optimization (PSO) and ant colony (ACO), have been widely applied to various problems Waleed et al (2021). In this study, the proposed approach employs improved version of PSO (IPSO) algorithm for deployment, where the optimal deployment of IoD nodes is obtained by implementing IPSO.…”

Section: Introductionmentioning

confidence: 99%

3D simulation model for IoD-to-vehicles communication in IoD-assisted VANET

Ahmed,

Sheltami,

Mahmoud

et al. 2023

Front. Built Environ.

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Vehicle ad hoc networks (VANETs) have gradually emerged to enhance transportation information, entertainment, safety, and other services. However, such infrastructures have certain limitations, causing intermittent network disconnection. Further, in urban areas, terrain heights act as obstacles and hinder or attenuate transmitted signals. In this study, we propose a dynamic 3D internet of drones collaborative communication approach for efficient VANET-assistance (3DIoDAV) by integrating the IoD network and VANET to support terrestrial communication. We model IoD locations as an optimization problem to optimize the IoD nodes in three-dimensional terrain. Improved particle swarm optimization is used to optimally deploy IoD nodes in 3D terrain for minimizing the number of isolated vehicles. The proposed approach considers the terrain profile influence on communication. Therefore, we propose a 3D propagation model for efficient IoD-to-vehicle (IoD2V) communication in 3D space. Experiments are performed based on the received signal from ground vehicles to examine the performance of the proposed model and the 3DIoDAV approach. Simulation results show different behaviors of IoD nodes in two-dimensional (2D) and 3D scenarios. Comparison with 2D VANET-assisted and IoDAV approaches demonstrates the proposed 3DIoDAV approach’s ability to detect terrain obstacles, which guarantees the dispatching of IoD nodes into the most appropriate locations in 3D space, thereby minimizing the impact of terrain obstacles on communication.

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Resource allocation of 5G network by exploiting particle swarm optimization

Cited by 9 publications

References 34 publications

A Review of Cognitive Hybrid Radio Frequency/Visible Light Communication Systems for Wireless Sensor Networks

A Review of Cognitive Hybrid Radio Frequency/Visible Light Communication Systems for Wireless Sensor Networks

3D Simulation Model for IoD-to-Vehicles Communication in IoD-assisted VANET

3D simulation model for IoD-to-vehicles communication in IoD-assisted VANET

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